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6. The method according to claim 1 , wherein the speech is processed in an environment having a speech recognizer software process and a logical command processor software process, wherein upon determination that an input needs additional processing at least a portion of an output of the speech recognizer software process is further processed by the logical command processor software process. | 6. The method according to claim 1 , wherein the speech is processed in an environment having a speech recognizer software process and a logical command processor software process, wherein upon determination that an input needs additional processing at least a portion of an output of the speech recognizer software process is further processed by the logical command processor software process. 7. The method according to claim 6 , wherein at least one non-linguistic implicit user input is employed as a cue to influence processing by the logical command processor, and at least one of a natural language analysis and a syntactic analysis are used by the logical command processor to determine a context of a speech input. | 0.885366 |
1. A method for rendering computer-generated display components associated with an application for display on a computer-enabled display surface, the method comprising the acts of: receiving a plurality of content descriptions from an application, the plurality of content descriptions including commands on how to draw a display component; storing the plurality of content descriptions in memory; receiving a drawing request from an application to graphically display application content; determining if the application content to be graphically displayed is stored as one or more of the plurality of content descriptions; when the drawing request is stored as one or more of the plurality of content descriptions, rendering, from the stored content description, display components that are representative of the application content to be graphically displayed and displaying the display components; and when the content description is not stored in memory, calling the application for a rasterized image representative of the application content to be graphically displayed and displaying the rasterized image. | 1. A method for rendering computer-generated display components associated with an application for display on a computer-enabled display surface, the method comprising the acts of: receiving a plurality of content descriptions from an application, the plurality of content descriptions including commands on how to draw a display component; storing the plurality of content descriptions in memory; receiving a drawing request from an application to graphically display application content; determining if the application content to be graphically displayed is stored as one or more of the plurality of content descriptions; when the drawing request is stored as one or more of the plurality of content descriptions, rendering, from the stored content description, display components that are representative of the application content to be graphically displayed and displaying the display components; and when the content description is not stored in memory, calling the application for a rasterized image representative of the application content to be graphically displayed and displaying the rasterized image. 8. The method of claim 1 , wherein application is operating on a first processing thread and wherein the rendering of the display components from the stored content description is performed by a rendering engine operating on a second processing thread, the second processing thread, wherein a nominal response time of the second processing thread is at least twice as fast as a nominal response time of the first processing thread. | 0.568097 |
28. The method of claim 27 , further comprising: determining, in the preemptive mode in the global thread, whether a global translation cache deletion event is pending prior to determining whether the binary translation has been enqueued for installation; scheduling, in the non-preemptive mode in the global thread, a local uninstall for each affected processor core of the multi-core processor in response to determining the global translation cache deletion event is pending; determining, in the non-preemptive mode in the binary translation scheduler, whether a local uninstall is pending for the processor core prior to determining whether the global thread is suspended; and performing, in the non-preemptive mode in the binary translation scheduler, the pending local uninstall in response to determining that the local uninstall is pending. | 28. The method of claim 27 , further comprising: determining, in the preemptive mode in the global thread, whether a global translation cache deletion event is pending prior to determining whether the binary translation has been enqueued for installation; scheduling, in the non-preemptive mode in the global thread, a local uninstall for each affected processor core of the multi-core processor in response to determining the global translation cache deletion event is pending; determining, in the non-preemptive mode in the binary translation scheduler, whether a local uninstall is pending for the processor core prior to determining whether the global thread is suspended; and performing, in the non-preemptive mode in the binary translation scheduler, the pending local uninstall in response to determining that the local uninstall is pending. 29. The method of claim 28 , wherein installing the binary translation into the global translation cache comprises: performing garbage collection, in the preemptive mode in the global thread, to recover global translation cache memory; and scheduling, in the non-preemptive mode in the global thread, a local uninstall for each affected processor core of the multi-core processor in response to performing the garbage collection. | 0.789154 |
28. A computer-readable memory device that includes programming instructions to control at least one processor, the computer-readable memory device comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms; instructions for calculating a second value representing variation of context in which the sequence occurs, where the variation of context in which the sequence occurs is calculated as a measure of entropy of the context of the sequence; instructions for identifying that the sequence is a semantic unit based on the first and second values; and instructions for outputting an indication that the sequence is a semantic unit. | 28. A computer-readable memory device that includes programming instructions to control at least one processor, the computer-readable memory device comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms; instructions for calculating a second value representing variation of context in which the sequence occurs, where the variation of context in which the sequence occurs is calculated as a measure of entropy of the context of the sequence; instructions for identifying that the sequence is a semantic unit based on the first and second values; and instructions for outputting an indication that the sequence is a semantic unit. 41. The computer-readable memory device of claim 28 , further including: instructions for applying one or more rules to the sequence, and where the instructions for identifying that the sequence is a semantic unit are further based at least in part on the application of the one or more rules. | 0.70519 |
7. A non-transitory medium storing instructions that, when performed by one or more computers, cause the one or more computers to perform operations comprising: identifying queries that each include (i) one or more first terms that are associated with a particular topic and (ii) one or more second terms, different than the one or more first terms, that are associated with a particular author; identifying web resources for which the particular author has been identified as an author; determining a quantity of selections of search results that (i) are generated in response to one or more of the queries and (ii) reference one or more of the web resources for which the particular author has been identified as an author; associating the particular author with the particular topic, as a topic-to-author association, when the quantity of selections satisfies a threshold that is associated with more than one selection; and using the topic-to-author association in ranking a search result, which references one or more of the web resources, that is generated in response to one or more subsequently received queries that includes one or more of the first terms that are associated with the particular topic. | 7. A non-transitory medium storing instructions that, when performed by one or more computers, cause the one or more computers to perform operations comprising: identifying queries that each include (i) one or more first terms that are associated with a particular topic and (ii) one or more second terms, different than the one or more first terms, that are associated with a particular author; identifying web resources for which the particular author has been identified as an author; determining a quantity of selections of search results that (i) are generated in response to one or more of the queries and (ii) reference one or more of the web resources for which the particular author has been identified as an author; associating the particular author with the particular topic, as a topic-to-author association, when the quantity of selections satisfies a threshold that is associated with more than one selection; and using the topic-to-author association in ranking a search result, which references one or more of the web resources, that is generated in response to one or more subsequently received queries that includes one or more of the first terms that are associated with the particular topic. 9. The medium of claim 7 , wherein the web resources are websites or webpages having respective associated web addresses. | 0.836088 |
11. The method of claim 1 , wherein the identifying of the set of the regions which are indistinguishable includes generating a collision list which lists the regions in the set together with their locations in the electronically stored document. | 11. The method of claim 1 , wherein the identifying of the set of the regions which are indistinguishable includes generating a collision list which lists the regions in the set together with their locations in the electronically stored document. 12. The method of claim 11 , wherein the generating of the collision list includes generating a plurality of collision lists, each list including locations of a plurality of regions which are indistinguishable from other regions in the set but which are distinguishable from regions in other sets. | 0.906991 |
8. A phone device comprising: a storage configured to store a registration table, in which phone numbers are associated with names of parties who own the phone numbers and each of the names is associated with a first language, with a second language, or with no valid language; and one or more processors coupled to the storage and configured to: in response to receiving a phone number, read a name of a party associated with the received phone number from the storage; responsive to the name associated with the first language, convert the name into voice data in the first language and output the voice data; responsive to the name associated with the second language, convert the name into voice data in the second language and output the voice data; responsive to the name associated with no valid language, convert the name into voice data in a default language and output the voice data, wherein the default language is one of the first language or the second language. | 8. A phone device comprising: a storage configured to store a registration table, in which phone numbers are associated with names of parties who own the phone numbers and each of the names is associated with a first language, with a second language, or with no valid language; and one or more processors coupled to the storage and configured to: in response to receiving a phone number, read a name of a party associated with the received phone number from the storage; responsive to the name associated with the first language, convert the name into voice data in the first language and output the voice data; responsive to the name associated with the second language, convert the name into voice data in the second language and output the voice data; responsive to the name associated with no valid language, convert the name into voice data in a default language and output the voice data, wherein the default language is one of the first language or the second language. 13. The phone device of claim 8 , wherein the first language is English and the second language is Spanish. | 0.796199 |
11. A method of personalizing a search of a document collection to a user, the method comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model, comprising: for each phrase of the query, accessing a related phrase bit vector for the phrase of the query, wherein each bit of the related phrase bit vector indicates the presence or absence of a second related phrase of the phrase of the query; determining from the related phrase bit vector which of the second related phrases are present in the user model; and forming a related phrase bit mask corresponding to the second related phrases that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. | 11. A method of personalizing a search of a document collection to a user, the method comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model, comprising: for each phrase of the query, accessing a related phrase bit vector for the phrase of the query, wherein each bit of the related phrase bit vector indicates the presence or absence of a second related phrase of the phrase of the query; determining from the related phrase bit vector which of the second related phrases are present in the user model; and forming a related phrase bit mask corresponding to the second related phrases that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. 12. The method of claim 11 , wherein weighting a plurality of scores of a corresponding plurality of the search results according to the identified one or more second related phrases, comprises: accessing a related phrase bit vector for a document and query phrase; and weighting the related phrase bit vector for the document using the related phrase bit mask. | 0.563978 |
1. A system for providing education-related alerts in an online learning environment, comprising: a watcher module to monitor an online learning environment comprising a plurality of users participating in online educational activities; an online database comprising a performance threshold and a time threshold for the online educational activities; an event module to receive a score for an assignment completed by one or more students in the online learning environment during a first time, to receive a further score for the same assignment completed by the student during a second time, to determine a score difference between the score and the further score, to determine a time difference between the first score and the second score, to apply the performance threshold to the score difference, to apply the time threshold to the time difference, and to determine an occurrence of suspected cheating when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; an alert module to generate an alert for the suspected cheating occurrence, comprising: a template module to select a template for the suspected cheating occurrence; a data entry module to populate the template with notification of the suspected cheating occurrence as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box that are filled by the data entry module; and an interactive element module to provide to recipients of the alert, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; a delivery module to provide the alert to one or more of the users as the recipients; and a processor to execute each of the modules, which are stored on a non-transitory computer-readable storage medium. | 1. A system for providing education-related alerts in an online learning environment, comprising: a watcher module to monitor an online learning environment comprising a plurality of users participating in online educational activities; an online database comprising a performance threshold and a time threshold for the online educational activities; an event module to receive a score for an assignment completed by one or more students in the online learning environment during a first time, to receive a further score for the same assignment completed by the student during a second time, to determine a score difference between the score and the further score, to determine a time difference between the first score and the second score, to apply the performance threshold to the score difference, to apply the time threshold to the time difference, and to determine an occurrence of suspected cheating when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; an alert module to generate an alert for the suspected cheating occurrence, comprising: a template module to select a template for the suspected cheating occurrence; a data entry module to populate the template with notification of the suspected cheating occurrence as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box that are filled by the data entry module; and an interactive element module to provide to recipients of the alert, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; a delivery module to provide the alert to one or more of the users as the recipients; and a processor to execute each of the modules, which are stored on a non-transitory computer-readable storage medium. 4. A system according to claim 1 , further comprising: a response module to automatically perform an action in response to the identified suspected cheating occurrence; and a notification module to provide at least one of the users with a notification of the response action. | 0.520987 |
16. A computer-implemented social media intelligence system comprising: a. a digital processor performing a computer program comprising executable instructions stored on a memory device; b. the computer program providing a social media intelligence application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; iv. a fourth software module conducting hierarchical clustering based on that distance metric; and vi. a fifth software module outputting a result associated with said hierarchical clustering. | 16. A computer-implemented social media intelligence system comprising: a. a digital processor performing a computer program comprising executable instructions stored on a memory device; b. the computer program providing a social media intelligence application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; iv. a fourth software module conducting hierarchical clustering based on that distance metric; and vi. a fifth software module outputting a result associated with said hierarchical clustering. 25. The system of claim 16 , wherein the result comprises a graphic visualization of the clusters. | 0.531794 |
54. A system for use with at least one document, the system comprising: a client device including a processor; a memory coupled to the processor; an input device coupled to the processor; and a display unit coupled to the processor; a scanner coupled to the processor; and at least one server coupled to the processor, the processor operating under a predetermined control program stored in the memory to generate a display on the display unit based on a hypertext mark-up language (HTML) document stored in the memory, the display generated by the HTML document including a document display portion, an index field portion, and a control portion separately defined in the display, the document display portion displaying document data received from a scanner, the document data generated by scanning the document with the scanner, the index field portion permitting index data to be input by a user via the input device for association with the document data, and the control portion including at least one control element operable by the user with the input device for use in generating at least a start scan signal to initiate scanning of the document with the scanner and for use in generating a send data signal with the input device to transmit the document data with the index data to the server over a network using a destination address from an address field of the display of the client device. | 54. A system for use with at least one document, the system comprising: a client device including a processor; a memory coupled to the processor; an input device coupled to the processor; and a display unit coupled to the processor; a scanner coupled to the processor; and at least one server coupled to the processor, the processor operating under a predetermined control program stored in the memory to generate a display on the display unit based on a hypertext mark-up language (HTML) document stored in the memory, the display generated by the HTML document including a document display portion, an index field portion, and a control portion separately defined in the display, the document display portion displaying document data received from a scanner, the document data generated by scanning the document with the scanner, the index field portion permitting index data to be input by a user via the input device for association with the document data, and the control portion including at least one control element operable by the user with the input device for use in generating at least a start scan signal to initiate scanning of the document with the scanner and for use in generating a send data signal with the input device to transmit the document data with the index data to the server over a network using a destination address from an address field of the display of the client device. 61. A system as claimed in claim 54 , wherein the control element can be operated by the user with the input device to select document data from among a plurality of scanned documents for display on the document display portion of the display. | 0.663596 |
12. The computer-implemented method of claim 11 further comprising matching the query to content residing in a database to generate the results from performing the query. | 12. The computer-implemented method of claim 11 further comprising matching the query to content residing in a database to generate the results from performing the query. 13. The computer-implemented method of claim 12 in which the database resides in a server in a network. | 0.879603 |
13. The method of claim 11 wherein using both explicit and implicit interpretations of a key assertion comprises, at least in part, considering likelihoods as correspond to the explicit and implicit interpretations. | 13. The method of claim 11 wherein using both explicit and implicit interpretations of a key assertion comprises, at least in part, considering likelihoods as correspond to the explicit and implicit interpretations. 14. The method of claim 13 wherein considering likelihoods as correspond to the explicit and implicit interpretations comprises, at least in part, according a likelihood advantage to an explicit interpretation of the key assertion. | 0.779716 |
1. A method comprising: computing, by a computer processor of a computing system, 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 a computed term frequency-inverse document frequency (tf-idf) associated with n-grams of an n-gram model of a domain, 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; indexing, by said computer processor executing said frequently occurring group of n-grams stored in a database cache storing said said deep parse output, 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. | 1. A method comprising: computing, by a computer processor of a computing system, 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 a computed term frequency-inverse document frequency (tf-idf) associated with n-grams of an n-gram model of a domain, 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; indexing, by said computer processor executing said frequently occurring group of n-grams stored in a database cache storing said said deep parse output, 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. 2. The method of claim 1 , wherein results of said verifying indicate that said specified text word sequence is available in said database cache, and wherein said method further comprises: retrieving, by said computer processor from said database cache, said specified text word sequence; and applying, by said computer processor, said specified text word sequence to a parse tree. | 0.707951 |
1. A method of presenting a data input interface, the method comprising: displaying a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation; displaying, by a data processing system, a separator within the text input field, wherein a first portion and a second portion are separated by the separator; receiving the first input to the single text input field to determine a selected operation which includes one of the first operation or the second operation, wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected; receiving a text input in the single text input field, the text input being displayable in the entire single text input field and performing the selected operation on the text input. | 1. A method of presenting a data input interface, the method comprising: displaying a single text input field which, through a first input to the text input field itself, can select between at least a first operation and a second operation; displaying, by a data processing system, a separator within the text input field, wherein a first portion and a second portion are separated by the separator; receiving the first input to the single text input field to determine a selected operation which includes one of the first operation or the second operation, wherein the first input comprises receiving a user input in either the first portion or the second portion of the text input field, wherein the first operation is selected if the user input is positioned in the first portion when the user input is received and wherein the second operation is selected if the user input is positioned in the second portion when the user input is received, wherein the first operation is a text search through a first source of data and wherein the second operation is either a file operation or a search operation that is different than the first operation, and wherein in response to the first input, the separator automatically disappears from the text input field and the first portion dominates the entire area of the text input field if the first operation is selected and the second portion dominates the entire area of the text input field if the second operation is selected; receiving a text input in the single text input field, the text input being displayable in the entire single text input field and performing the selected operation on the text input. 6. A method as in claim 1 further comprising: displaying a first identifier to identify the first operation and displaying a second identifier to identify the second operation. | 0.650774 |
23. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the steps of: a computer identifying a set of one or more terms related to a specific search query; wherein the set of one or more terms are not part of the specific search query; determining, for each term of the set of one or more terms, a third number of historical search queries, and adding said third number to a running total; wherein said third number is based on a count of those historical search queries that include both the specific search query and said each term; determining a ratio of said third number to the running total; obtaining a plurality of search results for the search query; determining that none of the results in the plurality of search results contain a particular term from the set of one or more terms; and generating a value representing a loss in variety for a set of results; wherein the set of results includes the plurality of search results, and wherein generating the value representing the loss in variety for the set of results is based at least in part on the ratio of said third number, for said each term of the set of one or more terms, to the running total; and reporting the value representing the loss in variety for the set of results. | 23. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the steps of: a computer identifying a set of one or more terms related to a specific search query; wherein the set of one or more terms are not part of the specific search query; determining, for each term of the set of one or more terms, a third number of historical search queries, and adding said third number to a running total; wherein said third number is based on a count of those historical search queries that include both the specific search query and said each term; determining a ratio of said third number to the running total; obtaining a plurality of search results for the search query; determining that none of the results in the plurality of search results contain a particular term from the set of one or more terms; and generating a value representing a loss in variety for a set of results; wherein the set of results includes the plurality of search results, and wherein generating the value representing the loss in variety for the set of results is based at least in part on the ratio of said third number, for said each term of the set of one or more terms, to the running total; and reporting the value representing the loss in variety for the set of results. 26. The computer-readable volatile or non-volatile medium of claim 23 , wherein generating the value representing the loss in variety of the set of results further comprises adding together the value representing the loss of variety for said each term in the set of one or more terms that is determined by: assigning a zero value if said each term is found in the set of results; or assigning a non-zero value, if the term is not found in the results, wherein the non-zero value is a function of the ratio of the third number of said each term to the running total. | 0.609421 |
14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod. | 14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod. 15. The spinal implant system of claim 14 wherein said deflection rod system is about parallel to the first horizontal rod. | 0.626934 |
11. A non-transitory computer program product for use with a computer, the non-transitory computer program product comprising a computer readable program code for evaluating a handwritten document, the computer readable program code is executable by a processor in a computing device to: identify a handwritten character in each of the one or more text fields in a digital image by applying a character recognition technique, wherein the digital image is obtainable by scanning of the handwritten document, wherein each of the one or more text fields are associated with a section, and wherein the one or more text fields have an associated predefined character type determinable based on the associated section; determine a character type of the identified handwritten character, wherein a character type of the identified character comprises at least one of a letter, a symbol, a number, or a special character; compare the character type of the handwritten character, identified from a text field of the one or more text fields, with the predefined character type associated with the text field; validate the character type of the identified handwritten character in each of the one or more text fields based on the comparison; and recommend the identified handwritten character for each of the one or more text fields, to a data entry user, based on the validation. | 11. A non-transitory computer program product for use with a computer, the non-transitory computer program product comprising a computer readable program code for evaluating a handwritten document, the computer readable program code is executable by a processor in a computing device to: identify a handwritten character in each of the one or more text fields in a digital image by applying a character recognition technique, wherein the digital image is obtainable by scanning of the handwritten document, wherein each of the one or more text fields are associated with a section, and wherein the one or more text fields have an associated predefined character type determinable based on the associated section; determine a character type of the identified handwritten character, wherein a character type of the identified character comprises at least one of a letter, a symbol, a number, or a special character; compare the character type of the handwritten character, identified from a text field of the one or more text fields, with the predefined character type associated with the text field; validate the character type of the identified handwritten character in each of the one or more text fields based on the comparison; and recommend the identified handwritten character for each of the one or more text fields, to a data entry user, based on the validation. 14. The non-transitory computer program product of claim 11 , wherein the recommendation is provided in a color different from the color of the handwritten character originally present in the handwritten document. | 0.5 |
5. A processor according to claim 1, wherein the means for defining a relative probability of occurrence includes means for recognizing a word of the sequence of words which is commonly confused with a different word, and means for substituting a tag of such different word in the tag sequence, such that the means for selecting a tag sequence of greatest relative probability determines if the tag of said different word has a greater relative probability of occurrence. | 5. A processor according to claim 1, wherein the means for defining a relative probability of occurrence includes means for recognizing a word of the sequence of words which is commonly confused with a different word, and means for substituting a tag of such different word in the tag sequence, such that the means for selecting a tag sequence of greatest relative probability determines if the tag of said different word has a greater relative probability of occurrence. 6. A processor according to claim 5, wherein the means for selecting a tag sequence of greatest relative probability of occurrence further includes means for identifying in order tag sequences having successively lesser relative probabilities of occurrence, thereby identifying a succession of next most probable tags for each word of the sequence, and wherein the means for further processing includes means for processing a said next most probable tag of a word in the event the most probable tag does not fit a correct parse of the sentence. | 0.762536 |
10. The method of claim 1 wherein a first hyperlink of the one or more hyperlinks identifies a search system, wherein the first hyperlink, when activated, causes a processor to access the search system. | 10. The method of claim 1 wherein a first hyperlink of the one or more hyperlinks identifies a search system, wherein the first hyperlink, when activated, causes a processor to access the search system. 11. The method of claim 10 wherein the first hyperlink is configured to include one or more of the extracted terms, and wherein the first hyperlink, when activated, causes the processor to access the search system using the one or more extracted terms. | 0.938675 |
9. A system, comprising: a data store storing advertisement selection data for a set of advertisements, the selection data specifying selections of the advertisements from search results pages for search queries; an advertisement management system comprising one or more processors configured to receive specified text and provide advertisements that are relevant to the specified text based on targeting keywords for the advertisements matching the specified text; and an ad-selection analysis subsystem coupled to the data store and the advertisement management system, the ad-selection analysis subsystem including one or more processors configured to perform operations including: creating clusters of terms and corresponding advertisements based on the advertisement selection data, each of the clusters including multiple corresponding advertisements and each of the corresponding advertisements in each cluster having a term vector that is within a threshold distance of each other term vector for other corresponding advertisements in the cluster, each term vector for a corresponding advertisement specifying the search queries for which the corresponding advertisement was both presented to a user and selected by the user, the term vector also specifying advertiser-designated keywords for the corresponding advertisement that triggered presentations of the corresponding advertisement, wherein at least one of the advertiser-designated keywords is not included in the search queries, and wherein creating the clusters comprises determining cluster vectors for the clusters, each cluster vector for a respective cluster being an aggregate representation of term vectors for each of multiple corresponding advertisements in the respective cluster; computing similarity measures between pairs of the clusters, each similarity measure for a pair of clusters being based on a distance between a cluster vector for a first cluster of the pair and a cluster vector for a second cluster of the pair; receiving a request for data identified as relevant to specified text; in response to the request: identifying, from the clusters, a particular cluster that includes a term matching the specified text; identifying, from the clusters, a co-relevant cluster for the particular cluster, the co-relevant cluster being identified based on the computed similarity measure between the particular cluster and the co-relevant cluster meeting a threshold similarity measure, the co-relevant cluster being a different cluster than the clusters that include the term matching the specified text; and providing data identified as relevant to the specified text, the data specifying at least one additional advertisement that is relevant to the specified text, the additional advertisement being one of the corresponding advertisements from the co-relevant cluster. | 9. A system, comprising: a data store storing advertisement selection data for a set of advertisements, the selection data specifying selections of the advertisements from search results pages for search queries; an advertisement management system comprising one or more processors configured to receive specified text and provide advertisements that are relevant to the specified text based on targeting keywords for the advertisements matching the specified text; and an ad-selection analysis subsystem coupled to the data store and the advertisement management system, the ad-selection analysis subsystem including one or more processors configured to perform operations including: creating clusters of terms and corresponding advertisements based on the advertisement selection data, each of the clusters including multiple corresponding advertisements and each of the corresponding advertisements in each cluster having a term vector that is within a threshold distance of each other term vector for other corresponding advertisements in the cluster, each term vector for a corresponding advertisement specifying the search queries for which the corresponding advertisement was both presented to a user and selected by the user, the term vector also specifying advertiser-designated keywords for the corresponding advertisement that triggered presentations of the corresponding advertisement, wherein at least one of the advertiser-designated keywords is not included in the search queries, and wherein creating the clusters comprises determining cluster vectors for the clusters, each cluster vector for a respective cluster being an aggregate representation of term vectors for each of multiple corresponding advertisements in the respective cluster; computing similarity measures between pairs of the clusters, each similarity measure for a pair of clusters being based on a distance between a cluster vector for a first cluster of the pair and a cluster vector for a second cluster of the pair; receiving a request for data identified as relevant to specified text; in response to the request: identifying, from the clusters, a particular cluster that includes a term matching the specified text; identifying, from the clusters, a co-relevant cluster for the particular cluster, the co-relevant cluster being identified based on the computed similarity measure between the particular cluster and the co-relevant cluster meeting a threshold similarity measure, the co-relevant cluster being a different cluster than the clusters that include the term matching the specified text; and providing data identified as relevant to the specified text, the data specifying at least one additional advertisement that is relevant to the specified text, the additional advertisement being one of the corresponding advertisements from the co-relevant cluster. 12. The system of claim 9 , wherein the ad-selection analysis subsystem is further configured to perform operations including: receiving a request for relevant resource keywords for resource text; identifying, from the clusters, relevant resource keywords for the resource text, the relevant resource keywords including at least one relevant term from a first cluster that includes a term matching the resource text and at least one relevant term from a co-relevant cluster for the first cluster, the co-relevant cluster being identified based on the computed similarity measure between the first cluster and the co-relevant cluster for the first cluster; and providing data specifying the relevant terms in response to the request. | 0.5 |
1. A method, implemented on a computer system, of executing an action on the computer system in response to high level information entered in the computer system, the computer system including a display screen and a pointer, the method comprising the following steps: (a) determining whether an assist function has been explicitly selected by interaction of the pointer with the display screen; (b) identifying one or more objects input into the computer system which are to be considered by the explicitly selected assist function, each of said objects having an object type recognized by the computer system including at least, persons, places, and particular actions; (c) comparing the one or more identified objects with a list of actions stored in the computer and available through the assist function, each action in said list specifying at least one action object and at least one other object of a type recognized by the computer system; (d) identifying at least one action available from the list of actions which includes at least one object of the same type as an object input in the computer system and identified in step (b); (e) selecting one action from the at least one action identified in step (d); and (f) executing the action selected in step (d). | 1. A method, implemented on a computer system, of executing an action on the computer system in response to high level information entered in the computer system, the computer system including a display screen and a pointer, the method comprising the following steps: (a) determining whether an assist function has been explicitly selected by interaction of the pointer with the display screen; (b) identifying one or more objects input into the computer system which are to be considered by the explicitly selected assist function, each of said objects having an object type recognized by the computer system including at least, persons, places, and particular actions; (c) comparing the one or more identified objects with a list of actions stored in the computer and available through the assist function, each action in said list specifying at least one action object and at least one other object of a type recognized by the computer system; (d) identifying at least one action available from the list of actions which includes at least one object of the same type as an object input in the computer system and identified in step (b); (e) selecting one action from the at least one action identified in step (d); and (f) executing the action selected in step (d). 2. The method of claim 1 wherein the step of determining whether an assist function has been explicitly selected comprises a step of determining whether an assist button or icon on said computer system has been selected. | 0.611957 |
11. An apparatus for managing financial information, comprising: a scanner for scanning various types of receipts of no predefined format, each said receipt containing expense information printed thereon; a computer in communication with said scanner, said computer receiving a scan of each said receipt, and processing said scan by collecting the expense information from the scan; and a display device in communication with said computer, wherein said computer organizes said expense information collected from each said scan by categorizing the expense information into one or more predetermined expense categories to obtain report information, wherein said report information for at least one of said predetermined categories is displayed on said display device. | 11. An apparatus for managing financial information, comprising: a scanner for scanning various types of receipts of no predefined format, each said receipt containing expense information printed thereon; a computer in communication with said scanner, said computer receiving a scan of each said receipt, and processing said scan by collecting the expense information from the scan; and a display device in communication with said computer, wherein said computer organizes said expense information collected from each said scan by categorizing the expense information into one or more predetermined expense categories to obtain report information, wherein said report information for at least one of said predetermined categories is displayed on said display device. 15. An apparatus as claimed in claim 11 , wherein each scan of said receipts is organized as an individual transaction so that the expense information obtained from each scanned receipt is able be individually viewed and edited. | 0.698016 |
13. A system for screening incoming data of a network, comprising: means for determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen the incoming data of the network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; means for creating a representation of the relationship including the cause interaction and the effect interaction; means for receiving a new rule to be inserted into the rule set; means for inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and means for determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set. | 13. A system for screening incoming data of a network, comprising: means for determining a relationship between a plurality of existing rules in a rule set of a rule based system used to screen the incoming data of the network, wherein the relationship includes a cause interaction and an effect interaction among the existing rules; means for creating a representation of the relationship including the cause interaction and the effect interaction; means for receiving a new rule to be inserted into the rule set; means for inserting a further relationship between the new rule and the existing rules into the representation to create a modified representation; and means for determining, based on the modified representation, if a conflict is created by insertion of the new rule in the rule set. 16. The system of claim 13 , wherein the rule set includes a parameter used to determine when the rule set is invoked. | 0.539588 |
1. An apparatus comprising: at least one processor; a memory coupled to the at least one processor; a composite application residing in the memory, the composite application including a plurality of components written in a plurality of different programming languages; a plurality of component interaction rules residing in the memory, each component interaction rule comprising at least one condition between components in different programming languages and at least one action to perform depending on whether the at least one condition is satisfied; and an application analysis mechanism residing in the memory and executed by the at least one processor, the application analysis mechanism generating an application model of the composite application, wherein the application model comprises: the plurality of components in the composite application separated into a plurality of categories according to programming language; and metadata that describes interaction between components in a first of the plurality of categories with components in a second of the plurality of categories; the application analysis mechanism analyzing the application model for conformance to the plurality of component interaction rules, and outputting results of analyzing the application model for conformance to the plurality of component interaction rules. | 1. An apparatus comprising: at least one processor; a memory coupled to the at least one processor; a composite application residing in the memory, the composite application including a plurality of components written in a plurality of different programming languages; a plurality of component interaction rules residing in the memory, each component interaction rule comprising at least one condition between components in different programming languages and at least one action to perform depending on whether the at least one condition is satisfied; and an application analysis mechanism residing in the memory and executed by the at least one processor, the application analysis mechanism generating an application model of the composite application, wherein the application model comprises: the plurality of components in the composite application separated into a plurality of categories according to programming language; and metadata that describes interaction between components in a first of the plurality of categories with components in a second of the plurality of categories; the application analysis mechanism analyzing the application model for conformance to the plurality of component interaction rules, and outputting results of analyzing the application model for conformance to the plurality of component interaction rules. 2. The apparatus of claim 1 wherein the at least one action comprises adding a warning to the results. | 0.569588 |
2. The method of claim 1 , further comprising: generating a pseudo-language build with the pseudo-translated locale-dependant code using the integrated build application; testing the pseudo-language build; and identifying at least one internationalization bug. | 2. The method of claim 1 , further comprising: generating a pseudo-language build with the pseudo-translated locale-dependant code using the integrated build application; testing the pseudo-language build; and identifying at least one internationalization bug. 7. The method of claim 2 , wherein the integrated build application comprises at least one resource file specific utility, and the locale-dependant code comprises at least one resource file. | 0.91016 |
1. A method of generating a score for a decision question comprising: receiving, from a first user, via an input device, a decision question comprising at least two choices; subsequently to receiving the decision question, presenting the decision question to at least one second user; subsequently to presenting the decision question, receiving: at least one secondary question; and for each secondary question, at least one recommendation of at least one of the choices of the decision question, the recommendation specifying a relationship between the secondary question and the recommended choice of the decision question; storing the received at least one secondary question and the received at least one recommendation; presenting the at least one secondary question to the first user; subsequently to presenting the at least one secondary question to the first user, receiving, from the first user, answers to at least a subset of the at least one secondary question; for each received answer, determining a score for at least one of the choices for the decision question, the score being based on the received answer and on at least one recommendation associated with the secondary question; subsequently to determining a score for each received answer, aggregating the determined scores; and subsequently to aggregating the determined scores, outputting an indication of the aggregated scores. | 1. A method of generating a score for a decision question comprising: receiving, from a first user, via an input device, a decision question comprising at least two choices; subsequently to receiving the decision question, presenting the decision question to at least one second user; subsequently to presenting the decision question, receiving: at least one secondary question; and for each secondary question, at least one recommendation of at least one of the choices of the decision question, the recommendation specifying a relationship between the secondary question and the recommended choice of the decision question; storing the received at least one secondary question and the received at least one recommendation; presenting the at least one secondary question to the first user; subsequently to presenting the at least one secondary question to the first user, receiving, from the first user, answers to at least a subset of the at least one secondary question; for each received answer, determining a score for at least one of the choices for the decision question, the score being based on the received answer and on at least one recommendation associated with the secondary question; subsequently to determining a score for each received answer, aggregating the determined scores; and subsequently to aggregating the determined scores, outputting an indication of the aggregated scores. 8. The method of claim 1 , further comprising, for at least a subset of the received recommendations, receiving a recommendation strength; and wherein determining a score comprises determining a score based on the received answer and at least one recommendation and recommendation strength associated with the secondary question. | 0.650864 |
6. A computer implemented method for providing categorized data, the method comprising: maintaining a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; mapping advertising content to at least one of the plurality of contexts using the at least one predefined concept; and storing the mapping of the advertising content to the at least one context in a database; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network. | 6. A computer implemented method for providing categorized data, the method comprising: maintaining a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; mapping advertising content to at least one of the plurality of contexts using the at least one predefined concept; and storing the mapping of the advertising content to the at least one context in a database; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network. 8. The method of claim 6 , wherein the advertising content is obtained from a manual entry based on user selection of one or more contexts. | 0.652016 |
1. A method of non-deterministic word generation from a noise source providing a bit flow, comprising: parallelizing, by a temporary storage device, the bit flow provided by the noise source to obtain first words, each first word having a first number of bits; applying, by a compression circuit, to said first words a compression function providing second words, each second word having a second number of bits, and, separately from applying to said first words a compression function, applying, by a diffusion/confusion circuit, to said first words a diffusion/confusion function providing third words, each third word having a third number of bits, the first words being input to the compression circuit and to the diffusion/confusion circuit in parallel; and selecting a second number of bits from an output of the diffusion/confusion circuit based on an output of the compression circuit, the selecting performed by a selection circuit, wherein the entropy per bit of the noise source is optimized by using the output of the compression circuit to select useful bits in the third words provided by the diffusion/confusion circuit, wherein a drift in the entropy of the noise source can be detected. | 1. A method of non-deterministic word generation from a noise source providing a bit flow, comprising: parallelizing, by a temporary storage device, the bit flow provided by the noise source to obtain first words, each first word having a first number of bits; applying, by a compression circuit, to said first words a compression function providing second words, each second word having a second number of bits, and, separately from applying to said first words a compression function, applying, by a diffusion/confusion circuit, to said first words a diffusion/confusion function providing third words, each third word having a third number of bits, the first words being input to the compression circuit and to the diffusion/confusion circuit in parallel; and selecting a second number of bits from an output of the diffusion/confusion circuit based on an output of the compression circuit, the selecting performed by a selection circuit, wherein the entropy per bit of the noise source is optimized by using the output of the compression circuit to select useful bits in the third words provided by the diffusion/confusion circuit, wherein a drift in the entropy of the noise source can be detected. 2. The method of claim 1 , wherein the diffusion/confusion function is a hash function, preferably selected from among functions SHA1 and MD5. | 0.553546 |
4. The method according to claim 3 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. | 4. The method according to claim 3 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. 6. The method according to claim 4 , comprising: weighting the second score signal, if one or both of: the at least one web page search result comprises one or more music-related terms; or the at least one web page search result comprises a music-related web page. | 0.927714 |
27. The computer system of claim 18 wherein the data further comprises processor executable code for: dividing a consolidated configuration model into the configuration sub-models. | 27. The computer system of claim 18 wherein the data further comprises processor executable code for: dividing a consolidated configuration model into the configuration sub-models. 28. The computer system of claim 27 wherein the code for dividing the consolidated configuration model into multiple configuration sub-models further comprises code for: dividing the configuration model so that complexity of each configuration sub-model allows processing using available data processing capabilities of the computer system while still representing the relationships included in the consolidated configuration model. | 0.861001 |
1. A computer-implemented method comprising: processing a query to identify a set of item listings, each item listing associated with an item or service being offered and assigned to a leaf-level category; determining a scope of the query based on a dictionary of queries or a length of the query when the query is not found in the dictionary; identifying one or more categories based on the scope of the query; and presenting a search results page with the item listings from the identified one or more categories. | 1. A computer-implemented method comprising: processing a query to identify a set of item listings, each item listing associated with an item or service being offered and assigned to a leaf-level category; determining a scope of the query based on a dictionary of queries or a length of the query when the query is not found in the dictionary; identifying one or more categories based on the scope of the query; and presenting a search results page with the item listings from the identified one or more categories. 4. The computer-implemented method of claim 1 wherein determining the scope of the query further comprises: determining the scope of the query using a number of keywords in the query. | 0.715992 |
1. A computer implemented method, comprising: identifying that each of a plurality of documents are mature based on one or more signals associated with the documents; in response to identifying the documents as mature: storing, via one or more networks, edits to the documents in at least one database for defining edit rules based on the edits, wherein the edits are from a plurality of users and are made via user interface input provided via applications executing on computing devices of the users, wherein each of the edits identifies one of a plurality of pre-edit phrases and an associated one of a plurality of post-edit phrases, and wherein each of a plurality of the edits is based on a user implemented change of the one of the pre-edit phrases to the one of the post-edit phrases in one of the plurality of mature documents; determining an edit rule pre-edit phrase based on a set of one or more of the pre-edit phrases identified by the edits; determining one or more edit rule post-edit phrases based on one or more of the post-edit phrases associated with the set of the one or more pre-edit phrases; defining an edit rule that associates the edit rule pre-edit phrase with the edit rule post-edit phrases; storing the edit rule for automatically determining, for a future phrase conforming to the edit rule pre-edit phrase, a rephrasing of the future phrase based on at least one of the edit rule post-edit phrases; after storing the edit rule: identifying a current document being edited by a given user via a given application of a given computing device of the given user, identifying that a given phrase in the current document conforms to the edit rule pre-edit phrase of the edit rule, in response to identifying that the given phrase conforms to the edit rule pre-edit phrase, determining a candidate rephrasing of the given phrase based on the edit rule, the determining comprising determining the candidate rephrasing based on a given one of the edit rule post-edit phrases of the edit rule, in response to user interface input provided at the given computing device, providing the candidate rephrasing of the given phrase for presentation to the user. | 1. A computer implemented method, comprising: identifying that each of a plurality of documents are mature based on one or more signals associated with the documents; in response to identifying the documents as mature: storing, via one or more networks, edits to the documents in at least one database for defining edit rules based on the edits, wherein the edits are from a plurality of users and are made via user interface input provided via applications executing on computing devices of the users, wherein each of the edits identifies one of a plurality of pre-edit phrases and an associated one of a plurality of post-edit phrases, and wherein each of a plurality of the edits is based on a user implemented change of the one of the pre-edit phrases to the one of the post-edit phrases in one of the plurality of mature documents; determining an edit rule pre-edit phrase based on a set of one or more of the pre-edit phrases identified by the edits; determining one or more edit rule post-edit phrases based on one or more of the post-edit phrases associated with the set of the one or more pre-edit phrases; defining an edit rule that associates the edit rule pre-edit phrase with the edit rule post-edit phrases; storing the edit rule for automatically determining, for a future phrase conforming to the edit rule pre-edit phrase, a rephrasing of the future phrase based on at least one of the edit rule post-edit phrases; after storing the edit rule: identifying a current document being edited by a given user via a given application of a given computing device of the given user, identifying that a given phrase in the current document conforms to the edit rule pre-edit phrase of the edit rule, in response to identifying that the given phrase conforms to the edit rule pre-edit phrase, determining a candidate rephrasing of the given phrase based on the edit rule, the determining comprising determining the candidate rephrasing based on a given one of the edit rule post-edit phrases of the edit rule, in response to user interface input provided at the given computing device, providing the candidate rephrasing of the given phrase for presentation to the user. 2. The method of claim 1 , wherein the one or more signals based on which at least one document of the mature documents is identified as mature include at least one of: a creation time of the document; an amount of time since the document was last modified; and a user associated with the document. | 0.565367 |
3. The method as claimed in claim 2 , wherein the one or more semantic clusters correspond to topics that occur in the first corpus but not in the second corpus. | 3. The method as claimed in claim 2 , wherein the one or more semantic clusters correspond to topics that occur in the first corpus but not in the second corpus. 4. The method as claimed in claim 3 , wherein at least one of said topics is expressed by at least two semantic graphs formed by linguistic analysis and from first and second sets of semantic clusters using different words and grammatical structures. | 0.890105 |
9. The method of claim 6 further comprising access means to said first and second tables. | 9. The method of claim 6 further comprising access means to said first and second tables. 12. The method of claim 9 wherein said access means providing a delete operation. | 0.968266 |
19. A non-transitory, tangible computer readable medium comprising: an executable computer program code configured to instruct a system to automatically optimize an information integration flow, the executable computer program code comprising the steps of: receiving a tool-specific input file representing a physical information integration flow; parsing the tool-specific input file to identify semantics of the physical information integration flow; creating a tool-agnostic input file containing rich semantics of at least one of datasets, implementations, schema, operators, database management systems, or ETL tools; transforming the tool-agnostic input file into an input directed acyclic graph (DAG); providing the input DAG to a quality objective (QoX) driven optimizer unit; and applying one or more heuristic algorithms to the input DAG to develop an optimum information integration flow design based on the rich semantics. | 19. A non-transitory, tangible computer readable medium comprising: an executable computer program code configured to instruct a system to automatically optimize an information integration flow, the executable computer program code comprising the steps of: receiving a tool-specific input file representing a physical information integration flow; parsing the tool-specific input file to identify semantics of the physical information integration flow; creating a tool-agnostic input file containing rich semantics of at least one of datasets, implementations, schema, operators, database management systems, or ETL tools; transforming the tool-agnostic input file into an input directed acyclic graph (DAG); providing the input DAG to a quality objective (QoX) driven optimizer unit; and applying one or more heuristic algorithms to the input DAG to develop an optimum information integration flow design based on the rich semantics. 20. The non-transitory, tangible computer readable medium of claim 19 , wherein the executable computer program code further comprises the steps of: choosing among one or more specific execution instances related to a dataset to be processed by the physical information integration flow; partitioning a dataset to be processed by the physical information integration flow based on schema properties; and optimizing the physical information integration flow based on implementation properties presented in the tool-agnostic input file. | 0.5 |
2. The method of claim 1 , further comprising: i) computing a total variance for sample values in the gesture; j) calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gesture, wherein the figure of merit is a measure of how well the gesture matched the catalog gesture; k) determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit; and l) taking action if the input gesture matches the one of the one or more catalog gesture. | 2. The method of claim 1 , further comprising: i) computing a total variance for sample values in the gesture; j) calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gesture, wherein the figure of merit is a measure of how well the gesture matched the catalog gesture; k) determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit; and l) taking action if the input gesture matches the one of the one or more catalog gesture. 13. The method of claim 2 , wherein the method is applied to a video game. | 0.836772 |
1. A method to be executed at least in part in a computing device for recognizing multiple semantic items from a single utterance, the method comprising: receiving a single utterance including at least two semantically distinct items from a user; performing a speech recognition operation on the single utterance to recognize a first item of the at least two semantically distinct items; determining a constraint based on the recognition of the first item; performing another speech recognition operation on the single utterance to recognize a second item of the at least two semantically distinct items based on the determined constraint, wherein performing the speech recognition operation includes obtaining a plurality of alternative values for the first item; providing the alternative values for the first item to the user; and receiving a user selection for one of the alternative values, wherein providing the alternative values to the user includes one of: a single step presentation that includes a combination of an alternative value for the first item and a value for the second item based on the alternative value for the first item selected according to a statistical language model; and a visual menu presentation that includes a listing of combinations of the alternative values for the first item and values for the second item based on the alternative values for the first item selected according to the statistical language model. | 1. A method to be executed at least in part in a computing device for recognizing multiple semantic items from a single utterance, the method comprising: receiving a single utterance including at least two semantically distinct items from a user; performing a speech recognition operation on the single utterance to recognize a first item of the at least two semantically distinct items; determining a constraint based on the recognition of the first item; performing another speech recognition operation on the single utterance to recognize a second item of the at least two semantically distinct items based on the determined constraint, wherein performing the speech recognition operation includes obtaining a plurality of alternative values for the first item; providing the alternative values for the first item to the user; and receiving a user selection for one of the alternative values, wherein providing the alternative values to the user includes one of: a single step presentation that includes a combination of an alternative value for the first item and a value for the second item based on the alternative value for the first item selected according to a statistical language model; and a visual menu presentation that includes a listing of combinations of the alternative values for the first item and values for the second item based on the alternative values for the first item selected according to the statistical language model. 7. The method of claim 1 , further comprising: providing the recognized first item to the user; receiving one of a user correction and a user confirmation for the provided first item; and determining the constraint based on one of the user corrected and user confirmed first item. | 0.68799 |
29. A computer program product comprising a non-transient computer-readable memory comprising computer-executable instructions for enterprise content management including integrating a plurality of applications and federating information, the instructions comprising: instructions for initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: receiving a request from a client system; and translating the request from the client system; and instructions for performing one or more high level validations; instructions for retrieving information from a mapping of a plurality of entities; and instructions for continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, wherein: at least one of the plurality of actions comprises at least one decision block, input or mapped process and where at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service. | 29. A computer program product comprising a non-transient computer-readable memory comprising computer-executable instructions for enterprise content management including integrating a plurality of applications and federating information, the instructions comprising: instructions for initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: receiving a request from a client system; and translating the request from the client system; and instructions for performing one or more high level validations; instructions for retrieving information from a mapping of a plurality of entities; and instructions for continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, wherein: at least one of the plurality of actions comprises at least one decision block, input or mapped process and where at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service. 39. The computer program product of claim 29 , wherein the instructions further comprise: instructions for mapping one or more repositories with one or more object types, thereby indicating that the one or more object types are included in the one or more repositories. | 0.532331 |
1. A system for mechanically reproducing language characters in a cursive form in accordance with the natural style calligraphy of said language, wherein a plurality of j cancatenation properties is associated with said natural style calligraphy, a selected combination of said cancatenation properties being applicable to each character of said language characters, said selected combination comprising an integral number of said concatenation properties equal in number from j to O where j is an integer; said system comprising; a. input means for inserting characters one at a time and for providing coded representations of characters which do concatenate and coded representations of characters which do not concatenate, b. said input means providing coded representations associated with spaces between groups of characters, c. decoder means for receiving said coded representations of said characters for providing output signals associated with said coded representation, d. said decoder means providing a first group of output signals associated with said coded representation of characters which do not concatenate, and a second group of output signals associated with said coded representation of characters which do concatenate, e. means responsive to said output signals from said decoder means for storing coded representations of a successive string of characters comprising a character under consideration, a preceding character and a following character, f. means for analyzing said stored coded representations of said successive string of characters according to the concatenation properties of said character under consideration, said preceding character and said following character, said analyzer means providing further coded representations whereby said further coded representations are representative of the applicable concatenation property, g. means for combining said coded representations from said input means with said further coded representations to provide a composite coded representation containing information corresponding to said character under consideration and its applicable concatenation property, and h. output means for receiving said composite coded representations for reproducing said characters with the natural style calligraphy. | 1. A system for mechanically reproducing language characters in a cursive form in accordance with the natural style calligraphy of said language, wherein a plurality of j cancatenation properties is associated with said natural style calligraphy, a selected combination of said cancatenation properties being applicable to each character of said language characters, said selected combination comprising an integral number of said concatenation properties equal in number from j to O where j is an integer; said system comprising; a. input means for inserting characters one at a time and for providing coded representations of characters which do concatenate and coded representations of characters which do not concatenate, b. said input means providing coded representations associated with spaces between groups of characters, c. decoder means for receiving said coded representations of said characters for providing output signals associated with said coded representation, d. said decoder means providing a first group of output signals associated with said coded representation of characters which do not concatenate, and a second group of output signals associated with said coded representation of characters which do concatenate, e. means responsive to said output signals from said decoder means for storing coded representations of a successive string of characters comprising a character under consideration, a preceding character and a following character, f. means for analyzing said stored coded representations of said successive string of characters according to the concatenation properties of said character under consideration, said preceding character and said following character, said analyzer means providing further coded representations whereby said further coded representations are representative of the applicable concatenation property, g. means for combining said coded representations from said input means with said further coded representations to provide a composite coded representation containing information corresponding to said character under consideration and its applicable concatenation property, and h. output means for receiving said composite coded representations for reproducing said characters with the natural style calligraphy. 2. A system as claimed in claim 1 wherein said concatenation properties are defined by three concatenation variables, one of said concatenation variables representative as to whether a character links or does not link, said other two concatenation variables each representative of the direction of a link and each corresponding to a respective side of said character. | 0.567266 |
28. A user-interface method of selecting and presenting to a first user a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of a second user learned from the second user selecting content of a second content system, the method comprising: receiving incremental input entered by the second user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the second user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the second user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the second user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the first user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the second user determined to be relevant to the content items of the first content system. | 28. A user-interface method of selecting and presenting to a first user a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of a second user learned from the second user selecting content of a second content system, the method comprising: receiving incremental input entered by the second user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the second user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the second user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the second user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the first user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the second user determined to be relevant to the content items of the first content system. 36. The method of claim 28 , wherein at least one of the incremental input and the subsequent incremental input are entered by the corresponding user on at least one of a telephone, a PDA, and a remote control. | 0.61168 |
1. A computer-implemented method of evaluating information confidence based on cognitive behavior indicators of a user, the method comprising: determining, by a processor, a system generated answer to a question in an active learning question and answer system, wherein the system generated answer includes a first answer confidence score for the system generated answer; querying a user for an answer to the question in the active learning question and answer system based on the first answer confidence score; receiving, by the processor, information from the user as an answer to the question in the active learning question and answer system; monitoring, by the processor, the user for one or more cognitive behavior indicators when the user is providing the information, wherein the one or more cognitive behavior indicators comprise one or more biometric measurements of the user at a time the information is provided by the user and measures of an influence of an external stimuli on the user at the time the information is provided by the user; determining, by the processor, a second answer confidence score for the information received from the user based on the one or more biometric measurements of the user and the measures of the influence of an external stimuli on the user; annotating, by the processor, the information with the cognitive behavior indicators, a user profile associated with the user, and the second answer confidence score; and updating the first answer confidence score based at least in part on the second answer confidence score. | 1. A computer-implemented method of evaluating information confidence based on cognitive behavior indicators of a user, the method comprising: determining, by a processor, a system generated answer to a question in an active learning question and answer system, wherein the system generated answer includes a first answer confidence score for the system generated answer; querying a user for an answer to the question in the active learning question and answer system based on the first answer confidence score; receiving, by the processor, information from the user as an answer to the question in the active learning question and answer system; monitoring, by the processor, the user for one or more cognitive behavior indicators when the user is providing the information, wherein the one or more cognitive behavior indicators comprise one or more biometric measurements of the user at a time the information is provided by the user and measures of an influence of an external stimuli on the user at the time the information is provided by the user; determining, by the processor, a second answer confidence score for the information received from the user based on the one or more biometric measurements of the user and the measures of the influence of an external stimuli on the user; annotating, by the processor, the information with the cognitive behavior indicators, a user profile associated with the user, and the second answer confidence score; and updating the first answer confidence score based at least in part on the second answer confidence score. 3. The computer-implemented method of claim 1 , wherein the cognitive behavior indicator comprises one or more of user eye tracking, user typing speed, user heart rate, user breathing rate, user blink frequency, user skin conductance, electroencephalogram information, user body temperature, user perspiration quantity, user blood pressure and user amount of time elapsed during information input. | 0.659829 |
11. A navigation system comprising: a control unit including a processor for: calculating a position factor based on a point of interest term generated from a brand name or a standard industry code description of a categorized point of interest; generating a point of interest term from the brand name and the standard industry code description associated with an uncategorized point of interest; applying a statistical rule to the point of interest term from the uncategorized point of interest to generate a category score for the point of interest term; determining a normalized category score based on matching between the point of interest term from the categorized point of interest and the point of interest term from the uncategorized point of interest; generating a category identifier for the uncategorized point of interest; and a communication unit including microelectronic, coupled to the control unit, for transmitting the category identifier for display on a device. | 11. A navigation system comprising: a control unit including a processor for: calculating a position factor based on a point of interest term generated from a brand name or a standard industry code description of a categorized point of interest; generating a point of interest term from the brand name and the standard industry code description associated with an uncategorized point of interest; applying a statistical rule to the point of interest term from the uncategorized point of interest to generate a category score for the point of interest term; determining a normalized category score based on matching between the point of interest term from the categorized point of interest and the point of interest term from the uncategorized point of interest; generating a category identifier for the uncategorized point of interest; and a communication unit including microelectronic, coupled to the control unit, for transmitting the category identifier for display on a device. 20. The system as claimed in claim 11 wherein the control unit is for multiplying the term frequency with a category uniqueness factor, a term length factor, and a position factor. | 0.877281 |
9. The system of claim 1 , further comprising: paginating the webpage based on said hierarchical structure; and adapting the paginated webpage for presentation on a device having device capabilities based on the hierarchical structure of the webpage and the device capabilities. | 9. The system of claim 1 , further comprising: paginating the webpage based on said hierarchical structure; and adapting the paginated webpage for presentation on a device having device capabilities based on the hierarchical structure of the webpage and the device capabilities. 10. The system of claim 9 , wherein the paginating the webpage based on said hierarchical structure further comprises generating an index for one or more pages of the paginated webpage. | 0.94572 |
3. The method of claim 1 , further comprising: providing a plurality of display attributes for each of the plurality of words or phrases, wherein the plurality of display attributes comprises at least a display alignment, a character color or a background color. | 3. The method of claim 1 , further comprising: providing a plurality of display attributes for each of the plurality of words or phrases, wherein the plurality of display attributes comprises at least a display alignment, a character color or a background color. 4. The method of claim 3 , wherein each of the plurality of display attributes is individually enabled for each of the respective plurality of words or phrases. | 0.952339 |
48. The system of claim 47 , wherein the data object is then serialized by said serializer component, for transmitting parsed message data to another system. | 48. The system of claim 47 , wherein the data object is then serialized by said serializer component, for transmitting parsed message data to another system. 49. The system of claim 48 , wherein the data object is itself not specific to a particular wire format. | 0.943662 |
21. The non-transitory computer-readable storage medium of claim 20 , wherein: the initial query, the modification to the initial query, and the user-submitted query, are all received from a particular user; and storing the association is performed on a user-specific basis, thereby causing the association between the initial query and the modification to the initial query to be maintained relative to said particular user; and determining whether the query association database contains an association for the user-submitted query involves determining whether the query association database contains an association for the user-submitted query for the particular user. | 21. The non-transitory computer-readable storage medium of claim 20 , wherein: the initial query, the modification to the initial query, and the user-submitted query, are all received from a particular user; and storing the association is performed on a user-specific basis, thereby causing the association between the initial query and the modification to the initial query to be maintained relative to said particular user; and determining whether the query association database contains an association for the user-submitted query involves determining whether the query association database contains an association for the user-submitted query for the particular user. 22. The non-transitory computer-readable storage medium of claim 21 , wherein the particular user is associated with a first identification, and wherein the step of storing an association comprises storing an association that establishes a relationship between the initial query, the user-submitted query, and the first identification. | 0.857769 |
15. A system for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the system comprising: a collection of subsets of content items associated with corresponding strings of one or more unresolved keystrokes for overloaded keys, the subsets of content items being ranked and associated with the content items based on an ordering criteria so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; and a computer memory comprising instructions for causing a computer system to: receive a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items select and present the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receive subsequent unresolved keystrokes from the user and form a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; and select and present the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting and presenting the subset of content items that is associated with the first unresolved keystroke and selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes selects the subset of content items using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. | 15. A system for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the system comprising: a collection of subsets of content items associated with corresponding strings of one or more unresolved keystrokes for overloaded keys, the subsets of content items being ranked and associated with the content items based on an ordering criteria so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; and a computer memory comprising instructions for causing a computer system to: receive a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items select and present the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receive subsequent unresolved keystrokes from the user and form a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; and select and present the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting and presenting the subset of content items that is associated with the first unresolved keystroke and selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes selects the subset of content items using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. 24. The system of claim 15 wherein content items having similar descriptors are grouped into the same subsets of content items. | 0.557924 |
17. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor, cause the at least one processor to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language corresponding to the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word. | 17. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor, cause the at least one processor to: capture behavioral data for a plurality of users with respect to a plurality of terms; obtain a rule set for stemming in a language corresponding to the plurality of terms; obtain a word to be stemmed; in response to determining that only one rule of the rule set is to be used to stem the obtained word, stemming the obtained word using only one rule; or in response to determining that more than one rule of the rule set is to be used in stemming the obtained word: determine a set of forms of the obtained word; determine an output set of forms corresponding to the set of forms, wherein each rule of the more than one rule corresponds to one of the forms in the output set of forms, determine, based at least in part upon the captured behavioral data, a relative measurement value of each form in the set of output forms, and select, based at least in part upon the relative measurement values, at least one form in the output set of forms to be used as a stem for the obtained word. 22. The non-transitory computer-readable storage medium of claim 17 , further cause the at least one processor to generate a whitelist for a plurality of words not having an appropriate rule in the rule set. | 0.578474 |
1. A printing apparatus comprising: a printing engine; a print processor operatively connected to said printing engine; and a user interface operatively connected to said print processor, said user interface receiving instructions to retrieve a remote electronic document maintained within a print queue of an external server, said user interface displaying a full-printing menu option and a second printing menu option, based on said user interface receiving selection of said full-printing menu option, said printing engine printing all of said remote electronic document without pausing to print a fully printed document, and based on said user interface receiving selection of said second printing menu option: said printing engine beginning printing sample pages of said remote electronic document and pausing printing said remote electronic document to print a partially printed document, said sample pages comprising non-consecutive pages of said remote electronic document appearing at various locations within said remote electronic document; said user interface displaying an inquiry regarding whether said partially printed document is acceptable after said pausing printing; said printing engine printing a remainder of said remote electronic document based on said user interface receiving input that said partially printed document is acceptable, said remainder comprising all pages of said remote electronic document other than said sample pages; and said print processor canceling printing said remainder of said remote electronic document and resetting said print queue of said external server to indicate that said remote electronic document has not been printed, based on said user interface receiving input that said partially printed document is unacceptable. | 1. A printing apparatus comprising: a printing engine; a print processor operatively connected to said printing engine; and a user interface operatively connected to said print processor, said user interface receiving instructions to retrieve a remote electronic document maintained within a print queue of an external server, said user interface displaying a full-printing menu option and a second printing menu option, based on said user interface receiving selection of said full-printing menu option, said printing engine printing all of said remote electronic document without pausing to print a fully printed document, and based on said user interface receiving selection of said second printing menu option: said printing engine beginning printing sample pages of said remote electronic document and pausing printing said remote electronic document to print a partially printed document, said sample pages comprising non-consecutive pages of said remote electronic document appearing at various locations within said remote electronic document; said user interface displaying an inquiry regarding whether said partially printed document is acceptable after said pausing printing; said printing engine printing a remainder of said remote electronic document based on said user interface receiving input that said partially printed document is acceptable, said remainder comprising all pages of said remote electronic document other than said sample pages; and said print processor canceling printing said remainder of said remote electronic document and resetting said print queue of said external server to indicate that said remote electronic document has not been printed, based on said user interface receiving input that said partially printed document is unacceptable. 2. The printing apparatus according to claim 1 , said printing engine printing other print requests between said pausing printing said remote electronic document and said printing said remainder of said remote electronic document. | 0.789607 |
1. A computer-implemented method comprising: maintaining a list of music sites, wherein a music site is a web site that provides access to music or music information; receiving a query; obtaining a plurality of search results responsive to the query, the search results being results from a search of web resources on the Internet; determining a count of the plurality of search results that identify resources on respective music sites that are in the list of music sites; determining that the query is a music query including determining that the count of the plurality of search results that identify resources on respective music sites satisfies a threshold; in response to determining that the query is a music query, obtaining music data for a song responsive to the query, where the music data comprises a Uniform Resource Locator (URL) of song content of the song on the Internet; generating a music answer box for the query, where the music answer box comprises the music data and a link to the URL of the song content; and providing the music answer box in addition to two or more of the search results. | 1. A computer-implemented method comprising: maintaining a list of music sites, wherein a music site is a web site that provides access to music or music information; receiving a query; obtaining a plurality of search results responsive to the query, the search results being results from a search of web resources on the Internet; determining a count of the plurality of search results that identify resources on respective music sites that are in the list of music sites; determining that the query is a music query including determining that the count of the plurality of search results that identify resources on respective music sites satisfies a threshold; in response to determining that the query is a music query, obtaining music data for a song responsive to the query, where the music data comprises a Uniform Resource Locator (URL) of song content of the song on the Internet; generating a music answer box for the query, where the music answer box comprises the music data and a link to the URL of the song content; and providing the music answer box in addition to two or more of the search results. 2. The method of claim 1 , further comprising: maintaining a lyrics index database that associates song lyrics with lyrics resources that include the song lyrics, wherein determining that the query is a music query further comprises determining that a lyrics resource of the lyrics index database includes song lyrics that match one or more terms of the query. | 0.596222 |
11. A system comprising: one or more computers configured to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. | 11. A system comprising: one or more computers configured to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. 17. The system of claim 11 , wherein the analysis includes treating a particular text string as a feature with a reduced clustering weight if the particular text string has been identified to be processed differently. | 0.547537 |
30. The method of claim 29 wherein the target-directed pricing enables the seller efficiently to manage inventory and adjust price based on inventory conditions. | 30. The method of claim 29 wherein the target-directed pricing enables the seller efficiently to manage inventory and adjust price based on inventory conditions. 31. A method claimed in claim 30 wherein a persistent price is avoided during promotion by using a configurable duty cycle of pricing variation during such promotion. | 0.93813 |
3. The method of claim 1 , wherein the parsing of the design of the electronic circuit includes traversing through nodes of the data structure to one of: preserve and discard a node thereof based on at least one keyword. | 3. The method of claim 1 , wherein the parsing of the design of the electronic circuit includes traversing through nodes of the data structure to one of: preserve and discard a node thereof based on at least one keyword. 4. The method of claim 3 , further comprising at least one of: determining a root node of the data structure; distinguishing between a node identifiable as useful and a node identifiable as useless progressively from a lowest level of the data structure to the highest level thereof; and identifying at least one path of the data structure for pruning of the connectivity descriptors. | 0.879763 |
1. A method for producing a structured document, the method comprising: converting an unstructured document into an output presentation in a first display, the output presentation including a number of displayable objects and respective decoration attributes about each of the displayable objects; receiving a definition file including document type definitions (DTD) related to the unstructured document; generating a tree structure in a second display showing hierarchical relationships of document elements from the DTD; displaying in a second display next to the first display a DTD structure from the DTD showing structures of the document elements and the tree structure showing the hierarchical relationships of the document elements based on a root element; associating one of the document elements in the tree structure with one of the displayable objects in the output presentation in the first display; and generating a modified output presentation including association information of each one of the displayable objects being associated with one of the definitions in the definition file. | 1. A method for producing a structured document, the method comprising: converting an unstructured document into an output presentation in a first display, the output presentation including a number of displayable objects and respective decoration attributes about each of the displayable objects; receiving a definition file including document type definitions (DTD) related to the unstructured document; generating a tree structure in a second display showing hierarchical relationships of document elements from the DTD; displaying in a second display next to the first display a DTD structure from the DTD showing structures of the document elements and the tree structure showing the hierarchical relationships of the document elements based on a root element; associating one of the document elements in the tree structure with one of the displayable objects in the output presentation in the first display; and generating a modified output presentation including association information of each one of the displayable objects being associated with one of the definitions in the definition file. 4. The method of claim 1 , wherein the definition file includes a structure for document elements, each corresponding to one of the displayable objects in the output presentation. | 0.61373 |
1. A computerized method for identifying needy queries for which additional responsive content is needed, the method comprising: receiving a query comprising one or more terms; retrieving a plurality of content items identified as responsive to the query, the one or more content items forming a result set and ranked according to one or more ranking techniques; determining an amount of the plurality of content items in the result set; electronically generating, via a processing device, a score for the plurality of ranked content items identified as responsive to the query; calculating an average of the scores associated with the plurality of ranked content items identified as responsive to the query; determining whether the query is needy based upon the amount of the plurality of content items in the result set and performing a comparison of the calculated average of the scores with respect to a needy query score threshold; wherein a query is determined to be a needy query on the basis of the amount of the plurality of content items in the result set being an inadequate response to the query, on the basis of the calculated average of scores associated with the plurality of content items failing to meet the needy query threshold; and retrieving additional responsive content items in addition to the plurality of content items in the result set for the needy query. | 1. A computerized method for identifying needy queries for which additional responsive content is needed, the method comprising: receiving a query comprising one or more terms; retrieving a plurality of content items identified as responsive to the query, the one or more content items forming a result set and ranked according to one or more ranking techniques; determining an amount of the plurality of content items in the result set; electronically generating, via a processing device, a score for the plurality of ranked content items identified as responsive to the query; calculating an average of the scores associated with the plurality of ranked content items identified as responsive to the query; determining whether the query is needy based upon the amount of the plurality of content items in the result set and performing a comparison of the calculated average of the scores with respect to a needy query score threshold; wherein a query is determined to be a needy query on the basis of the amount of the plurality of content items in the result set being an inadequate response to the query, on the basis of the calculated average of scores associated with the plurality of content items failing to meet the needy query threshold; and retrieving additional responsive content items in addition to the plurality of content items in the result set for the needy query. 3. The method of claim 1 wherein generating a score for the plurality of ranked content items identified as responsive to the query comprises generating a score indicating a degree to which the plurality of ranked content items are responsive to the query. | 0.572647 |
1. A method for the speech recognition of sentences that are put together from several words of a given vocabulary, wherein a limited number of permissible sentences are predetermined, the permissible sentences having a syntax and the words of the given vocabulary having syntactical positions in the permissible sentences, said method comprising the steps of: (a) providing an N-gram speech model into which the syntax of the permissible sentences is integrated, the speech model being such that words which recur in the permissible sentences in different syntactical positions are distinguished from one another in the speech model, according to syntactical constraints, by indexes that are valid for the syntactical positions of the words which recur; (b) conducting a recognition process; and (c) while the recognition process of step (b) is in progress, examining only a matching of an actual speech signal with permissible N-gram word sequences that are determined through consideration of the syntactical constraints by consideration of the indexes of the speech model. | 1. A method for the speech recognition of sentences that are put together from several words of a given vocabulary, wherein a limited number of permissible sentences are predetermined, the permissible sentences having a syntax and the words of the given vocabulary having syntactical positions in the permissible sentences, said method comprising the steps of: (a) providing an N-gram speech model into which the syntax of the permissible sentences is integrated, the speech model being such that words which recur in the permissible sentences in different syntactical positions are distinguished from one another in the speech model, according to syntactical constraints, by indexes that are valid for the syntactical positions of the words which recur; (b) conducting a recognition process; and (c) while the recognition process of step (b) is in progress, examining only a matching of an actual speech signal with permissible N-gram word sequences that are determined through consideration of the syntactical constraints by consideration of the indexes of the speech model. 3. A method according to claim 1, wherein step (a) comprises providing a bigram model as the speech model. | 0.685153 |
1. An extended online analytical apparatus for one or more data sources wherein each data source has a data format, comprising: an aggregator that aggregates one or more pieces of data from the one or more data sources to generate aggregated pieces of data; a virtual schema generator that generates an XML-based virtual schema from the aggregated pieces of data without a data warehouse and without a data warehouse data model, wherein the virtual schema is a multidimensional data model generated based on the data format of the one or more data sources; and an analytical cube generator that generates an eXtensible on-line analytical processing (XOLAP) cube by executing commands from a declarative language against the virtual schema. | 1. An extended online analytical apparatus for one or more data sources wherein each data source has a data format, comprising: an aggregator that aggregates one or more pieces of data from the one or more data sources to generate aggregated pieces of data; a virtual schema generator that generates an XML-based virtual schema from the aggregated pieces of data without a data warehouse and without a data warehouse data model, wherein the virtual schema is a multidimensional data model generated based on the data format of the one or more data sources; and an analytical cube generator that generates an eXtensible on-line analytical processing (XOLAP) cube by executing commands from a declarative language against the virtual schema. 4. The apparatus of claim 1 further comprising one or more adaptors associated with one or more data sources, each adaptor converting one or more pieces of data from a particular data source having a particular data format into a common data format. | 0.674157 |
13. An apparatus according to claim 8, further comprising means for instructing said display means to display one of the inputted characters and the graphic patterns corresponding to the character patterns at one time. | 13. An apparatus according to claim 8, further comprising means for instructing said display means to display one of the inputted characters and the graphic patterns corresponding to the character patterns at one time. 17. An apparatus according to claim 13, wherein the graphic patterns corresponding to the character patterns comprise dot patterns based on vector data. | 0.922684 |
9. A computer readable storage medium containing a program which, when executed, performs an operation, comprising: receiving a database query; determining at least one data element required for executing the database query; identifying, from a plurality of storage devices, a storage device storing the determined at least one data element; adding the received database query to a first queue of a plurality of queues each having a plurality of queued queries, each of the queues having a predefined association with a respective storage device of the plurality of storage devices, wherein the predefined association of the first queue is a first predefined association with the identified storage device storing the determined at least one data element, wherein each of the queued queries of a given of one of the queues requires one or more data elements stored in the respective storage device in order to be executed, wherein each queued query is received during a specified time period, and wherein the specified time period is selected according to an energy consumption objective; and after the specified time period: dispatching the plurality of queued queries from the first queue; retrieving, from the respective storage device, data elements required for executing the dispatched queries; and executing the dispatched queries, using the retrieved data elements as inputs. | 9. A computer readable storage medium containing a program which, when executed, performs an operation, comprising: receiving a database query; determining at least one data element required for executing the database query; identifying, from a plurality of storage devices, a storage device storing the determined at least one data element; adding the received database query to a first queue of a plurality of queues each having a plurality of queued queries, each of the queues having a predefined association with a respective storage device of the plurality of storage devices, wherein the predefined association of the first queue is a first predefined association with the identified storage device storing the determined at least one data element, wherein each of the queued queries of a given of one of the queues requires one or more data elements stored in the respective storage device in order to be executed, wherein each queued query is received during a specified time period, and wherein the specified time period is selected according to an energy consumption objective; and after the specified time period: dispatching the plurality of queued queries from the first queue; retrieving, from the respective storage device, data elements required for executing the dispatched queries; and executing the dispatched queries, using the retrieved data elements as inputs. 11. The computer readable storage medium of claim 9 , wherein the storage device is a hard-disk drive. | 0.550128 |
1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. | 1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. 8. The system of claim 1 , wherein the user feedback comprises chatspeak in the second language. | 0.587252 |
15. The at least one non-transitory computer-readable storage medium of claim 14 , wherein the identifying comprises: identifying a plurality of tokens of the text input of a same text normalization type for which a contrastive stress pattern is to be applied; and identifying the at least one token to be rendered with contrastive stress from among the plurality of tokens of the same text normalization type. | 15. The at least one non-transitory computer-readable storage medium of claim 14 , wherein the identifying comprises: identifying a plurality of tokens of the text input of a same text normalization type for which a contrastive stress pattern is to be applied; and identifying the at least one token to be rendered with contrastive stress from among the plurality of tokens of the same text normalization type. 20. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the at least one token to be rendered with contrastive stress is identified based at least in part on an order of the plurality of tokens in the text input. | 0.869552 |
10. A method comprising, by one or more computer systems: building a profile for an end user based on collectively learned preferences of the end user, the profile comprising a set of keywords and a weight assigned to each keyword in the set of keywords; receiving a translated query for sensor data associated with a specific sensor among a plurality of sensor data from a plurality of sensors, the plurality of sensor data being indexed according to a multi-dimensional array, one or more first ones of the dimensions comprising time and one or more second ones of the dimensions comprising one or more pre-determined sensor-data attributes, the translated query having been translated from an original query for particular sensor data, the translated query comprising an unique resource locator specifying the specific sensor of the plurality of sensors, the translated query comprising one or more values for one or more of the dimensions of the multi-dimensional array; generating one or more multi-dimensional-array filters based on the translated query; determining that the translated query is not accurate; modifying the translated query based on the profile for the end user to provide a more relevant response to the translated query; applying the one or more multi-dimensional-array filters to the plurality of sensor data as indexed to identify the sensor data associated with the specific sensor among a plurality of sensor data for a response to the modified translated query; accessing a cache of popular queries and their associated results; determining whether the received translated query matches one of the queries in the cache of popular queries; and in response to a determination that the received translated query matches one of the queries in the cache of popular queries, communicating the results associated with the matched query in the cache of popular queries to the query originator. | 10. A method comprising, by one or more computer systems: building a profile for an end user based on collectively learned preferences of the end user, the profile comprising a set of keywords and a weight assigned to each keyword in the set of keywords; receiving a translated query for sensor data associated with a specific sensor among a plurality of sensor data from a plurality of sensors, the plurality of sensor data being indexed according to a multi-dimensional array, one or more first ones of the dimensions comprising time and one or more second ones of the dimensions comprising one or more pre-determined sensor-data attributes, the translated query having been translated from an original query for particular sensor data, the translated query comprising an unique resource locator specifying the specific sensor of the plurality of sensors, the translated query comprising one or more values for one or more of the dimensions of the multi-dimensional array; generating one or more multi-dimensional-array filters based on the translated query; determining that the translated query is not accurate; modifying the translated query based on the profile for the end user to provide a more relevant response to the translated query; applying the one or more multi-dimensional-array filters to the plurality of sensor data as indexed to identify the sensor data associated with the specific sensor among a plurality of sensor data for a response to the modified translated query; accessing a cache of popular queries and their associated results; determining whether the received translated query matches one of the queries in the cache of popular queries; and in response to a determination that the received translated query matches one of the queries in the cache of popular queries, communicating the results associated with the matched query in the cache of popular queries to the query originator. 11. The method of claim 10 , wherein one or more of the multi-dimensional-array filters omits any sensor data below a ranking specified by the translated query. | 0.612056 |
2. The non-transitory computer-readable medium encoded with instructions according to claim 1 , said instructions, when executed by the computer, further cause the computer to split up said description in dependencies between said object classes, and in the case of a dependency between two object classes each translated by a different code generator, said instructions cause the computer to make said dependency be handled by two adapters that each translate it into a computer code for interfacing the computer codes produced by said code generators for said two object classes. | 2. The non-transitory computer-readable medium encoded with instructions according to claim 1 , said instructions, when executed by the computer, further cause the computer to split up said description in dependencies between said object classes, and in the case of a dependency between two object classes each translated by a different code generator, said instructions cause the computer to make said dependency be handled by two adapters that each translate it into a computer code for interfacing the computer codes produced by said code generators for said two object classes. 6. The non-transitory computer-readable medium encoded with instructions according to claim 2 , wherein said two adapters having to handle the dependency are chosen following assignment rules associating, for the orientation of the dependency of said two object classes, an adapter corresponding to each of the code generators translating said two object classes, said assignment rules being modifiable. | 0.753958 |
1. A method performed by a computer means for changing a grammatically incorrect sentence that has been pre-translated from a source language into a grammatically correct sentence in a target language, comprising the steps of: storing a plurality of unique grammar markers in a first database and associating each unique grammar marker with a unique grammar rule; storing a plurality of unique grammar marker patterns in a second database and associating each unique grammar marker pattern with a unique self-correction rule; inputting a pre-translated sentence that may have grammatical errors therein into a raw translation buffer; pre-identifying grammar markers in said pre-translated sentence, each grammar marker being associated with a word which may have grammatical variations in said target language but not in said source language; scanning said pre-translated sentence to identify a grammar marker or a plurality of grammar markers, if any, and a grammar marker pattern or a plurality of grammar maker patterns, if any, in said pre-translated sentence; providing a key match buffer for temporary storage of data; inputting any identified grammar marker into said key match buffer; providing a pattern match buffer for temporary storage of data; inputting any identified grammar marker pattern into said pattern match buffer, providing a correction scheme means in said computer means for retrieving appropriate grammar rules and self-correction rules from said first and second databases, respectively, and for making appropriate corrections to generate a substantially grammatically correct sentence; interconnecting a first plurality of logic gates between said correction scheme means and said first database and between said correction scheme means and said key match buffer; comparing the grammar markers in the key match buffer with the grammar markers in the first database and opening said first plurality of logic gates when a match of grammar rules is made; inputting grammar rules fetched from said first database into said correction scheme means when said first plurality of logic gates is enabled; interconnecting a second plurality of logic gates between said correction scheme means and said second database and between said correction scheme means and said pattern match buffer; comparing the grammar marker patterns in the pattern match buffer with the grammar marker patterns in the second database and opening said second plurality of logic gates when a match of self-correction rules is made; inputting self-correction rules fetched from said second database into said correction scheme means when said second plurality of logic gates is enabled; and correcting said pre-translated sentence having grammatical errors therein by applying in said correction scheme means said fetched grammar rules and said fetched self-correction rules to said pre-translated sentence to produce a sentence substantially free of grammatical errors; said fetched grammar rules and said fetched self-correction rules being appropriate rules to correct the pre-translated sentence because each grammar rule in said first database is associated with a unique grammar marker stored with it in said first database and because each self-correction rule in said second database is associated with a unique grammar marker pattern stored with it in said second database so that any grammar marker in said key match buffer will match only a counterpart grammar marker in said first database and therefore cause delivery of the grammar rule associated with said counterpart grammar marker in said first database to the correction scheme means, and so that any grammar marker in said pattern match buffer will match only a counterpart grammar marker pattern in said second database and therefore cause delivery of the self-correction rule associated with said counterpart grammar marker pattern in said second database to the correction scheme means; whereby ungrammatical expressions in the pre-translated sentence are corrected in the absence of human intervention. | 1. A method performed by a computer means for changing a grammatically incorrect sentence that has been pre-translated from a source language into a grammatically correct sentence in a target language, comprising the steps of: storing a plurality of unique grammar markers in a first database and associating each unique grammar marker with a unique grammar rule; storing a plurality of unique grammar marker patterns in a second database and associating each unique grammar marker pattern with a unique self-correction rule; inputting a pre-translated sentence that may have grammatical errors therein into a raw translation buffer; pre-identifying grammar markers in said pre-translated sentence, each grammar marker being associated with a word which may have grammatical variations in said target language but not in said source language; scanning said pre-translated sentence to identify a grammar marker or a plurality of grammar markers, if any, and a grammar marker pattern or a plurality of grammar maker patterns, if any, in said pre-translated sentence; providing a key match buffer for temporary storage of data; inputting any identified grammar marker into said key match buffer; providing a pattern match buffer for temporary storage of data; inputting any identified grammar marker pattern into said pattern match buffer, providing a correction scheme means in said computer means for retrieving appropriate grammar rules and self-correction rules from said first and second databases, respectively, and for making appropriate corrections to generate a substantially grammatically correct sentence; interconnecting a first plurality of logic gates between said correction scheme means and said first database and between said correction scheme means and said key match buffer; comparing the grammar markers in the key match buffer with the grammar markers in the first database and opening said first plurality of logic gates when a match of grammar rules is made; inputting grammar rules fetched from said first database into said correction scheme means when said first plurality of logic gates is enabled; interconnecting a second plurality of logic gates between said correction scheme means and said second database and between said correction scheme means and said pattern match buffer; comparing the grammar marker patterns in the pattern match buffer with the grammar marker patterns in the second database and opening said second plurality of logic gates when a match of self-correction rules is made; inputting self-correction rules fetched from said second database into said correction scheme means when said second plurality of logic gates is enabled; and correcting said pre-translated sentence having grammatical errors therein by applying in said correction scheme means said fetched grammar rules and said fetched self-correction rules to said pre-translated sentence to produce a sentence substantially free of grammatical errors; said fetched grammar rules and said fetched self-correction rules being appropriate rules to correct the pre-translated sentence because each grammar rule in said first database is associated with a unique grammar marker stored with it in said first database and because each self-correction rule in said second database is associated with a unique grammar marker pattern stored with it in said second database so that any grammar marker in said key match buffer will match only a counterpart grammar marker in said first database and therefore cause delivery of the grammar rule associated with said counterpart grammar marker in said first database to the correction scheme means, and so that any grammar marker in said pattern match buffer will match only a counterpart grammar marker pattern in said second database and therefore cause delivery of the self-correction rule associated with said counterpart grammar marker pattern in said second database to the correction scheme means; whereby ungrammatical expressions in the pre-translated sentence are corrected in the absence of human intervention. 10. The method of claim 1, wherein a grammar marker of said plurality of grammar markers includes a progressive mode marker. | 0.556641 |
24. A system for speech-based user authentication, comprising: a processor configured to receive a spoken utterance of a speaker, generate a phoneme-independent matrix based on the spoken utterance, wherein the phoneme-independent matrix comprises a plurality of phoneme-independent feature vectors each having been extracted from a respective frame sampled from the spoken utterance at a sampling frequency, decompose the phoneme-independent matrix into multiple sets of vectors at least a first set of vectors defining at least one speaker-specific recognition unit and a second set of vectors defining at least one content reference sequence, compute at least one speaker-specific distribution value based on at least the speaker-specific recognition unit; and authenticate an input speech signal based on the at least one speaker-specific distribution value. | 24. A system for speech-based user authentication, comprising: a processor configured to receive a spoken utterance of a speaker, generate a phoneme-independent matrix based on the spoken utterance, wherein the phoneme-independent matrix comprises a plurality of phoneme-independent feature vectors each having been extracted from a respective frame sampled from the spoken utterance at a sampling frequency, decompose the phoneme-independent matrix into multiple sets of vectors at least a first set of vectors defining at least one speaker-specific recognition unit and a second set of vectors defining at least one content reference sequence, compute at least one speaker-specific distribution value based on at least the speaker-specific recognition unit; and authenticate an input speech signal based on the at least one speaker-specific distribution value. 25. The system of claim 24 wherein the processor is further configured to decompose the phoneme-independent matrix into the at least one speaker-specific recognition unit. | 0.711564 |
1. A method comprising: collecting, over a network, data relating to a plurality of keywords, wherein the data relating to keywords comprises: a plurality of concept keywords, each concept keyword relating to one of a plurality of concepts and data relating to relationships among the plurality of concepts, data relating to a plurality of entity keywords, each entity keyword relating to one of a plurality of entities and data relating to relationships among the plurality of entities, and data relating to relationships between the plurality of entities and the plurality of concept keywords; storing, using at least one computing device, the data relating to a plurality of keywords, on a knowledgebase stored on a computer-readable medium, wherein the plurality of concept keywords and the data relating to relationships among the plurality of concepts is used to create a hierarchy of concept definitions having a plurality of typed and weighted concept-to-concept relationships with one another, and wherein the data relating to a plurality of entities is used to create a plurality of entity profiles, each entity profile relating to one of the plurality of entities, and wherein the data relating to relationships among the plurality of entities is used to create a plurality of typed and weighted entity-to-entity relationships, and wherein the data relating to relationships between the plurality of entities and the plurality of concept keywords is used to create a plurality of typed and weighted entity-to-concept relationships. | 1. A method comprising: collecting, over a network, data relating to a plurality of keywords, wherein the data relating to keywords comprises: a plurality of concept keywords, each concept keyword relating to one of a plurality of concepts and data relating to relationships among the plurality of concepts, data relating to a plurality of entity keywords, each entity keyword relating to one of a plurality of entities and data relating to relationships among the plurality of entities, and data relating to relationships between the plurality of entities and the plurality of concept keywords; storing, using at least one computing device, the data relating to a plurality of keywords, on a knowledgebase stored on a computer-readable medium, wherein the plurality of concept keywords and the data relating to relationships among the plurality of concepts is used to create a hierarchy of concept definitions having a plurality of typed and weighted concept-to-concept relationships with one another, and wherein the data relating to a plurality of entities is used to create a plurality of entity profiles, each entity profile relating to one of the plurality of entities, and wherein the data relating to relationships among the plurality of entities is used to create a plurality of typed and weighted entity-to-entity relationships, and wherein the data relating to relationships between the plurality of entities and the plurality of concept keywords is used to create a plurality of typed and weighted entity-to-concept relationships. 4. The method of claim 1 wherein the user's current concept comprises the demographic (male/female, age group, postal code) or chosen role of the use (consumer, vendor, or employee). | 0.555077 |
7. A non-transitory computer-readable medium storing program instructions that, when executed by a processor, cause the processor to perform a method of extracting a desired status value related to a remotely monitored image output device, automatically without human intervention, wherein the processor is configured to communicate with the image output device using plural application-layer communication protocols, the method comprising: accessing a memory to determine, based on a vendor type of the image output device, a communication protocol of the plural application-layer communication protocols, to use to extract the desired status value from the image output device, the memory storing, for each of the plural application-layer communication protocols, information of at least one vendor, the accessing step determining which of the plural application-layer communication protocols can should be used to obtain the desired status value based on the information of at least one vendor stored in the memory and the vendor information of the image output device; accessing the image output device without human intervention using the determined communication protocol to obtain device information of the monitored image output device that is stored on the image output device; extracting the desired status value from the obtained device information; and storing the extracted desired status value. | 7. A non-transitory computer-readable medium storing program instructions that, when executed by a processor, cause the processor to perform a method of extracting a desired status value related to a remotely monitored image output device, automatically without human intervention, wherein the processor is configured to communicate with the image output device using plural application-layer communication protocols, the method comprising: accessing a memory to determine, based on a vendor type of the image output device, a communication protocol of the plural application-layer communication protocols, to use to extract the desired status value from the image output device, the memory storing, for each of the plural application-layer communication protocols, information of at least one vendor, the accessing step determining which of the plural application-layer communication protocols can should be used to obtain the desired status value based on the information of at least one vendor stored in the memory and the vendor information of the image output device; accessing the image output device without human intervention using the determined communication protocol to obtain device information of the monitored image output device that is stored on the image output device; extracting the desired status value from the obtained device information; and storing the extracted desired status value. 8. The computer-readable medium of claim 7 , wherein the accessing step comprises accessing the memory to determine the communication protocol based on the vendor type and the type of model of the image output device. | 0.788333 |
8. A computing system comprising: one or more computing devices configured to: cause a change to data accessible via a data model, the data model being usable to create an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to the data accessible via the data model; create an intermediate representation of the page based on the page description and the data model, the intermediate representation including at least a portion of the data accessible via the data model that includes the changed data, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; determine an expected value for a portion of the intermediate representation based on the change to the data accessible via the data model; identify an actual value for the portion of the intermediate representation; determine whether the actual value matches the expected value; and when the actual value does not match the expected value, store an indication of an error. | 8. A computing system comprising: one or more computing devices configured to: cause a change to data accessible via a data model, the data model being usable to create an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to the data accessible via the data model; create an intermediate representation of the page based on the page description and the data model, the intermediate representation including at least a portion of the data accessible via the data model that includes the changed data, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; determine an expected value for a portion of the intermediate representation based on the change to the data accessible via the data model; identify an actual value for the portion of the intermediate representation; determine whether the actual value matches the expected value; and when the actual value does not match the expected value, store an indication of an error. 12. The computing system recited in claim 8 , the one or more computing devices configured to: compile test procedure computer programming language instructions describing a test procedure for testing the page to create an executable test procedure. | 0.616963 |
1. A method for signifying information objects comprising the steps: obtaining a plurality of information objects; providing the plurality of information objects to an indexer for signification; providing the indexer with a deliberately ambiguated signifier prompt; wherein the deliberately ambiguated signifier prompt comprises one of a one-dimensional figure and a multi-dimensional figure, the figure having a plurality of labeled points specifying attributes, and wherein none of the labeled points comprise a desired response, and wherein the indexer signifies each of the information objects by indicating a position on the deliberately ambiguated signifier prompt to represent the information object; and storing in a computer system each of the information objects with the indexer's response to the deliberately ambiguated signifier prompt. | 1. A method for signifying information objects comprising the steps: obtaining a plurality of information objects; providing the plurality of information objects to an indexer for signification; providing the indexer with a deliberately ambiguated signifier prompt; wherein the deliberately ambiguated signifier prompt comprises one of a one-dimensional figure and a multi-dimensional figure, the figure having a plurality of labeled points specifying attributes, and wherein none of the labeled points comprise a desired response, and wherein the indexer signifies each of the information objects by indicating a position on the deliberately ambiguated signifier prompt to represent the information object; and storing in a computer system each of the information objects with the indexer's response to the deliberately ambiguated signifier prompt. 9. The method for signifying information objects of claim 1 , wherein the deliberately ambiguated signifier prompt comprises a linear scale having a first end with a first label indicating a first unfavorable attribute and a second end having a second label indicating a second unfavorable attribute that is opposed to the first unfavorable attribute, and wherein the indexer signifies each of the information objects by indicating a position on the linear scale to represent the information object. | 0.566444 |
19. The computer-implemented method of claim 14 , further comprising generating one or more alternative speech recognition results using the first language model. | 19. The computer-implemented method of claim 14 , further comprising generating one or more alternative speech recognition results using the first language model. 20. The computer-implemented method of claim 19 , further comprising providing to the first client device an alternative speech recognition result from the one or more alternative speech recognition results with a confidence value that satisfies a threshold. | 0.85051 |
8. Apparatus operable to provide a single-end speech quality Measurement, comprising: a feature extraction module which extracts, frame-by-frame, perceptual features from a received speech signal that has been processed by network equipment, transmitted on a communications link, or both; a time segmentation module which classifies each frame based on the perceptual features into a class selected from a set of classes including voiced and unvoiced; a statistical reference model generated prior to extraction of the perceptual features, the reference model including at least one statistical model for each class of the set of classes; a consistency calculation module which, for the frames of each class, operates in response to output from the feature extraction module to assess the perceptual features with a statistical model of that class to form indicators of subjective speech quality without reference to a corresponding speech signal that has not been processed by network equipment, transmitted on a communications link, or both, including assessing at least some unvoiced frames; and a scoring module which employs the indicators of speech quality from different classes to produce a speech quality score without reference to a corresponding speech signal that has not been processed by network equipment, transmitted on a communications link, or both. | 8. Apparatus operable to provide a single-end speech quality Measurement, comprising: a feature extraction module which extracts, frame-by-frame, perceptual features from a received speech signal that has been processed by network equipment, transmitted on a communications link, or both; a time segmentation module which classifies each frame based on the perceptual features into a class selected from a set of classes including voiced and unvoiced; a statistical reference model generated prior to extraction of the perceptual features, the reference model including at least one statistical model for each class of the set of classes; a consistency calculation module which, for the frames of each class, operates in response to output from the feature extraction module to assess the perceptual features with a statistical model of that class to form indicators of subjective speech quality without reference to a corresponding speech signal that has not been processed by network equipment, transmitted on a communications link, or both, including assessing at least some unvoiced frames; and a scoring module which employs the indicators of speech quality from different classes to produce a speech quality score without reference to a corresponding speech signal that has not been processed by network equipment, transmitted on a communications link, or both. 14. The apparatus of claim 8 wherein the statistical reference model includes Gaussian Mixture Models. | 0.545856 |
20. The computer-readable medium of claim 12 wherein the contents of the computer-readable medium cause the computer system to further: identify within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determine to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word. | 20. The computer-readable medium of claim 12 wherein the contents of the computer-readable medium cause the computer system to further: identify within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determine to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word. 22. The computer-readable medium of claim 20 wherein the determining determines to attribute to the first occurrence of the second word the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a determination that the second occurrence of the second word is more closely related to the first word than is the third occurrence of the second word. | 0.690035 |
63. The system of claim 61 , wherein an average hypothesis comprises an average of the plurality of pose models of each set of pose models, wherein the average hypothesis approximates a maximum likelihood estimate for a true pose of a corresponding object. | 63. The system of claim 61 , wherein an average hypothesis comprises an average of the plurality of pose models of each set of pose models, wherein the average hypothesis approximates a maximum likelihood estimate for a true pose of a corresponding object. 65. The system of claim 63 , wherein a smoothed hypothesis is generated through application of a correction factor to the average hypothesis. | 0.860862 |
14. A machine-readable storage device with instruction stored thereon, the instructions when executed operable to cause a computerized mobile device to: receive an indication of a first user input comprising an actuation of a graphical element, the actuation being associated with a voice input operation, the first user input being detected at a presence-sensitive display; responsive to receiving the indication of the first user input and prior to a termination of the actuation: initiate the voice input operation; receive, using the voice input operation, an indication of a user-spoken search phrase comprising one or more search terms; output for display, the one or more candidate text search phrases determined based at least in part on the spoken phrase; receive an indication of a gesture sliding from a first area of a presence-sensitive display associated with the one or more candidate text search phrases to a second area of the presence-sensitive display associated with at least one icon; receive an indication of a second user input indicating the termination of the actuation, wherein the second user input indicates a completion of the user-spoken search phrase; and responsive to receiving the indication of the second user inputs perform an action associated with the at least one icon using the one or more terms in the spoken phrase. | 14. A machine-readable storage device with instruction stored thereon, the instructions when executed operable to cause a computerized mobile device to: receive an indication of a first user input comprising an actuation of a graphical element, the actuation being associated with a voice input operation, the first user input being detected at a presence-sensitive display; responsive to receiving the indication of the first user input and prior to a termination of the actuation: initiate the voice input operation; receive, using the voice input operation, an indication of a user-spoken search phrase comprising one or more search terms; output for display, the one or more candidate text search phrases determined based at least in part on the spoken phrase; receive an indication of a gesture sliding from a first area of a presence-sensitive display associated with the one or more candidate text search phrases to a second area of the presence-sensitive display associated with at least one icon; receive an indication of a second user input indicating the termination of the actuation, wherein the second user input indicates a completion of the user-spoken search phrase; and responsive to receiving the indication of the second user inputs perform an action associated with the at least one icon using the one or more terms in the spoken phrase. 15. The machine-readable medium of claim 14 , wherein the action comprises one of performing a search, composing a text message, and composing an email message. | 0.623616 |
1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance. | 1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance. 4. The apparatus according to claim 1 , further comprising a voice input unit into which speaker's voice is input, wherein the determination unit determines whether the first text needs to be replaced or not depending on quality of the voice input into the voice input unit. | 0.571592 |
1. A computer-executed method for displaying social interest in television programs, the method comprising: storing a plurality of social media content items received from an external social networking system; selecting a plurality of television programs, each television program associated with one of a series of chronological time segments of television; for each selected television program: determining that a subset of the social media content items is relevant to the television program, storing the subset of the social media content items relevant to the television program, and determining a level of social interest in the television program based on the subset of the social media content items determined to be relevant to the television program; for each of the time segments, determining a level of social interest in the time segment based upon an aggregate level of social interest in the television programs associated with the time segment; and graphically displaying at least one time segment and the determined level of social interest for each displayed time segment. | 1. A computer-executed method for displaying social interest in television programs, the method comprising: storing a plurality of social media content items received from an external social networking system; selecting a plurality of television programs, each television program associated with one of a series of chronological time segments of television; for each selected television program: determining that a subset of the social media content items is relevant to the television program, storing the subset of the social media content items relevant to the television program, and determining a level of social interest in the television program based on the subset of the social media content items determined to be relevant to the television program; for each of the time segments, determining a level of social interest in the time segment based upon an aggregate level of social interest in the television programs associated with the time segment; and graphically displaying at least one time segment and the determined level of social interest for each displayed time segment. 3. The computer-executed method of claim 1 , further comprising filtering the time segments according to a search term, wherein graphically displaying at least one time segment comprises displaying only a subset of the series of chronological time segments corresponding to the search term. | 0.736697 |
1. A system comprising: a database interface; a communication interface; and collaboration circuitry in communication with the database interface and the communication interface, the collaboration circuitry configured to: retrieve defined roles assigned to geographically distributed entities and communication pathway preference information for the geographically distributed entities from the database interface; generate an event notification for an event for distribution to the geographically distributed entities; implement an adaptable subscription model that is operable to select specific entities among the geographically distributed entities to which to send the event notification, where the adaptable subscription model is operable to identify the specific entities responsive to the defined roles in comparison to the event; tune the adaptable subscription model by subscribing the geographically distributed entities to additional events, where the additional events are selected responsive to the defined roles of the geographically distributed entities; determine the specific entities to which to send the event notification to based on the adaptable subscription model; and determine communication pathways, supported by the communication interface, for sending the event notification to the selected entities, responsive to the communication pathway preference information for the selected entities; digital collaboration workspace circuitry in communication with the database interface and the communication interface, the digital collaboration workspace circuitry configured to: provide a newsfeed comprising event notifications for events that a system subscriber is following; aggregate communications responsive to the event notifications to obtain an event conversation; insert the event notifications and event conversation into the newsfeed to obtain an enhanced newsfeed; and generate a digital collaboration workspace user interface comprising the enhanced newsfeed; persistent status circuitry configured to: promote specific event notifications to a persistent status; place the event notifications promoted to, persistent status as a persistent note in a prioritized location on the digital collaboration workspace user interface; and retain the persistent note in the prioritized location until a pre-determined condition is met; workspace update circuitry configured to process subsequent events and subsequent event notifications to update the newsfeed provided by the digital collaboration workspace circuitry; and knowledge capture circuitry configured to perform a knowledge capture process to: store a collaboration occurrence in a knowledge base, process the collaboration occurrence to identify relevant metadata tags, and generate additional documentation comprising the metadata tags. | 1. A system comprising: a database interface; a communication interface; and collaboration circuitry in communication with the database interface and the communication interface, the collaboration circuitry configured to: retrieve defined roles assigned to geographically distributed entities and communication pathway preference information for the geographically distributed entities from the database interface; generate an event notification for an event for distribution to the geographically distributed entities; implement an adaptable subscription model that is operable to select specific entities among the geographically distributed entities to which to send the event notification, where the adaptable subscription model is operable to identify the specific entities responsive to the defined roles in comparison to the event; tune the adaptable subscription model by subscribing the geographically distributed entities to additional events, where the additional events are selected responsive to the defined roles of the geographically distributed entities; determine the specific entities to which to send the event notification to based on the adaptable subscription model; and determine communication pathways, supported by the communication interface, for sending the event notification to the selected entities, responsive to the communication pathway preference information for the selected entities; digital collaboration workspace circuitry in communication with the database interface and the communication interface, the digital collaboration workspace circuitry configured to: provide a newsfeed comprising event notifications for events that a system subscriber is following; aggregate communications responsive to the event notifications to obtain an event conversation; insert the event notifications and event conversation into the newsfeed to obtain an enhanced newsfeed; and generate a digital collaboration workspace user interface comprising the enhanced newsfeed; persistent status circuitry configured to: promote specific event notifications to a persistent status; place the event notifications promoted to, persistent status as a persistent note in a prioritized location on the digital collaboration workspace user interface; and retain the persistent note in the prioritized location until a pre-determined condition is met; workspace update circuitry configured to process subsequent events and subsequent event notifications to update the newsfeed provided by the digital collaboration workspace circuitry; and knowledge capture circuitry configured to perform a knowledge capture process to: store a collaboration occurrence in a knowledge base, process the collaboration occurrence to identify relevant metadata tags, and generate additional documentation comprising the metadata tags. 2. The system of claim 1 , where the knowledge capture circuitry is configured to trigger the knowledge capture process responsive to a user input. | 0.752508 |
8. The non-transitory, tangible, and computer-readable medium of claim 1 , wherein each of the one or more resource fields comprises a string comprising a Uniform Resource Identifier (URI) that maps to a resource to be imported into the message, wherein each URI is a string that identifies a location of the resource to be imported. | 8. The non-transitory, tangible, and computer-readable medium of claim 1 , wherein each of the one or more resource fields comprises a string comprising a Uniform Resource Identifier (URI) that maps to a resource to be imported into the message, wherein each URI is a string that identifies a location of the resource to be imported. 9. The non-transitory, tangible, and computer-readable medium of claim 8 , wherein each of the one or more resource fields comprise a source indication that identifies a specific location within the resource from which imported time-variant data is to be derived, wherein the source indication comprises: an explicit indication that explicitly states where the imported time-variant data is specifically located within the resource; or an implicit indication when an explicit indication is lacking, wherein the implicit indication indicates that the specific location of the imported time-variant data is in a root location of the resource. | 0.741738 |
3. A method for alerting a user to abnormal micro-blog activity comprising: collecting a plurality of tokenized, received micro-blog messages in a first time interval; selecting a plurality of seed tokens; forming a plurality of soft clusters of micro-blog messages in which all the messages in a soft cluster have the same seed token, each of the soft clusters has a different seed token, and some of the messages are in more than one soft cluster; reducing the number of soft clusters by eliminating some soft clusters that are less dense than other soft clusters; eliminating duplication of messages so that each text message is found in only one soft cluster; agglomeratively merging the soft clusters to produce a first output of clustered text messages; examining the received micro-blog messages for abnormal activity; and alerting a user when the abnormal activity is detected. | 3. A method for alerting a user to abnormal micro-blog activity comprising: collecting a plurality of tokenized, received micro-blog messages in a first time interval; selecting a plurality of seed tokens; forming a plurality of soft clusters of micro-blog messages in which all the messages in a soft cluster have the same seed token, each of the soft clusters has a different seed token, and some of the messages are in more than one soft cluster; reducing the number of soft clusters by eliminating some soft clusters that are less dense than other soft clusters; eliminating duplication of messages so that each text message is found in only one soft cluster; agglomeratively merging the soft clusters to produce a first output of clustered text messages; examining the received micro-blog messages for abnormal activity; and alerting a user when the abnormal activity is detected. 11. The method of claim 3 further comprising: collecting a plurality of first outputs in a second time interval that comprises multiple first time intervals; selecting a plurality of seed tokens; forming a plurality of soft clusters of text messages in which all the text messages in a soft cluster have the same seed token, each of the soft clusters has a different seed token, and some of the text messages are in more than one soft cluster; reducing the number of soft clusters by eliminating some soft clusters that are less dense than other soft clusters; eliminating duplication of text messages so that each text message is found in only one soft cluster; and agglomeratively merging the soft clusters to produce a second output of clustered text messages. | 0.562855 |
8. The method of claim 1 , further comprising verifying that one or more of the designated start time, end time, and location is within a collaborative region defined by an owner of the first video file, the collaborative region specifying at least one of a temporal subset of the first video file and a spatial subset of frames of the first video file. | 8. The method of claim 1 , further comprising verifying that one or more of the designated start time, end time, and location is within a collaborative region defined by an owner of the first video file, the collaborative region specifying at least one of a temporal subset of the first video file and a spatial subset of frames of the first video file. 9. The method of claim 8 , wherein the owner of the first video file is a user that submitted the first video file for storage in the video database. | 0.948496 |
1. A computer-readable medium having computer executable instructions encoded thereon, the computer executable instructions executed by a processor to perform operations for long-query retrieval comprising: identifying a query file on which to base a query; performing decomposition comprising utilizing a probabilistic topic model to obtain a decomposed version of the query file, the decomposed version of the query file comprising: topic-related words, which do not include file-specific words; and at least one file-specific word, which is not a topic-related word; creating a composite representation of the query file, the composite representation comprising: a vector of the topic-related words; and an index of a configurable number of file-specific words; based at least on the vector of the topic-related words, determining a topic corresponding to the query file; comparing the vector of the topic-related words of the query file to vectors of topic-related words of a plurality of files; selecting a candidate set of files from the plurality of files based at least on a ranking of closeness of proximity of the vectors of the topic-related words of the candidate set of files to the vector of the topic-related words of the query file; performing re-ranking of the files in the candidate set of files, the re-ranking comprising: comparing the index of the file-specific words of the query file to indexes of the file-specific words of the files in the candidate set of files; and assigning scores to files in the candidate set of files based at least on calculated similarity of the indexes of the candidate set of files and the index of the query file; and returning a configurable number of the files from the candidate set of files having the highest scores. | 1. A computer-readable medium having computer executable instructions encoded thereon, the computer executable instructions executed by a processor to perform operations for long-query retrieval comprising: identifying a query file on which to base a query; performing decomposition comprising utilizing a probabilistic topic model to obtain a decomposed version of the query file, the decomposed version of the query file comprising: topic-related words, which do not include file-specific words; and at least one file-specific word, which is not a topic-related word; creating a composite representation of the query file, the composite representation comprising: a vector of the topic-related words; and an index of a configurable number of file-specific words; based at least on the vector of the topic-related words, determining a topic corresponding to the query file; comparing the vector of the topic-related words of the query file to vectors of topic-related words of a plurality of files; selecting a candidate set of files from the plurality of files based at least on a ranking of closeness of proximity of the vectors of the topic-related words of the candidate set of files to the vector of the topic-related words of the query file; performing re-ranking of the files in the candidate set of files, the re-ranking comprising: comparing the index of the file-specific words of the query file to indexes of the file-specific words of the files in the candidate set of files; and assigning scores to files in the candidate set of files based at least on calculated similarity of the indexes of the candidate set of files and the index of the query file; and returning a configurable number of the files from the candidate set of files having the highest scores. 4. A computer-readable medium as recited in claim 1 , wherein the query file comprises one selected from: a document; an image; a photograph; an audio file; or a multimedia file. | 0.5 |
25. The system of claim 20 , wherein the feature indexing unit creates a quantization tree and adds a feature point to the quantization tree for the invisible junction feature descriptors. | 25. The system of claim 20 , wherein the feature indexing unit creates a quantization tree and adds a feature point to the quantization tree for the invisible junction feature descriptors. 26. The system of claim 25 , wherein the feature indexing unit adds the feature point by adding a leaf node including a page ID and coordinates (x, y) of the feature point. | 0.956136 |
10. A system for analyzing a document comprising: a text extractor configured to extract text of the document from a native form of the document, wherein the text of the document comprises a glossary including a lexical ontology; a separator configured to separate the document into two or more physical sections; a text analyzer configured to: identify, using text analytics on the lexical ontology of the glossary and without user-input, one or more directives within the text; and generate, based on the one or more directives, one or more annotations within the two or more physical sections; a comparator configured to compare the annotations to identify duplicate annotations and conflicting annotations within the text; and a searchable interface configured to display the annotations and results of the comparison of the annotations. | 10. A system for analyzing a document comprising: a text extractor configured to extract text of the document from a native form of the document, wherein the text of the document comprises a glossary including a lexical ontology; a separator configured to separate the document into two or more physical sections; a text analyzer configured to: identify, using text analytics on the lexical ontology of the glossary and without user-input, one or more directives within the text; and generate, based on the one or more directives, one or more annotations within the two or more physical sections; a comparator configured to compare the annotations to identify duplicate annotations and conflicting annotations within the text; and a searchable interface configured to display the annotations and results of the comparison of the annotations. 15. The system of claim 10 , further comprising: indexing the annotations; and combining the annotations with second annotations from another document; and wherein the comparing comprises comparing the annotations with the second annotations. | 0.772472 |
11. A method of inputting and editing text on an electronic device with a user interface comprising at least one input system which detects input actions of a user to generate and edit text, and at least one text presentation system through which said text is presented to said user, the method comprising: recording the location of a text insertion position within said text presentation system where a next generated textual object will be output; detecting a distinctive input action to identify one or more of said textual objects previously output to said text presentation system; identifying one or more of said textual objects previously output based on the detected distinctive input action; determining one or more alternate textual objects that correspond to one or more detected input actions from which said identified one or more textual objects was previously determined; replacing said identified previously output one or more textual objects with one or more of said determined alternate textual objects; and restoring said text insertion position to a location recorded prior to said detecting of said distinctive input action. | 11. A method of inputting and editing text on an electronic device with a user interface comprising at least one input system which detects input actions of a user to generate and edit text, and at least one text presentation system through which said text is presented to said user, the method comprising: recording the location of a text insertion position within said text presentation system where a next generated textual object will be output; detecting a distinctive input action to identify one or more of said textual objects previously output to said text presentation system; identifying one or more of said textual objects previously output based on the detected distinctive input action; determining one or more alternate textual objects that correspond to one or more detected input actions from which said identified one or more textual objects was previously determined; replacing said identified previously output one or more textual objects with one or more of said determined alternate textual objects; and restoring said text insertion position to a location recorded prior to said detecting of said distinctive input action. 14. The method of claim 11 , further comprising automatically generating one or more spaces between one or more output textual objects. | 0.672009 |
14. The non-transitory computer readable medium according to claim 13 , wherein the instructions further comprise: collecting a user image, wherein when it is detected that a quantity of people in the user image is a preset value, performing the user attribute recognition on the speech data. | 14. The non-transitory computer readable medium according to claim 13 , wherein the instructions further comprise: collecting a user image, wherein when it is detected that a quantity of people in the user image is a preset value, performing the user attribute recognition on the speech data. 15. The non-transitory computer readable medium according to claim 14 , wherein the instructions further comprise: extracting face data from the user image; and performing face recognition on the face data to obtain a second user attribute recognition result. | 0.885983 |
11. The non-transitory computable readable medium of claim 10 wherein the header properties are simple mail transfer protocol (SMTP) x-header properties. | 11. The non-transitory computable readable medium of claim 10 wherein the header properties are simple mail transfer protocol (SMTP) x-header properties. 14. The non-transitory computer readable medium of claim 11 wherein the pre-defined classification criteria are defined relative to one or more security levels and one or more selected from the group comprising: sensitivity levels, intended distribution groups and retention level. | 0.911142 |
15. A non-transitory computer-readable storage medium having instruction stored which, when executed by a computing device, result in the computing device performing operations comprising: receiving, from a speech recognition system, recognized speech; identifying information about a speaker of the recognized speech from the recognized speech; and submitting the recognized speech and the information to a question-answering engine which selects and outputs a response associated with the recognized speech based on the recognized speech and the information. | 15. A non-transitory computer-readable storage medium having instruction stored which, when executed by a computing device, result in the computing device performing operations comprising: receiving, from a speech recognition system, recognized speech; identifying information about a speaker of the recognized speech from the recognized speech; and submitting the recognized speech and the information to a question-answering engine which selects and outputs a response associated with the recognized speech based on the recognized speech and the information. 16. The non-transitory computer-readable storage medium of claim 15 , wherein the information comprises demographic features. | 0.572238 |
18. The non-transitory medium of claim 17 , comprising instructions compatible with: the set of characteristics including aggregate statistical characteristics comprising at least one of generic aggregate statistics and scenario aggregate statistics, the generic aggregate statistics being calculated in a manner that is independent of a set of semantics of the attributes, and the scenario aggregate statistics being defined through a domain expert and being relevant in a particular scenario to enable incorporation of a domain-specific interpretation of the semantics of the each attribute and each set of data of the at least one of the initial result set and the subsequent result set. | 18. The non-transitory medium of claim 17 , comprising instructions compatible with: the set of characteristics including aggregate statistical characteristics comprising at least one of generic aggregate statistics and scenario aggregate statistics, the generic aggregate statistics being calculated in a manner that is independent of a set of semantics of the attributes, and the scenario aggregate statistics being defined through a domain expert and being relevant in a particular scenario to enable incorporation of a domain-specific interpretation of the semantics of the each attribute and each set of data of the at least one of the initial result set and the subsequent result set. 20. The non-transitory medium of claim 18 , comprising instructions compatible with: the scenario aggregate statistics being programmed via user-defined aggregate queries and associated with the at least one of the initial result set and the subsequent result set, a syntax of the user-defined aggregate queries being specific to a standard query processing engine, and a signature of the scenario aggregate statistics creating a signature that corresponds to a set of table valued functions. | 0.672482 |
1. One or more non-transitory, tangible computer-readable media having computer-executable instructions for performing a method by running a software program on a computer, the computer operating under an operating system, the method including issuing instructions from the software program to extract semantic bio-entity relationships or patterns from non-annotated data by natural language processing and graph theoretic algorithm, the instructions comprising: receiving a plurality of known bio-entity strings and a plurality of interaction word strings; receiving annotated text as training data that contains true and false patterns; automatically building a decision support tool based on said true and false patterns to which said non-annotated data can be parsed, said decision support tool including at least a first level and a second level, said first level having a first decision node, said second level having a second decision node, said first and second decision nodes each associated with at least a portion of said true and false patterns; receiving said non-annotated data; extracting a textual clause of said non-annotated data that contains non-triplet word strings and at least one triplet, said at least one triplet including a first bio-entity, a second bio-entity, and an interaction word, wherein said interaction word indicates a possible relationship between said first bio-entity and said second bio-entity; automatically parsing said extracted textual clause through said decision support tool to obtain a plurality of components based on dependencies among said plurality of components; extracting said at least one triplet from said plurality of components by attempting to match said plurality of components of said parsed, extracted textual clause to said first level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said first level of said decision support tool; identifying extraction of said at least one triplet as false if said plurality of components fails to match said first level of said decision support tool; as a result of said plurality of components failing to match said first level of said decision support tool, extracting said at least one triplet from said plurality of components by attempting to match said plurality of components to said second level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said second level of said decision support tool, said second level of said decision support tool being a simplified pattern of said first level of said decision support tool to capture textual clauses that are not identical to said extracted textual clause; and identifying extraction of said at least one triplet as false if said plurality of components fails to match said second level of said decision support tool. | 1. One or more non-transitory, tangible computer-readable media having computer-executable instructions for performing a method by running a software program on a computer, the computer operating under an operating system, the method including issuing instructions from the software program to extract semantic bio-entity relationships or patterns from non-annotated data by natural language processing and graph theoretic algorithm, the instructions comprising: receiving a plurality of known bio-entity strings and a plurality of interaction word strings; receiving annotated text as training data that contains true and false patterns; automatically building a decision support tool based on said true and false patterns to which said non-annotated data can be parsed, said decision support tool including at least a first level and a second level, said first level having a first decision node, said second level having a second decision node, said first and second decision nodes each associated with at least a portion of said true and false patterns; receiving said non-annotated data; extracting a textual clause of said non-annotated data that contains non-triplet word strings and at least one triplet, said at least one triplet including a first bio-entity, a second bio-entity, and an interaction word, wherein said interaction word indicates a possible relationship between said first bio-entity and said second bio-entity; automatically parsing said extracted textual clause through said decision support tool to obtain a plurality of components based on dependencies among said plurality of components; extracting said at least one triplet from said plurality of components by attempting to match said plurality of components of said parsed, extracted textual clause to said first level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said first level of said decision support tool; identifying extraction of said at least one triplet as false if said plurality of components fails to match said first level of said decision support tool; as a result of said plurality of components failing to match said first level of said decision support tool, extracting said at least one triplet from said plurality of components by attempting to match said plurality of components to said second level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said second level of said decision support tool, said second level of said decision support tool being a simplified pattern of said first level of said decision support tool to capture textual clauses that are not identical to said extracted textual clause; and identifying extraction of said at least one triplet as false if said plurality of components fails to match said second level of said decision support tool. 9. One or more non-transitory, tangible computer-readable media as in claim 1 , further comprising: the step of automatically building said decision support tool further based on relationships among additional dependencies among said true and false patterns in said annotated data. | 0.676083 |
1. A data aggregation apparatus, comprising: a communication device to receive data from a plurality of remote data sources, the received data being associated with a plurality of search terms; a processor coupled to the communication device; and a storage device in communication with the processor and storing instructions configured to be executed by the processor to: analyze the received data to identify a trending search term; compare the trending search term with a whitelist of topical terms, the whitelist including terms relevant to a predetermined topic associated with a particular publishing entity; determine that the trending search term is relevant to the predetermined topic; query a content database using the trending search term to identify a caption to be associated with the trending search term, the content database including content published by the particular publishing entity; append the caption to the trending search term; and store the trending search term and the caption in a database, wherein the terms in the whitelist of topical terms are derived from data in the content database. | 1. A data aggregation apparatus, comprising: a communication device to receive data from a plurality of remote data sources, the received data being associated with a plurality of search terms; a processor coupled to the communication device; and a storage device in communication with the processor and storing instructions configured to be executed by the processor to: analyze the received data to identify a trending search term; compare the trending search term with a whitelist of topical terms, the whitelist including terms relevant to a predetermined topic associated with a particular publishing entity; determine that the trending search term is relevant to the predetermined topic; query a content database using the trending search term to identify a caption to be associated with the trending search term, the content database including content published by the particular publishing entity; append the caption to the trending search term; and store the trending search term and the caption in a database, wherein the terms in the whitelist of topical terms are derived from data in the content database. 3. The apparatus of claim 1 , wherein the trending search term is a search term identified as having a higher than normal search frequency. | 0.54849 |
19. A method of classifying a document comprising: using a processor (or computer) to perform the steps of: determining one or more metrics for each classifier engine; using said metrics to determine how to use said classifier engines to classify said document; classifying said document accordingly; using said metrics to rank said classifier engines from best to worst, and wherein classifying said document includes: generating, for each classifier engine, a list of probabilities of said document being classified by each classifier engine into each one of a group of possible classes; determining if the best classifier engine has a highest probability that is greater than the highest probability of each other classifier engine by a predetermined amount; if so, using output from said best classifier engine to classify said document; and if not, summing said probabilities for each class, and classifying said document into the class with the largest sum of probabilities. | 19. A method of classifying a document comprising: using a processor (or computer) to perform the steps of: determining one or more metrics for each classifier engine; using said metrics to determine how to use said classifier engines to classify said document; classifying said document accordingly; using said metrics to rank said classifier engines from best to worst, and wherein classifying said document includes: generating, for each classifier engine, a list of probabilities of said document being classified by each classifier engine into each one of a group of possible classes; determining if the best classifier engine has a highest probability that is greater than the highest probability of each other classifier engine by a predetermined amount; if so, using output from said best classifier engine to classify said document; and if not, summing said probabilities for each class, and classifying said document into the class with the largest sum of probabilities. 21. The method of claim 19 wherein said classifier engines are ranked from best to worst based on engine accuracy. | 0.693324 |
9. 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, from a user device of a first user, a media object and a query associated with the media object, wherein the query requests information related to content presented in the media object; providing for presentation the media object and the query to a plurality of second users different from the first user; receiving a suggested answer to the query from one or more second users of the plurality of second users, wherein a suggested answer from a particular second user is either (i) a new suggested answer submitted by the particular second user in response to the query or (ii) associated with a previous suggested answer to the query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the query and providing for presentation one or more of the suggested answers to the first user. | 9. 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, from a user device of a first user, a media object and a query associated with the media object, wherein the query requests information related to content presented in the media object; providing for presentation the media object and the query to a plurality of second users different from the first user; receiving a suggested answer to the query from one or more second users of the plurality of second users, wherein a suggested answer from a particular second user is either (i) a new suggested answer submitted by the particular second user in response to the query or (ii) associated with a previous suggested answer to the query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the query and providing for presentation one or more of the suggested answers to the first user. 11. The system of claim 9 , wherein providing one or more of the suggested answers includes providing one or more ranked suggested answers and wherein providing one or more ranked suggested answers comprises: grouping similar suggested answers based on a semantic similarity measure; and ranking the suggested answers where each group of similar suggested answers is given a combined ranking. | 0.54295 |
1. A method to be executed at least in part in a computing device for using obscured image data to reconstruct an annotated image, the method comprising: receiving an image to be annotated and annotations to be superimposed onto the image; determining obscured image content (OIC) based on a position of the annotations to be superimposed onto the image; persisting OIC data separate from the image, wherein the OIC data comprises a minimal amount of information necessary to reconstruct the image, the minimal amount of information comprising pixel data from the image which has been obscured by the annotations; rendering the annotations on the image, wherein the annotations are persisted on the image such that the annotated image is a single layer flat image; making the annotated image and the OIC data available for use by annotation-aware and annotation-unaware applications; receiving the annotated image and the OIC data; generating a bitmap based on the annotated image; reading the OIC data; copying only the pixel data from the image which has been obscured by the annotations onto the image to reconstruct the obscured pixels; displaying the reconstructed image; and storing an identifier to mitigate changes by at least one of the annotation-unaware applications, wherein the identifier uniquely identifies exact binary data in the image, wherein the identifier is stored with restore data for restoring the image from the annotated image. | 1. A method to be executed at least in part in a computing device for using obscured image data to reconstruct an annotated image, the method comprising: receiving an image to be annotated and annotations to be superimposed onto the image; determining obscured image content (OIC) based on a position of the annotations to be superimposed onto the image; persisting OIC data separate from the image, wherein the OIC data comprises a minimal amount of information necessary to reconstruct the image, the minimal amount of information comprising pixel data from the image which has been obscured by the annotations; rendering the annotations on the image, wherein the annotations are persisted on the image such that the annotated image is a single layer flat image; making the annotated image and the OIC data available for use by annotation-aware and annotation-unaware applications; receiving the annotated image and the OIC data; generating a bitmap based on the annotated image; reading the OIC data; copying only the pixel data from the image which has been obscured by the annotations onto the image to reconstruct the obscured pixels; displaying the reconstructed image; and storing an identifier to mitigate changes by at least one of the annotation-unaware applications, wherein the identifier uniquely identifies exact binary data in the image, wherein the identifier is stored with restore data for restoring the image from the annotated image. 7. The method of claim 1 , wherein the image includes at least one from a set of: a still image, a video image, a text document, a spreadsheet document, and a graphic. | 0.704188 |
3. The print control apparatus according to claim 1 , wherein, based on the print page range, the rasterizing unit does not rasterize pages of the print job before that precede the print start page, (ii) rasterizes the sequential target pages, and (iii) does not rasterize pages of the print job that succeed the print end page. | 3. The print control apparatus according to claim 1 , wherein, based on the print page range, the rasterizing unit does not rasterize pages of the print job before that precede the print start page, (ii) rasterizes the sequential target pages, and (iii) does not rasterize pages of the print job that succeed the print end page. 4. The print control apparatus according to claim 3 , wherein the print controller further functions as an analyzing unit configured to analyze a page of a document file, of the plurality of ordered document files, wherein the analyzing unit (i) analyzes the pages of the print job that precede the print start page and the sequential target pages, and (ii) does not analyze the pages of the print job that succeed the print end page. | 0.880033 |
14. The device of claim 13 , further including multiple declarative specifications in the relationship template, each declarative specification including least a subject and an object. | 14. The device of claim 13 , further including multiple declarative specifications in the relationship template, each declarative specification including least a subject and an object. 15. The device of claim 14 , wherein a particular declarative specification further includes a predicate, wherein the predicate is a literal that expresses a relationship captured by a particular declarative specification. | 0.919872 |
10. A computer-readable medium encoded with data and instructions for enabling generative programming utilizing focused grammars; the data and instructions causing an apparatus executing the instructions to: receive a stochastic grammar defining variable parameters; generate a candidate program using said grammar; evaluate said candidate program in accordance with predetermined criteria; designate a particular candidate program as a modulating program ill accordance with results of the evaluation; and create a focused grammar to focus results during subsequent iterations of generating a candidate program, wherein said focused grammar is created based upon a decomposition of terminal and non-terminal nodes of said modulating program and includes at least an additional production and a different production probability as compared to said grammar. | 10. A computer-readable medium encoded with data and instructions for enabling generative programming utilizing focused grammars; the data and instructions causing an apparatus executing the instructions to: receive a stochastic grammar defining variable parameters; generate a candidate program using said grammar; evaluate said candidate program in accordance with predetermined criteria; designate a particular candidate program as a modulating program ill accordance with results of the evaluation; and create a focused grammar to focus results during subsequent iterations of generating a candidate program, wherein said focused grammar is created based upon a decomposition of terminal and non-terminal nodes of said modulating program and includes at least an additional production and a different production probability as compared to said grammar. 11. The computer-readable medium of claim 10 further encoded with data and instructions; the data and instructions further causing an apparatus executing the instructions to implement said focused grammar to generate an additional candidate program that is similar to said modulating program. | 0.5 |
1. A method comprising: receiving, at a computing device, a query template comprising a request for web pages from a data set that resides in a cloud comprising a cluster of computing devices; optimizing, via the computing device, the query template to segment the query template into an offline phase and an online phase, the offline phase comprising a query segment with no parameters, the online phase comprising a query segment with parameters; executing, via the computing device, the offline phase in accordance with the cluster of computing devices of the cloud to build one or more indexes; executing, via the computing device, the online phase in accordance with a client computer, wherein the building of the index is based on a space constraint associated with the client computer; sending, via the computing device, the one or more indexes based on the space constraint to the client computer; providing a versioning of a query template to help a user backtrack to correct a mistake; receiving a request to correct the mistake; and returning to a previous version of the query template. | 1. A method comprising: receiving, at a computing device, a query template comprising a request for web pages from a data set that resides in a cloud comprising a cluster of computing devices; optimizing, via the computing device, the query template to segment the query template into an offline phase and an online phase, the offline phase comprising a query segment with no parameters, the online phase comprising a query segment with parameters; executing, via the computing device, the offline phase in accordance with the cluster of computing devices of the cloud to build one or more indexes; executing, via the computing device, the online phase in accordance with a client computer, wherein the building of the index is based on a space constraint associated with the client computer; sending, via the computing device, the one or more indexes based on the space constraint to the client computer; providing a versioning of a query template to help a user backtrack to correct a mistake; receiving a request to correct the mistake; and returning to a previous version of the query template. 7. The method of claim 1 , wherein the one or more indexes are at least one of: a conventional information retrieval index; a relational index; and a non-standard index. | 0.813187 |
1. A method for cloud-driven task execution, wherein the method comprises: determining a plurality of attributes of a task that is (i) requested by a client device and (ii) precluded from execution on a given operating system of the client device based on a policy consideration of the given operating system, wherein the plurality of attributes comprises at least one policy context attribute and multiple context attributes comprising location of a user associated with the client device, the type of client device, a data type associated with the task, a location of data associated with the task, a given operation to be performed on data associated with the task, and one or more content attributes of data associated with the task; correlating each of the plurality of attributes to at least one alternative asset in a cloud network, wherein the at least one alternative asset comprises at least one service that can execute tasks on the given operating system; provisioning the at least one alternative asset from the cloud network to the client device to enable execution of the task on the given operating system of the client device; wherein at least one of the steps is carried out by a computer device. | 1. A method for cloud-driven task execution, wherein the method comprises: determining a plurality of attributes of a task that is (i) requested by a client device and (ii) precluded from execution on a given operating system of the client device based on a policy consideration of the given operating system, wherein the plurality of attributes comprises at least one policy context attribute and multiple context attributes comprising location of a user associated with the client device, the type of client device, a data type associated with the task, a location of data associated with the task, a given operation to be performed on data associated with the task, and one or more content attributes of data associated with the task; correlating each of the plurality of attributes to at least one alternative asset in a cloud network, wherein the at least one alternative asset comprises at least one service that can execute tasks on the given operating system; provisioning the at least one alternative asset from the cloud network to the client device to enable execution of the task on the given operating system of the client device; wherein at least one of the steps is carried out by a computer device. 4. The method of claim 1 , wherein said provisioning comprises streaming the task to the client device. | 0.616199 |
1. A computer-implemented method, comprising: receiving, by a computing device, a query for which one or more indexes are to be recommended, the query including one or more expressions; identifying, by the computing device, an expression in the query; generating, in the computing device, a set of column statistics related to the expression, and storing the set of column statistics in a memory; identifying one or more candidate function-based indexes associated with the query based, at least in part, on the set of column statistics; generating a set of function-based index statistics related to the one or more candidate function-based indexes; and recommending a candidate function-based index based, at least in part, on the set of function-based index statistics. | 1. A computer-implemented method, comprising: receiving, by a computing device, a query for which one or more indexes are to be recommended, the query including one or more expressions; identifying, by the computing device, an expression in the query; generating, in the computing device, a set of column statistics related to the expression, and storing the set of column statistics in a memory; identifying one or more candidate function-based indexes associated with the query based, at least in part, on the set of column statistics; generating a set of function-based index statistics related to the one or more candidate function-based indexes; and recommending a candidate function-based index based, at least in part, on the set of function-based index statistics. 4. The method of claim 1 , the set of column statistics including one or more at a number of rows in a column, a number of distinct values in a column, and a number of times a specified value appears in a column. | 0.59434 |
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