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6,105,026 | 2 | 3 | 2. The method of claim 1, further comprising the steps of: acquiring a second lock on said body of metadata associated with said one or more partitions; updating said body of metadata; and releasing said second lock on said body of metadata. | 2. The method of claim 1, further comprising the steps of: acquiring a second lock on said body of metadata associated with said one or more partitions; updating said body of metadata; and releasing said second lock on said body of metadata. 3. The method of claim 2, wherein: said step of acquiring said second lock on said body of metadata comprises the step of acquiring an exclusive data dictionary lock on a subset of said body of metadata; and said step of releasing said second lock on said body of metadata comprises the step of releasing said exclusive data dictionary lock on said subset of said body of metadata. | 0.5 |
8,843,362 | 1 | 8 | 1. A system comprising: one or more computer processors configured to: receive data relating to a composition of a target group; receive logged communications of the target group; extract textual information from the logged communications; analyze the textual information using statistical and linguistic sentiment analysis techniques; generate one or more vectors from the analysis of the textual information; combine one or more assessments from multiple vectors; identify an individual or sub-group from the target group as a function of the analysis of the textual information; and transmit to a user interface for display on the user interface or transmit to another processor the identified individual or sub-group of the target group and transmit to the user interface for display on the user interface or transmit to another processor a sentiment assessment of the identified individual or sub-group as a function of the statistical and linguistic sentiment analysis; wherein the logged communications are a database of recorded audio voices; and wherein the system comprises a processor configured to analyze the one or more recorded audio voices for audio voice characteristics; and wherein the one or more processors are further configured to analyze the sentiment of the individual or sub-group over a period of time. | 1. A system comprising: one or more computer processors configured to: receive data relating to a composition of a target group; receive logged communications of the target group; extract textual information from the logged communications; analyze the textual information using statistical and linguistic sentiment analysis techniques; generate one or more vectors from the analysis of the textual information; combine one or more assessments from multiple vectors; identify an individual or sub-group from the target group as a function of the analysis of the textual information; and transmit to a user interface for display on the user interface or transmit to another processor the identified individual or sub-group of the target group and transmit to the user interface for display on the user interface or transmit to another processor a sentiment assessment of the identified individual or sub-group as a function of the statistical and linguistic sentiment analysis; wherein the logged communications are a database of recorded audio voices; and wherein the system comprises a processor configured to analyze the one or more recorded audio voices for audio voice characteristics; and wherein the one or more processors are further configured to analyze the sentiment of the individual or sub-group over a period of time. 8. The system of claim 1 , wherein the one or more processors configured to analyze the textual information using statistical and linguistic sentiment analysis techniques are configured to receive a plug-in natural language statistical and/or linguistic sentiment analyzer. | 0.830012 |
8,385,652 | 3 | 4 | 3. The method of claim 2 wherein the geometrical properties on which each of the candidate inter-character breaks are classified further include a size of the respective candidate inter-character break and its neighboring breaks relative to an average break size for the textual line. | 3. The method of claim 2 wherein the geometrical properties on which each of the candidate inter-character breaks are classified further include a size of the respective candidate inter-character break and its neighboring breaks relative to an average break size for the textual line. 4. The method of claim 3 wherein the geometrical properties on which each of the candidate inter-character breaks are classified further include a degree of regularity in estimated character widths for the candidate characters in the textual line. | 0.5 |
7,618,042 | 1 | 3 | 1. A word forming game comprising the steps of: providing a plurality of chips having indicia on one surface, the chips being placed indicia surface down, a timing device and a word validating device wherein at least a majority of the indicia are letters of the alphabet; allowing the players to take turns in order, wherein a turn comprises turning over one chip from the plurality to reveal the chip's indicium wherein the chip is added to a pool of revealed indicia; forming an English word, wherein the step of forming includes the steps of: a player attempting to form an English word from at least three of the revealed indicia in the pool or from at least one of the revealed indicia in the pool and all of the indicia of a word previously formed; and the player placing the English word thus formed into a display of words owned by the player; starting the timing device to time a timing period as soon as all of the chips have been turned over and repeating the step of forming; ending play when the end of the timing period is indicated by the timing device; creating a score for each player wherein the score is determined by a number and a length of words in the player's display; and declaring a winner, the winner being the player having the highest score. | 1. A word forming game comprising the steps of: providing a plurality of chips having indicia on one surface, the chips being placed indicia surface down, a timing device and a word validating device wherein at least a majority of the indicia are letters of the alphabet; allowing the players to take turns in order, wherein a turn comprises turning over one chip from the plurality to reveal the chip's indicium wherein the chip is added to a pool of revealed indicia; forming an English word, wherein the step of forming includes the steps of: a player attempting to form an English word from at least three of the revealed indicia in the pool or from at least one of the revealed indicia in the pool and all of the indicia of a word previously formed; and the player placing the English word thus formed into a display of words owned by the player; starting the timing device to time a timing period as soon as all of the chips have been turned over and repeating the step of forming; ending play when the end of the timing period is indicated by the timing device; creating a score for each player wherein the score is determined by a number and a length of words in the player's display; and declaring a winner, the winner being the player having the highest score. 3. The word forming game according to claim 1 , wherein the timing device is selected from the group consisting of an hour glass, a digital timer and a mechanical timer. | 0.646444 |
9,824,698 | 20 | 21 | 20. The method of claim 19 further including determining a social scenario based on the environment, location and orientation of the system and wherein the set of emotional states is determined relative to the social scenario. | 20. The method of claim 19 further including determining a social scenario based on the environment, location and orientation of the system and wherein the set of emotional states is determined relative to the social scenario. 21. The method of claim 20 wherein providing feedback includes rendering in the display one of: a specific indication of an emotional state including a visual representation specifying the state, or a positive or negative general indication of a change in emotional state based on tinting the display. | 0.5 |
8,885,184 | 29 | 34 | 29. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method comprising: acquiring print data for a print job; generating a first job ticket defined according to a first language for the print job; wrapping a second job ticket defined according to a second language within the first job ticket; and transmitting the print data and the first job ticket to a server. | 29. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method comprising: acquiring print data for a print job; generating a first job ticket defined according to a first language for the print job; wrapping a second job ticket defined according to a second language within the first job ticket; and transmitting the print data and the first job ticket to a server. 34. The medium of claim 29 wherein: the first job ticket comprises an AFP Form Map; and wrapping the second job ticket comprises inserting the second job ticket within an Object Container structure of a Medium Map of the AFP Form Map. | 0.746753 |
8,782,613 | 12 | 14 | 12. The system of claim 11 , wherein the operations further comprise: receiving optimization instructions for the third code statements as to how to rectify the performance issues caused by the third code statements; modifying the actual source code for the computer program in accordance with the optimization instructions; and validating the actual source code as has been modified. | 12. The system of claim 11 , wherein the operations further comprise: receiving optimization instructions for the third code statements as to how to rectify the performance issues caused by the third code statements; modifying the actual source code for the computer program in accordance with the optimization instructions; and validating the actual source code as has been modified. 14. The system of claim 12 , wherein validating the actual source code as has been modified comprises: compiling the actual source code as has been modified to generate a compiled version of the computer program; and testing a compiled version of the computer program. | 0.5 |
8,751,986 | 1 | 9 | 1. A method of circuit design with a computer system, comprising: generating with the computer system a placed, routed, and optimized circuit design, including: guiding, with the computer system, coarse placement of the circuit design according to rules created specifically and automatically for a set of circuit elements in the circuit design, at least one of the rules specified at a register transfer language-level in response to a register transfer language-level construct in the circuit design, the rules specifying positioning of each circuit element of the set of circuit elements in the circuit design relative to other circuit elements of the set of circuit elements in the circuit design; and completing synthesis placement, routing, and optimization of the circuit design according to the rules, wherein the register transfer language-level construct includes at least one of: (i) a plurality of register banks that are part of a pipelined datapath, and the rules specify spaces between register banks of the pipelined datapath, and the spaces are sufficient for combinational logic coupling together different register banks of the pipelined datapath; and (ii) a multiplexer having a bit width of M and a number of inputs per bit of N, and the multiplexer has a rectangle shape with a width and a height such that M is equal to a product of the width times the height. | 1. A method of circuit design with a computer system, comprising: generating with the computer system a placed, routed, and optimized circuit design, including: guiding, with the computer system, coarse placement of the circuit design according to rules created specifically and automatically for a set of circuit elements in the circuit design, at least one of the rules specified at a register transfer language-level in response to a register transfer language-level construct in the circuit design, the rules specifying positioning of each circuit element of the set of circuit elements in the circuit design relative to other circuit elements of the set of circuit elements in the circuit design; and completing synthesis placement, routing, and optimization of the circuit design according to the rules, wherein the register transfer language-level construct includes at least one of: (i) a plurality of register banks that are part of a pipelined datapath, and the rules specify spaces between register banks of the pipelined datapath, and the spaces are sufficient for combinational logic coupling together different register banks of the pipelined datapath; and (ii) a multiplexer having a bit width of M and a number of inputs per bit of N, and the multiplexer has a rectangle shape with a width and a height such that M is equal to a product of the width times the height. 9. The method of claim 1 , wherein the register transfer language-level construct includes a shifter. | 0.847432 |
8,046,350 | 1 | 4 | 1. A method performed by one or more server devices, the method comprising: receiving, at one or more processors of the one or more server devices, a query, from a client device, that includes one or more terms; determining, by one or more processors of the one or more server devices, whether the query is a commercial query by: determining whether the one or more terms of the query, in any particular order, matches a commercial query pattern in a list of commercial query patterns, where the list of commercial query patterns includes patterns associated with one or more host names or domain names that include more than a particular number of hyphens, and identifying the query as a commercial query when the one or more terms of the query, in any particular order, matches the commercial query pattern in the list of commercial query patterns; processing, by one or more processors of the one or more server devices, the query in a first processing manner when the query is not determined to be a commercial query, where processing the query in the first processing manner includes ranking documents in a first ranking manner; and processing, by one or more processors of the one or more server devices, the query in a second, different processing manner in response to determining that the query is a commercial query, where processing the query in the second processing manner includes ranking documents in a second, different ranking manner. | 1. A method performed by one or more server devices, the method comprising: receiving, at one or more processors of the one or more server devices, a query, from a client device, that includes one or more terms; determining, by one or more processors of the one or more server devices, whether the query is a commercial query by: determining whether the one or more terms of the query, in any particular order, matches a commercial query pattern in a list of commercial query patterns, where the list of commercial query patterns includes patterns associated with one or more host names or domain names that include more than a particular number of hyphens, and identifying the query as a commercial query when the one or more terms of the query, in any particular order, matches the commercial query pattern in the list of commercial query patterns; processing, by one or more processors of the one or more server devices, the query in a first processing manner when the query is not determined to be a commercial query, where processing the query in the first processing manner includes ranking documents in a first ranking manner; and processing, by one or more processors of the one or more server devices, the query in a second, different processing manner in response to determining that the query is a commercial query, where processing the query in the second processing manner includes ranking documents in a second, different ranking manner. 4. The method of claim 1 where the processing the query in the first processing manner includes: retrieving one or more documents relating to the query, and scoring the one or more documents based at least in part on a first set of criteria. | 0.822009 |
8,525,708 | 2 | 3 | 2. The decoding device according to claim 1 , wherein the i stage decoder connects the one partial symbol to the end of the i−1 partial symbols which are input. | 2. The decoding device according to claim 1 , wherein the i stage decoder connects the one partial symbol to the end of the i−1 partial symbols which are input. 3. The decoding device according to claim 2 , wherein the i stage decoder updates selected probabilistic models per unit cycle and on the basis of one partial symbol. | 0.5 |
10,131,204 | 10 | 11 | 10. The method of claim 8 , further comprising preconditioning by sending an automation command to the vehicle climate-controlled context to instruct the vehicle climate-controlled context to adjust temperature settings of the vehicle climate-controlled context in accordance with the correlation identified according to the user profile. | 10. The method of claim 8 , further comprising preconditioning by sending an automation command to the vehicle climate-controlled context to instruct the vehicle climate-controlled context to adjust temperature settings of the vehicle climate-controlled context in accordance with the correlation identified according to the user profile. 11. The method of claim 10 , wherein the correlation indicates a temperature setting of the vehicle climate-controlled context likely to be selected by the user according to the temperature setting of the home premises climate-controlled context and the current environmental conditions, wherein a temperature setting of the home premises climate-controlled context and the temperature setting of the vehicle climate-controlled context specify different temperatures. | 0.5 |
8,296,679 | 9 | 11 | 9. The electronic device of claim 7 wherein the plurality of objects further comprise a number of candidates, and wherein the operations further comprise: making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment. | 9. The electronic device of claim 7 wherein the plurality of objects further comprise a number of candidates, and wherein the operations further comprise: making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment. 11. The electronic device of claim 9 wherein the plurality of objects further comprise a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the operations further comprise determining that the at least portion of the string of reference characters comprises more than a predetermined quantity of characters and, responsive thereto, storing the at least portion of the string of reference characters as at least a portion of a combination object. | 0.5 |
8,577,908 | 16 | 23 | 16. A tangible computer-readable storage medium containing a program which, when executed by a processor, performs an operation of preventing alterations of data in a database when a query is executed against the database, the operation comprising: providing a logical representation of the data defining a plurality of logical fields abstractly describing a manner of accessing and exposing, via a user interface, associated physical entities of the data, wherein each of the plurality of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entities of the data; and wherein at least a portion of the plurality of logical fields include lock attributes referenced in order to lock the respective logical field; receiving an abstract query comprising at least one logical field of the portion of logical fields; in response to receiving the abstract query, locking the at least one logical field before executing the abstract query on the basis of the respective lock attributes of the at least one logical field; and unlocking at least one logical field after executing the abstract query. | 16. A tangible computer-readable storage medium containing a program which, when executed by a processor, performs an operation of preventing alterations of data in a database when a query is executed against the database, the operation comprising: providing a logical representation of the data defining a plurality of logical fields abstractly describing a manner of accessing and exposing, via a user interface, associated physical entities of the data, wherein each of the plurality of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entities of the data; and wherein at least a portion of the plurality of logical fields include lock attributes referenced in order to lock the respective logical field; receiving an abstract query comprising at least one logical field of the portion of logical fields; in response to receiving the abstract query, locking the at least one logical field before executing the abstract query on the basis of the respective lock attributes of the at least one logical field; and unlocking at least one logical field after executing the abstract query. 23. The computer-readable storage medium of claim 16 , wherein each logical field comprises an access method for the associated physical entity of the data. | 0.907253 |
7,661,071 | 14 | 15 | 14. The method of claim 13 further comprising receiving instructions, in addition to the scene schema, for instantiating the three-dimensional scene. | 14. The method of claim 13 further comprising receiving instructions, in addition to the scene schema, for instantiating the three-dimensional scene. 15. The method of claim 14 , wherein the instructions alter at least one of the behavioral properties. | 0.5 |
8,793,235 | 7 | 9 | 7. A computer-implemented method for prerendering using a search result page, the method comprising: sending a search query to a search engine; receiving a set of search results responsive to the search query, the set of search results comprising at least one prerender instruction indicating at least one of the search results is a candidate for prerendering; identifying the at least one prerender instruction, wherein the at least one prerender instruction is identified using an indication, the indication comprising at least one of: an amount of traffic flowing from the search engine to the at least one search result, a location of a client device that provided the search query, or a size of one or more resources associated with the at least one search result; and prerendering the at least one search result associated with the at least one prerender instruction for loading the search result into a hidden browser instance. | 7. A computer-implemented method for prerendering using a search result page, the method comprising: sending a search query to a search engine; receiving a set of search results responsive to the search query, the set of search results comprising at least one prerender instruction indicating at least one of the search results is a candidate for prerendering; identifying the at least one prerender instruction, wherein the at least one prerender instruction is identified using an indication, the indication comprising at least one of: an amount of traffic flowing from the search engine to the at least one search result, a location of a client device that provided the search query, or a size of one or more resources associated with the at least one search result; and prerendering the at least one search result associated with the at least one prerender instruction for loading the search result into a hidden browser instance. 9. The method of claim 7 , further comprising: storing metrics associated with a selection of a selected search result from the set of search result; and transmitting the metrics to provide statistical data to improve selection of prerendering candidates in response to subsequent search queries. | 0.5 |
9,354,709 | 4 | 5 | 4. The device of claim 3 , wherein: the determining completion of the first stage is further based at least in part on a first confidence score; and the determining completion of the tilt gesture is further based at least in part on a second confidence score. | 4. The device of claim 3 , wherein: the determining completion of the first stage is further based at least in part on a first confidence score; and the determining completion of the tilt gesture is further based at least in part on a second confidence score. 5. The device of claim 4 , wherein: the first confidence score is based at least in part on the first rotation; and the second confidence score is based at least in part on the second rotation. | 0.5 |
9,286,572 | 1 | 2 | 1. A system for managing an autonomous actor network, the system comprising: a metadata collector configured to obtain metadata information associated with the autonomous actor network and autonomous actors included therein; an autonomous actor, said autonomous actor including a self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and a processor configured to generate an assessment value for the autonomous actor based on the obtained metadata information and the self-assessment identifier, wherein the processor is configured to generate the assessment value at least in part by comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process. | 1. A system for managing an autonomous actor network, the system comprising: a metadata collector configured to obtain metadata information associated with the autonomous actor network and autonomous actors included therein; an autonomous actor, said autonomous actor including a self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and a processor configured to generate an assessment value for the autonomous actor based on the obtained metadata information and the self-assessment identifier, wherein the processor is configured to generate the assessment value at least in part by comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process. 2. The system of claim 1 , wherein the metadata information associated with the autonomous actor network comprises at least one of network size, time, physical parameter, or boundary condition for the autonomous actor network. | 0.753275 |
9,268,459 | 2 | 3 | 2. The method of claim 1 , wherein identifying the design example comprises: for each of a subset of the plurality of design examples, comparing a transformation cost corresponding to the second set of UI components with a threshold value. | 2. The method of claim 1 , wherein identifying the design example comprises: for each of a subset of the plurality of design examples, comparing a transformation cost corresponding to the second set of UI components with a threshold value. 3. The method of claim 2 , wherein the transformation cost includes a cost associated with adding a UI component to the second set. | 0.70362 |
8,239,350 | 16 | 24 | 16. A computer system for resolving ambiguities in date values associated with an attribute of an entity, the computer system comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: obtain a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determine if that the first text string conforms to one or more date formats; assign a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtain a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determine if that the second text string conforms to one or more date formats; assign a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determine a first date string expressed in a date format with a highest first confidence value for the first text string; determine a second date string expressed in a date format with a highest second confidence value for the second text string; and merge a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute. | 16. A computer system for resolving ambiguities in date values associated with an attribute of an entity, the computer system comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: obtain a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determine if that the first text string conforms to one or more date formats; assign a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtain a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determine if that the second text string conforms to one or more date formats; assign a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determine a first date string expressed in a date format with a highest first confidence value for the first text string; determine a second date string expressed in a date format with a highest second confidence value for the second text string; and merge a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute. 24. The system of claim 16 , wherein the merging of the date formats retains components of the date format for the first text string and components of the date format for the second text string that are not ambiguous. | 0.71372 |
8,484,077 | 1 | 6 | 1. A computer-implemented method for combining probability of click models in an online advertising system, said method comprising: receiving, at a computer, at least one feature set slice; training, in a computer, a plurality of slice predictive models, the slice predictive models corresponding to at least a portion of the features in the at least one feature set slice; assigning weights, in a computer, to at least two of the plurality of slice predictive models by overlaying a weighted distribution model over the plurality of slice predictive models; and calculating, in a computer, a combined predictive model based on the at least two of the plurality of slice predictive models and their assigned weights. | 1. A computer-implemented method for combining probability of click models in an online advertising system, said method comprising: receiving, at a computer, at least one feature set slice; training, in a computer, a plurality of slice predictive models, the slice predictive models corresponding to at least a portion of the features in the at least one feature set slice; assigning weights, in a computer, to at least two of the plurality of slice predictive models by overlaying a weighted distribution model over the plurality of slice predictive models; and calculating, in a computer, a combined predictive model based on the at least two of the plurality of slice predictive models and their assigned weights. 6. The method of claim 1 , wherein the combined predictive model p(c|x) is calculated using the formula: p ( c = 1 | x ) = 1 1 + exp ( ∑ i = 1 K α i f i ( x ) ) . | 0.631356 |
8,595,845 | 2 | 6 | 2. The non-transitory storage medium of claim 1 , wherein the standardized vulnerability score includes a standardized component and an environmental component adjusting the standardized component to features of a particular system including the asset. | 2. The non-transitory storage medium of claim 1 , wherein the standardized vulnerability score includes a standardized component and an environmental component adjusting the standardized component to features of a particular system including the asset. 6. The non-transitory storage medium of claim 2 , wherein the standardized component includes a temporal component reflecting changes to risk posed by the vulnerability over time. | 0.728788 |
8,719,004 | 5 | 8 | 5. A software product comprising instructions, stored on non-transitory computer-readable media, wherein the instructions, when executed by a computer, perform steps for punctuating voicemail transcription text, comprising: instructions for receiving, at a device, a voicemail message from telecommunication service provider; instructions for transcribing, via the device, the voicemail into a transcription text and determining a beginning time and an ending time of each transcribed word within the voicemail; instructions for identifying Y largest pauses within the transcription text, where Y is a limit on the number of ellipses to be inserted; and instructions for inserting ellipses into the transcription text at the position of the Y largest pauses wherein the Y largest pauses is a number smaller than a total number of pauses of the transcription text. | 5. A software product comprising instructions, stored on non-transitory computer-readable media, wherein the instructions, when executed by a computer, perform steps for punctuating voicemail transcription text, comprising: instructions for receiving, at a device, a voicemail message from telecommunication service provider; instructions for transcribing, via the device, the voicemail into a transcription text and determining a beginning time and an ending time of each transcribed word within the voicemail; instructions for identifying Y largest pauses within the transcription text, where Y is a limit on the number of ellipses to be inserted; and instructions for inserting ellipses into the transcription text at the position of the Y largest pauses wherein the Y largest pauses is a number smaller than a total number of pauses of the transcription text. 8. The software product of claim 5 , further comprising storing the transcription text at a storage device. | 0.5 |
9,208,231 | 1 | 4 | 1. A method performed by one or more data processing apparatus, the method comprising: receiving a search query input through a search engine user interface, wherein the search engine user interface is in a particular language; identifying a first resource that satisfies the search query; accessing click data that identifies a plurality of requests for the first resource, wherein each of the plurality of requests is initiated by a user selection of a search result identifying the first resource; for each of the plurality of requests for the first resource identified in the click data: identifying a respective search engine user interface that received the request of the user selection identifying the first resource, and identifying a search engine user interface language of the respective search engine user interface that received the request; determining a plurality of language relevance scores for the first resource, wherein each language relevance score is a measure of relevance of a respective one of the identified search engine user interface languages of the first resource, and wherein the language relevance scores are based on a number of requests associated with each search engine user interface language; selecting one or more of the identified search engine user interface languages as relevant languages of the first resource based on the language relevance scores; and adjusting a search result score of the first resource based on the particular language being one of the one or more relevant languages of the first resource. | 1. A method performed by one or more data processing apparatus, the method comprising: receiving a search query input through a search engine user interface, wherein the search engine user interface is in a particular language; identifying a first resource that satisfies the search query; accessing click data that identifies a plurality of requests for the first resource, wherein each of the plurality of requests is initiated by a user selection of a search result identifying the first resource; for each of the plurality of requests for the first resource identified in the click data: identifying a respective search engine user interface that received the request of the user selection identifying the first resource, and identifying a search engine user interface language of the respective search engine user interface that received the request; determining a plurality of language relevance scores for the first resource, wherein each language relevance score is a measure of relevance of a respective one of the identified search engine user interface languages of the first resource, and wherein the language relevance scores are based on a number of requests associated with each search engine user interface language; selecting one or more of the identified search engine user interface languages as relevant languages of the first resource based on the language relevance scores; and adjusting a search result score of the first resource based on the particular language being one of the one or more relevant languages of the first resource. 4. The method of claim 1 , wherein determining the plurality of language relevance scores for the first resource comprises: assigning a weight to each of the plurality of requests for the first resource; and calculating the language relevance scores based on the assigned weights. | 0.580838 |
9,201,889 | 4 | 5 | 4. The method of claim 1 , wherein performing, on the computing device, the search based on the search term further comprises: performing, on the computing device, a federated search based on the search term including by accessing the search functionality of the shared storage. | 4. The method of claim 1 , wherein performing, on the computing device, the search based on the search term further comprises: performing, on the computing device, a federated search based on the search term including by accessing the search functionality of the shared storage. 5. The method of claim 4 , further comprising: performing the federated search by accessing a local search functionality of the computing device to search a local storage based on the search term. | 0.5 |
9,501,566 | 1 | 5 | 1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user. | 1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user. 5. The method of claim 1 , further comprising displaying, at the first section of the GUI, the relevance score for each of the concept terms in the set of concept terms, the relevance score indicating a degree of relevance of the corresponding concept term to the input phrase. | 0.642119 |
9,414,040 | 2 | 8 | 2. A processor-based device for providing video content annotation comprising: a receiver interface for receiving a video content; a processor configured to: perform object recognition to identify one or more objects in the video content; generate one or more language tags for at least one of the one or more objects; and associate the one or more language tags with utilization information configured to be used by a user device in the displaying of at least one of the one or more language tags with the video content; and a network interface for providing the one or more language tags with associated utilization information to one or more user devices over a network. | 2. A processor-based device for providing video content annotation comprising: a receiver interface for receiving a video content; a processor configured to: perform object recognition to identify one or more objects in the video content; generate one or more language tags for at least one of the one or more objects; and associate the one or more language tags with utilization information configured to be used by a user device in the displaying of at least one of the one or more language tags with the video content; and a network interface for providing the one or more language tags with associated utilization information to one or more user devices over a network. 8. The processor-based device of claim 2 , wherein the one or more language tags are provided in a audio stream tags of a streaming video content. | 0.676991 |
7,475,010 | 1 | 7 | 1. A method for resolving natural language ambiguities within text documents on a computer system comprising a processor and memory that would cause the processor to perform the following, comprising the steps of: i. training probabilistic classifiers from annotated training data containing a sense tag for each polysemous word; ii. processing said text documents into tokens and determining their part-of-speech tags; iii computing a measure of confidence using said probabilistic classifiers for each known sense of said tokens defined within a semantic lexicon based on contextual features and assigning a default sense for tokens absent from said semantic lexicon based on their part-of-speech tags; iv. determining assignment of word senses for each said token in said sentence such that the combined probability across said sentence is maximized; and v. integrating additional contextual features as generated by one or more of the following natural language processing modules into said probabilistic classifiers whereby said measure of confidence is improved: using a chunking module to identify multi-word phrases and the associated measure of confidence for each phrase; using a named-entity recognition module to identify named entities and the associated measure of confidence for each entity; using a syntactic parsing module to construct sentential parse trees and the associated measure of confidence for each tree; using an anaphora resolution module to identify anaphor references and the associated measure of confidence for each reference; using a discourse categorization module to determine document categories and the associated measure of confidence for each category; using a discourse structure analysis module to determine discourse structures and the associated measure of confidence for each structure. | 1. A method for resolving natural language ambiguities within text documents on a computer system comprising a processor and memory that would cause the processor to perform the following, comprising the steps of: i. training probabilistic classifiers from annotated training data containing a sense tag for each polysemous word; ii. processing said text documents into tokens and determining their part-of-speech tags; iii computing a measure of confidence using said probabilistic classifiers for each known sense of said tokens defined within a semantic lexicon based on contextual features and assigning a default sense for tokens absent from said semantic lexicon based on their part-of-speech tags; iv. determining assignment of word senses for each said token in said sentence such that the combined probability across said sentence is maximized; and v. integrating additional contextual features as generated by one or more of the following natural language processing modules into said probabilistic classifiers whereby said measure of confidence is improved: using a chunking module to identify multi-word phrases and the associated measure of confidence for each phrase; using a named-entity recognition module to identify named entities and the associated measure of confidence for each entity; using a syntactic parsing module to construct sentential parse trees and the associated measure of confidence for each tree; using an anaphora resolution module to identify anaphor references and the associated measure of confidence for each reference; using a discourse categorization module to determine document categories and the associated measure of confidence for each category; using a discourse structure analysis module to determine discourse structures and the associated measure of confidence for each structure. 7. The method for resolving natural language ambiguities within text documents of claim 1 , further comprising resolving structural ambiguities of said text documents using a syntactical parsing module whereby additional contextual features are extracted. | 0.92685 |
7,900,174 | 7 | 8 | 7. The method according to claim 1 , wherein performing the one or more simulations comprises: performing a simulation for a first value of a design parameter, wherein the first value is user-specified; performing a simulation for a second value of a design parameter, wherein the second value is user-specified; and implementing a sectional algorithm for determining at least one range of the one or more values of the one or more design parameters. | 7. The method according to claim 1 , wherein performing the one or more simulations comprises: performing a simulation for a first value of a design parameter, wherein the first value is user-specified; performing a simulation for a second value of a design parameter, wherein the second value is user-specified; and implementing a sectional algorithm for determining at least one range of the one or more values of the one or more design parameters. 8. The method according to claim 7 further comprising generating a test file for performing the one or more simulations, wherein the one or more simulations is performed on the range of the one or more values of the one or more design parameters. | 0.5 |
8,245,132 | 1 | 10 | 1. A computer-implemented system including a computer processor configured to create an advertisement, the system comprising: a. an administrative toolkit configured to facilitate a template creator at a first location to create a template comprising a plurality of template portions, and to input content components to populate the template, the administrative toolkit comprising: i. a template definition and editing module configured to: 1. create the template at a development site accessible to the template creator and not accessible to an end user; and 2. establish rules governing content to be placed in one or more of the template portions; and ii. a template inventory management module configured to move a copy of the template from the development site to a production site accessible to the end user, thereby updating the production site; and b. an end-user interface configured to facilitate the end user at a second location to: i. access the copy of the template over an information exchange network after the copy of the template has been moved to the production site; and ii. populate one or more of the portions with content in accordance with the rules established by the template creator, whereby the end user can create a customized advertisement that conforms to standards set by the template creator, wherein: the administrative toolkit is different and separate from the end-user interface. | 1. A computer-implemented system including a computer processor configured to create an advertisement, the system comprising: a. an administrative toolkit configured to facilitate a template creator at a first location to create a template comprising a plurality of template portions, and to input content components to populate the template, the administrative toolkit comprising: i. a template definition and editing module configured to: 1. create the template at a development site accessible to the template creator and not accessible to an end user; and 2. establish rules governing content to be placed in one or more of the template portions; and ii. a template inventory management module configured to move a copy of the template from the development site to a production site accessible to the end user, thereby updating the production site; and b. an end-user interface configured to facilitate the end user at a second location to: i. access the copy of the template over an information exchange network after the copy of the template has been moved to the production site; and ii. populate one or more of the portions with content in accordance with the rules established by the template creator, whereby the end user can create a customized advertisement that conforms to standards set by the template creator, wherein: the administrative toolkit is different and separate from the end-user interface. 10. The system of claim 1 , wherein the advertisement is a print publication. | 0.865385 |
8,131,647 | 19 | 21 | 19. The method of claim 1 , wherein the user has obtained the authorization credential in exchange for user-performance of a specified action. | 19. The method of claim 1 , wherein the user has obtained the authorization credential in exchange for user-performance of a specified action. 21. The method of claim 19 , wherein the specified action is contributing an annotation of a digital work. | 0.5 |
9,900,271 | 1 | 4 | 1. A method for displaying a plurality of chat threads on a wireless mobile terminal comprising a user input device and a display, the method comprising: receiving a plurality of inbound chat messages corresponding to the plurality of chat threads, each of the plurality of inbound chat messages comprising message content; transmitting a plurality of outbound chat messages from the wireless mobile terminal corresponding to the plurality of chat threads, each of the plurality of outbound chat messages comprising message content and being transmitted to at least one user-selected recipient to thereby become a sent chat message, wherein one or more of the pluralities of inbound and outbound messages further comprise speech content; for each outbound chat message that is a speech chat message, further transmitting a copy of the speech chat message to the wireless mobile terminal as an input chat message; simultaneously displaying the message content of each of the pluralities of inbound and sent chat messages corresponding to the plurality of chat threads in a single content region of a chat history display; receiving at the user input device a user selection of the displayed message content of a user-selected displayed chat message corresponding to one of the displayed pluralities of inbound and sent chat messages; and in response to the user selection of the displayed message content of the user-selected displayed chat message, visually highlighting in the single content region of the chat history display the displayed message content of each of the displayed inbound and sent chat messages associated with a particular chat thread corresponding to the user-selected displayed chat message and further in response to said user selection, displaying in the chat history display a plurality of display identifiers representative of a sender and each of one or more recipients of the user-selected displayed chat message. | 1. A method for displaying a plurality of chat threads on a wireless mobile terminal comprising a user input device and a display, the method comprising: receiving a plurality of inbound chat messages corresponding to the plurality of chat threads, each of the plurality of inbound chat messages comprising message content; transmitting a plurality of outbound chat messages from the wireless mobile terminal corresponding to the plurality of chat threads, each of the plurality of outbound chat messages comprising message content and being transmitted to at least one user-selected recipient to thereby become a sent chat message, wherein one or more of the pluralities of inbound and outbound messages further comprise speech content; for each outbound chat message that is a speech chat message, further transmitting a copy of the speech chat message to the wireless mobile terminal as an input chat message; simultaneously displaying the message content of each of the pluralities of inbound and sent chat messages corresponding to the plurality of chat threads in a single content region of a chat history display; receiving at the user input device a user selection of the displayed message content of a user-selected displayed chat message corresponding to one of the displayed pluralities of inbound and sent chat messages; and in response to the user selection of the displayed message content of the user-selected displayed chat message, visually highlighting in the single content region of the chat history display the displayed message content of each of the displayed inbound and sent chat messages associated with a particular chat thread corresponding to the user-selected displayed chat message and further in response to said user selection, displaying in the chat history display a plurality of display identifiers representative of a sender and each of one or more recipients of the user-selected displayed chat message. 4. The method of claim 1 , wherein the copy of the speech chat message transmitted to the wireless mobile terminal is equivalent to the output speech chat message originally transmitted to the wireless mobile terminal. | 0.643791 |
9,852,205 | 16 | 17 | 16. A computer readable storage medium storing computer executable instructions configured for execution by one or more processors of a computer system to configure the one or more processors to: generate a graphical user interface including at least a representation of a plurality of dimensions of a multidimensional data set; receive, via the graphical user interface, a selection of at least two dimensions of the multidimensional data set; determine a plurality of data objects each corresponding to different combinations of values of the selected dimensions; generate a plurality of two-dimensional graphs that are spatially positioned in a single graphical user interface view, wherein: each of the two-dimensional graphs is generated based on data associated with a respective one of the plurality of data objects, each of the two-dimensional graphs comprises a respective x-axis and a respective y-axis, the x-axes of the two-dimensional graphs each have a first common scale and a first common interval, and the y-axes of the two-dimensional graphs each have a second common scale and a second common interval, and data represented in each respective two-dimensional graph is shown according to the first common scale and the first common interval of the x-axes and the second common scale and the second common interval of the y-axes; and update the graphical user interface to display the single graphical user interface view including the plurality of two-dimensional graphs, wherein: the plurality of two-dimensional graphs are displayed in a plurality of rows and columns, each combination of row and column corresponds to a different respective combination of values of the selected dimensions, and the plurality of two-dimensional graphs are spatially positioned in the single graphical user interface view in corresponding rows and columns to enable a user to directly compare data represented in the plurality of two-dimensional graphs to view differences in data across the selected dimensions. | 16. A computer readable storage medium storing computer executable instructions configured for execution by one or more processors of a computer system to configure the one or more processors to: generate a graphical user interface including at least a representation of a plurality of dimensions of a multidimensional data set; receive, via the graphical user interface, a selection of at least two dimensions of the multidimensional data set; determine a plurality of data objects each corresponding to different combinations of values of the selected dimensions; generate a plurality of two-dimensional graphs that are spatially positioned in a single graphical user interface view, wherein: each of the two-dimensional graphs is generated based on data associated with a respective one of the plurality of data objects, each of the two-dimensional graphs comprises a respective x-axis and a respective y-axis, the x-axes of the two-dimensional graphs each have a first common scale and a first common interval, and the y-axes of the two-dimensional graphs each have a second common scale and a second common interval, and data represented in each respective two-dimensional graph is shown according to the first common scale and the first common interval of the x-axes and the second common scale and the second common interval of the y-axes; and update the graphical user interface to display the single graphical user interface view including the plurality of two-dimensional graphs, wherein: the plurality of two-dimensional graphs are displayed in a plurality of rows and columns, each combination of row and column corresponds to a different respective combination of values of the selected dimensions, and the plurality of two-dimensional graphs are spatially positioned in the single graphical user interface view in corresponding rows and columns to enable a user to directly compare data represented in the plurality of two-dimensional graphs to view differences in data across the selected dimensions. 17. The computer readable storage medium of claim 16 , wherein the one or more processors are further configured to: receive, via the graphical user interface, an indication of a new interval and a mathematical operation; apply the mathematical operation to the determined data objects; re-generate the plurality of two-dimensional graphs such that: at least one of the first common interval or the second common interview corresponds to the new interval; and at least one of the x-axis or the y-axis of each of the two-dimensional graphs represents an output of the applied mathematical operation; and update the graphical user interface to display the single graphical user interface view including the re-generated two-dimensional graphs. | 0.5 |
8,924,923 | 10 | 19 | 10. A method of generating a multi-level test case in an apparatus of generating a multi-level test case from a unified modeling language (UML) sequence diagram (SD) based on a multiple condition control flow graph (MCCFG), the method comprising the steps of: model-converting, by a model converting unit, the unified modeling language (UML) sequence diagram (SD) according to a unified modeling language (UML) sequence diagram (SD) metamodel and a multiple condition control flow graph (MCCFG) metamodel to generate the multiple condition control flow graph (MCCFG); and converting, by a coverage criteria unit, the multiple condition control flow graph (MCCFG) into a plurality of test cases. | 10. A method of generating a multi-level test case in an apparatus of generating a multi-level test case from a unified modeling language (UML) sequence diagram (SD) based on a multiple condition control flow graph (MCCFG), the method comprising the steps of: model-converting, by a model converting unit, the unified modeling language (UML) sequence diagram (SD) according to a unified modeling language (UML) sequence diagram (SD) metamodel and a multiple condition control flow graph (MCCFG) metamodel to generate the multiple condition control flow graph (MCCFG); and converting, by a coverage criteria unit, the multiple condition control flow graph (MCCFG) into a plurality of test cases. 19. The method of claim 10 , wherein in the converting, each of the plurality of test cases is generated so as to be divided into at least five of Test scenario ID, Testcase ID, Inflow, Event, Condition, and Outflow. | 0.781818 |
9,984,392 | 1 | 7 | 1. A computer-implemented method comprising: accessing profiles for a plurality of users of the social networking system, each profile identifying a connection to each of a plurality of other users of the social networking system, the plurality of users comprising a viewing user; receiving a message from a third party system that is in a different domain than the social networking system, the message identifying the third party system and describing an action performed on a web page of the third party system by the viewing user; generating, by a computer of the social networking system, a confirmation message for display in a user interface to the viewing user on the third party system, the confirmation message providing an example of a story that could be provided to a plurality of connections of the viewing user, the story describing the action performed on the third party system by the viewing user; sending, by the computer of the social networking system to the third party system, the generated confirmation message for display in the user interface within a nested iframe on the web page of the third party system, the nested iframe being within a domain of the social networking system and allowing communication from the social networking system to the user on the web page of the third party system without sharing personal information that the social networking system has for the viewing user; receiving an indication of whether the viewing user opts in or opts out of allowing the story describing the action performed on the third party system by the viewing user to be provided to the plurality of connections based on the user having selected an opt in or opt out feature in the nested iframe on the user interface; based on the viewing user opting in to allowing the story to be provided to the plurality of connections, generating a plurality of news feeds each including the story describing the action in addition to a plurality of other stories describing other actions taken by other users of the social networking system; and providing for display to each of the plurality of connections a user interface including the generated news feed for the connection, wherein different connections receive different sets of other stories in the news feed. | 1. A computer-implemented method comprising: accessing profiles for a plurality of users of the social networking system, each profile identifying a connection to each of a plurality of other users of the social networking system, the plurality of users comprising a viewing user; receiving a message from a third party system that is in a different domain than the social networking system, the message identifying the third party system and describing an action performed on a web page of the third party system by the viewing user; generating, by a computer of the social networking system, a confirmation message for display in a user interface to the viewing user on the third party system, the confirmation message providing an example of a story that could be provided to a plurality of connections of the viewing user, the story describing the action performed on the third party system by the viewing user; sending, by the computer of the social networking system to the third party system, the generated confirmation message for display in the user interface within a nested iframe on the web page of the third party system, the nested iframe being within a domain of the social networking system and allowing communication from the social networking system to the user on the web page of the third party system without sharing personal information that the social networking system has for the viewing user; receiving an indication of whether the viewing user opts in or opts out of allowing the story describing the action performed on the third party system by the viewing user to be provided to the plurality of connections based on the user having selected an opt in or opt out feature in the nested iframe on the user interface; based on the viewing user opting in to allowing the story to be provided to the plurality of connections, generating a plurality of news feeds each including the story describing the action in addition to a plurality of other stories describing other actions taken by other users of the social networking system; and providing for display to each of the plurality of connections a user interface including the generated news feed for the connection, wherein different connections receive different sets of other stories in the news feed. 7. The method of claim 1 , further comprising based on the viewing user opting out of allowing the story to be provided to the one or more connections, preventing the story describing the action performed on the third party system from being provided to connections of the viewing user. | 0.597183 |
7,805,704 | 8 | 12 | 8. A computer-implemented method for enabling a developer of a voice user interface to mix different types of audible dialog prompts within the voice user interface, the method comprising: providing, within a development framework utilized by the developer to selectively configure audible dialog prompts within the voice user interface, a first dialog container that includes instructions that are executed by a computer processor that is a component of a computing device so as to activate, in a predetermined sequence, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the first dialog container, the predetermined sequence being at least partially determined by semantics-driven audible dialog logic embedded within the first dialog container so as to delegate functions to dialog elements assigned to the first dialog container; and providing, within the development framework, a second dialog container that includes instructions that are executed by the computer processor so as to activate, in a predetermined order, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the second dialog container, the predetermined order being at least partially determined by state-driven audible dialog logic embedded within the second dialog container so as to delegate functions to dialog elements assigned to the second dialog container. | 8. A computer-implemented method for enabling a developer of a voice user interface to mix different types of audible dialog prompts within the voice user interface, the method comprising: providing, within a development framework utilized by the developer to selectively configure audible dialog prompts within the voice user interface, a first dialog container that includes instructions that are executed by a computer processor that is a component of a computing device so as to activate, in a predetermined sequence, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the first dialog container, the predetermined sequence being at least partially determined by semantics-driven audible dialog logic embedded within the first dialog container so as to delegate functions to dialog elements assigned to the first dialog container; and providing, within the development framework, a second dialog container that includes instructions that are executed by the computer processor so as to activate, in a predetermined order, audible dialog prompts that correspond to a collection of audible dialog elements assigned to the second dialog container, the predetermined order being at least partially determined by state-driven audible dialog logic embedded within the second dialog container so as to delegate functions to dialog elements assigned to the second dialog container. 12. The method of claim 8 , wherein the collection of audible dialog elements assigned to the first dialog container includes an audible dialog element that is a FormFillingDialog element, wherein the FormFillingDialog element includes computer readable instructions that, when executed by the computer processor, facilitate a semantic-driven audible dialog with a user through the voice user interface, wherein the semantic-driven dialog includes audible dialog prompts provided to the user in a manner that prompts the user through a process of filling in fields within a form. | 0.5 |
9,342,580 | 1 | 8 | 1. A computer-implemented method for analyzing media content, the method comprising: accessing demographics information of a plurality of users to identify a subset of the plurality of users; accessing outcome measure information of the subset of the plurality of users, the outcome measure information relating to a plurality of media content, the plurality of media content comprising a first media content and a second media content; calculating a first outcome measure for the first media content, the first outcome measure based on the outcome measure information; calculating a second outcome measure for the second media content, the second outcome measure based on the outcome measure information; accessing respective character models of one or more characters depicted in the first media content; accessing respective character models of one or more characters depicted in the second media content; determining, for the first media content: a first attribute value of a first attribute of the one or more characters depicted in the first media content, the determination based on the respective character models and in accordance with a first capture function; and a second attribute value of a second attribute of the one or more characters depicted in the first media content, the determination based on the respective character models and in accordance with a second capture function; determining, for the second media content: a third attribute value of the first attribute of the one or more characters depicted in the second media content, the determination based on the respective character models and in accordance with the first capture function; and a fourth attribute value of the second attribute of the one or more characters depicted in the second media content, the determination based on the respective character models and in accordance with the second capture function; and performing a regression using the first attribute value, the second attribute value, the third attribute value, the fourth attribute value, the first outcome measure, and the second outcome measure to determine at least one attribute of significance. | 1. A computer-implemented method for analyzing media content, the method comprising: accessing demographics information of a plurality of users to identify a subset of the plurality of users; accessing outcome measure information of the subset of the plurality of users, the outcome measure information relating to a plurality of media content, the plurality of media content comprising a first media content and a second media content; calculating a first outcome measure for the first media content, the first outcome measure based on the outcome measure information; calculating a second outcome measure for the second media content, the second outcome measure based on the outcome measure information; accessing respective character models of one or more characters depicted in the first media content; accessing respective character models of one or more characters depicted in the second media content; determining, for the first media content: a first attribute value of a first attribute of the one or more characters depicted in the first media content, the determination based on the respective character models and in accordance with a first capture function; and a second attribute value of a second attribute of the one or more characters depicted in the first media content, the determination based on the respective character models and in accordance with a second capture function; determining, for the second media content: a third attribute value of the first attribute of the one or more characters depicted in the second media content, the determination based on the respective character models and in accordance with the first capture function; and a fourth attribute value of the second attribute of the one or more characters depicted in the second media content, the determination based on the respective character models and in accordance with the second capture function; and performing a regression using the first attribute value, the second attribute value, the third attribute value, the fourth attribute value, the first outcome measure, and the second outcome measure to determine at least one attribute of significance. 8. The computer-implemented method of claim 1 , the method further comprising: displaying media analytics for the at least one attribute of significance, wherein the at least one attribute of significance is determined based on a value of the at least one attribute of significance exceeding a threshold significance value. | 0.848071 |
9,378,254 | 9 | 12 | 9. An information handling system comprising: a plurality of processors; a memory coupled to at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors to copy records between tables in a relational database, wherein the set of instructions perform actions of: receiving a Structured Query Language (SQL) table COPY statement, wherein the COPY statement is devoid of an INSERT clause and identifies a source table and a target table; retrieving a plurality of column names from a metadata corresponding to the source table; and generating an SQL statement, based upon the COPY statement, that includes an INSERT INTO clause pertaining to the target table and a SELECT clause pertaining to the source table, wherein the INSERT INTO clause includes a set of target column names corresponding to the plurality of column names, and wherein the SELECT clause includes a set of corresponding source column names. | 9. An information handling system comprising: a plurality of processors; a memory coupled to at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors to copy records between tables in a relational database, wherein the set of instructions perform actions of: receiving a Structured Query Language (SQL) table COPY statement, wherein the COPY statement is devoid of an INSERT clause and identifies a source table and a target table; retrieving a plurality of column names from a metadata corresponding to the source table; and generating an SQL statement, based upon the COPY statement, that includes an INSERT INTO clause pertaining to the target table and a SELECT clause pertaining to the source table, wherein the INSERT INTO clause includes a set of target column names corresponding to the plurality of column names, and wherein the SELECT clause includes a set of corresponding source column names. 12. The information handling system of claim 9 wherein the COPY statement further identifies a WHERE clause that includes a WHERE clause expression, and wherein the actions performed further comprise: including the WHERE clause in the generated SQL statement. | 0.913378 |
6,076,061 | 7 | 8 | 7. The speech recognition apparatus according to claim 6, wherein said changing means sets a plurality of areas each of which is related to a different class of recognition information and controls the weight for each class of the recognition information in accordance with relationship between the viewpoint detected by said detecting means and each of the plurality of areas. | 7. The speech recognition apparatus according to claim 6, wherein said changing means sets a plurality of areas each of which is related to a different class of recognition information and controls the weight for each class of the recognition information in accordance with relationship between the viewpoint detected by said detecting means and each of the plurality of areas. 8. The speech recognition apparatus according to claim 7, wherein one of the plurality of areas is set for each respective image, shown on a display screen, representing an application and has a predetermined size in which the image is included. | 0.69375 |
7,516,468 | 21 | 22 | 21. The system of claim 20 further including: receiving a selection of one of the product descriptions from the user; and transmitting the selection to a transaction server, the transaction server for implementing a transaction in accordance with the selection. | 21. The system of claim 20 further including: receiving a selection of one of the product descriptions from the user; and transmitting the selection to a transaction server, the transaction server for implementing a transaction in accordance with the selection. 22. The system of claim 21 wherein the selection is transmitted from the receiver to the transaction server using a modem. | 0.5 |
7,899,657 | 32 | 42 | 32. A computer-based system for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the system comprising: a computer, comprising: a processor; and a memory medium coupled to the processor; an input coupled to the processor and the memory medium, wherein the input is operable to receive a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations of said reservoir; and an output coupled to the processor and the memory medium; wherein the memory medium stores program instructions which are executable by the processor to: receive a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterize the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively perform said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and store the parameterized model in the memory medium, wherein the parameterized model is usable to analyze reservoir operations; and wherein the output is operable to provide the parameterized model and/or the resulting model output values to other systems or processes to manage the reservoir operations. | 32. A computer-based system for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the system comprising: a computer, comprising: a processor; and a memory medium coupled to the processor; an input coupled to the processor and the memory medium, wherein the input is operable to receive a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations of said reservoir; and an output coupled to the processor and the memory medium; wherein the memory medium stores program instructions which are executable by the processor to: receive a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterize the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively perform said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and store the parameterized model in the memory medium, wherein the parameterized model is usable to analyze reservoir operations; and wherein the output is operable to provide the parameterized model and/or the resulting model output values to other systems or processes to manage the reservoir operations. 42. The system of claim 32 , wherein said one or more derivative constraints comprise: estimated allowable ranges for one or more derivatives. | 0.818878 |
8,914,276 | 1 | 3 | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. | 1. A computer-implemented method to provide automated translation of video captions and playback to one or more clients, the method comprising: receiving an indication of a video that includes associated caption text; identifying a source language associated with the caption text without playing the video; selecting a target language to which to translate the associated caption text from the identified source language; automatically translating the caption text from the identified source language to the selected target language without playing the video; storing the translated captions in a caption file after automatically translating the caption text; repackaging the received video and translated captions so that the video can be played with the new captions; and playing the received video and displaying each translated caption at appropriate points during the video, wherein the preceding steps are performed by at least one processor. 3. The method of claim 1 wherein receiving the video comprises providing a path to a video host that hosts the video and provides automated translation as needed based on client requests for translation. | 0.552863 |
5,511,199 | 24 | 25 | 24. The method of claim 23, wherein said second computer program includes at least one child class and at least one parent class, and each description of a child class includes a pointer to a description of its parent class. | 24. The method of claim 23, wherein said second computer program includes at least one child class and at least one parent class, and each description of a child class includes a pointer to a description of its parent class. 25. The method of claim 24, wherein each description of a class includes a list of functions provided by that class, further comprising the steps of determining whether the target function is provided by said target class and if not provided, then reading said pointer to said parent class description and searching said target function in a corresponding list of function of the parent class. | 0.5 |
8,886,624 | 1 | 2 | 1. A search system using an extended keyword pool, the system comprising: a processor including a purchased keyword module configured to generate a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; the processor including an additional keyword module configured to generate an additional keyword set by extracting a keyword from at least one source; the processor including a unified search keyword module configured to generate a unified search keyword set by searching for a keyword having a number of hits greater than a determined number of hits during a determined period; and the processor including a search module configured to, provide an associated keyword or an extended keyword with respect to a search word, using an extended keyword pool, the extended keyword pool being generated such that the purchased keyword set, the additional keyword set, and the unified search keyword set are connected to one another, provide the associated keyword or the extended keyword with respect to the search word based on new keyword scores or associated scores of keywords included in the extended keyword pool, increase the new keyword scores of the keywords included in the unified search keyword set, excluding the keywords included in the purchased keyword set and the additional keyword set, and increase the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. | 1. A search system using an extended keyword pool, the system comprising: a processor including a purchased keyword module configured to generate a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; the processor including an additional keyword module configured to generate an additional keyword set by extracting a keyword from at least one source; the processor including a unified search keyword module configured to generate a unified search keyword set by searching for a keyword having a number of hits greater than a determined number of hits during a determined period; and the processor including a search module configured to, provide an associated keyword or an extended keyword with respect to a search word, using an extended keyword pool, the extended keyword pool being generated such that the purchased keyword set, the additional keyword set, and the unified search keyword set are connected to one another, provide the associated keyword or the extended keyword with respect to the search word based on new keyword scores or associated scores of keywords included in the extended keyword pool, increase the new keyword scores of the keywords included in the unified search keyword set, excluding the keywords included in the purchased keyword set and the additional keyword set, and increase the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. 2. The system of claim 1 , wherein the purchased keyword module is configured to update the purchased keyword set by adding, to the purchased keyword set, a keyword that shows an increase in a corresponding purchase history through the search advertisement of greater than a determined amount, during a desired period, and the purchased keyword module is configured to update the purchased keyword set by removing, from the purchased keyword set, a keyword that does not have an increase in the corresponding purchase history through the search advertisement during the desired period. | 0.644593 |
9,686,595 | 1 | 5 | 1. A method for providing audio-based guidance in a media guide, the method comprising: receiving a plurality of listings, wherein each of the plurality of listings is associated with a respective media item of a plurality of media items, the plurality of media items including a first media item having audio-friendly characteristics that make media content desirable to users who have difficulties viewing or understanding a visual portion of the content, the plurality of media items including a second media item not having the audio-friendly characteristics; generating for display the plurality of listings; receiving a first user command to navigate to a listing associated with the first media item; automatically determining that the first media item has the audio-friendly characteristics; and playing an audio notification when the first media item is determined to have the audio-friendly characteristics. | 1. A method for providing audio-based guidance in a media guide, the method comprising: receiving a plurality of listings, wherein each of the plurality of listings is associated with a respective media item of a plurality of media items, the plurality of media items including a first media item having audio-friendly characteristics that make media content desirable to users who have difficulties viewing or understanding a visual portion of the content, the plurality of media items including a second media item not having the audio-friendly characteristics; generating for display the plurality of listings; receiving a first user command to navigate to a listing associated with the first media item; automatically determining that the first media item has the audio-friendly characteristics; and playing an audio notification when the first media item is determined to have the audio-friendly characteristics. 5. The method of claim 1 , wherein the plurality of media items comprises Internet-delivered content items and the audio-friendly characteristics comprise audio clips or streams that describe the visual portion of the content. | 0.55336 |
5,548,681 | 9 | 10 | 9. The speech dialogue system of claim 8, wherein the speech segment detection means obtains the power level of the synthetic speech response by calculating a convolution of the synthetic speech response and an estimate for the filter coefficients. | 9. The speech dialogue system of claim 8, wherein the speech segment detection means obtains the power level of the synthetic speech response by calculating a convolution of the synthetic speech response and an estimate for the filter coefficients. 10. The speech dialogue system of claim 9, wherein the estimate for the filter coefficients is obtained by adding a wide frequency band noise to the synthetic speech response. | 0.537037 |
9,836,288 | 10 | 11 | 10. The system of claim 7 , wherein the optimization engine is further configured to replace the first optimized code portion with the programmatic expression. | 10. The system of claim 7 , wherein the optimization engine is further configured to replace the first optimized code portion with the programmatic expression. 11. The system of claim 10 , wherein the execution engine is further configured to execute the optimized application source code using an interpreter. | 0.5 |
9,864,744 | 1 | 2 | 1. A method, performed by a computing device, for mining translation pairs for training in-domain machine translation engines, comprising: obtaining one or more sources of potential translation pairs comprising one or more content items, wherein the one or more sources of potential translation pairs are in an identified domain for which a machine translation engine is to be trained; generating one or more potential translation pairs from the obtained one or more sources of potential translation pairs by applying one or more automated filtering techniques to the obtained one or more sources of potential translation pairs, wherein one of the one or more automated filtering techniques applied to a selected obtained source of potential translation pairs is configured based on a type of the selected obtained source of potential translation pairs, and wherein each of the one or more potential translation pairs comprises at least two language snippets; selecting at least one actual translation pair from the generated one or more potential translation pairs, said selecting comprising: extracting characteristics from each of the two language snippets of at least one of the one or more potential translation pairs; determining that the two language snippets of the at least one of the one or more potential translation pairs are translations of each other by comparing the extracted characteristics; and training the machine translation engine using the selected at least one actual translation pair. | 1. A method, performed by a computing device, for mining translation pairs for training in-domain machine translation engines, comprising: obtaining one or more sources of potential translation pairs comprising one or more content items, wherein the one or more sources of potential translation pairs are in an identified domain for which a machine translation engine is to be trained; generating one or more potential translation pairs from the obtained one or more sources of potential translation pairs by applying one or more automated filtering techniques to the obtained one or more sources of potential translation pairs, wherein one of the one or more automated filtering techniques applied to a selected obtained source of potential translation pairs is configured based on a type of the selected obtained source of potential translation pairs, and wherein each of the one or more potential translation pairs comprises at least two language snippets; selecting at least one actual translation pair from the generated one or more potential translation pairs, said selecting comprising: extracting characteristics from each of the two language snippets of at least one of the one or more potential translation pairs; determining that the two language snippets of the at least one of the one or more potential translation pairs are translations of each other by comparing the extracted characteristics; and training the machine translation engine using the selected at least one actual translation pair. 2. The method of claim 1 , wherein: the obtained one or more sources of potential translation pairs comprise single content items that each contain multiple languages; each of the at least two language snippets for each potential translation pair is a portion of one of the single content items; each of the at least two language snippets for each potential translation pair comprises two or more consecutive words for which a particular language has been identified; and the identified domain for which the machine translation engine is to be trained is a social media domain. | 0.581277 |
8,275,362 | 1 | 8 | 1. A computer-implemented method of presenting information to a user in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. | 1. A computer-implemented method of presenting information to a user in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. 8. The computer-implemented method of claim 1 , wherein receiving the one or more ambiguous characters includes: receiving the one or more ambiguous characters in a keyword retrieval field of a web browser application; wherein rendering the results includes displaying a drop down window adjacent to the keyword retrieval field while the user inputs the ambiguous characters, the drop down window displaying likely results for the ambiguous characters; and updating the displayed likely results upon receiving additional ambiguous characters from the user. | 0.577508 |
9,437,207 | 19 | 22 | 19. A computer-implemented method for processing speech data in accordance with a privacy regulation, the method comprising: receiving, from a user device executing an entertainment application, a raw audio waveform that includes speech data of a user, wherein the raw audio waveform is recorded by the user device in response to the user interacting with the entertainment application; providing metadata and the raw audio waveform to a speech processing environment controlled by a third party for processing, where the metadata identifies a frequency component of a frequency representation of the raw audio waveform that is to be modified; directing the third party to perform an anonymization operation on the raw audio waveform before performing a speech processing operation, wherein the anonymization operation includes generating the frequency representation of the raw audio waveform, modifying the frequency component of the frequency representation that could be used to identify the user in order to produce a modified frequency representation, and generating an anonymized representation of the raw audio waveform from the modified frequency representation; allowing the third-party speech processing system to copy an element of the anonymized representation to improve future instances of speech processing; receiving, from the speech processing environment, a textual depiction of speech in the anonymized representation of the raw audio waveform; determining a responsive action for a synthetic character based at least in part on the textual depiction; and transmitting, to the user device, an instruction indicative of the responsive action for execution by the user device, wherein execution of the instruction causes the synthetic character to perform the responsive action within the entertainment application. | 19. A computer-implemented method for processing speech data in accordance with a privacy regulation, the method comprising: receiving, from a user device executing an entertainment application, a raw audio waveform that includes speech data of a user, wherein the raw audio waveform is recorded by the user device in response to the user interacting with the entertainment application; providing metadata and the raw audio waveform to a speech processing environment controlled by a third party for processing, where the metadata identifies a frequency component of a frequency representation of the raw audio waveform that is to be modified; directing the third party to perform an anonymization operation on the raw audio waveform before performing a speech processing operation, wherein the anonymization operation includes generating the frequency representation of the raw audio waveform, modifying the frequency component of the frequency representation that could be used to identify the user in order to produce a modified frequency representation, and generating an anonymized representation of the raw audio waveform from the modified frequency representation; allowing the third-party speech processing system to copy an element of the anonymized representation to improve future instances of speech processing; receiving, from the speech processing environment, a textual depiction of speech in the anonymized representation of the raw audio waveform; determining a responsive action for a synthetic character based at least in part on the textual depiction; and transmitting, to the user device, an instruction indicative of the responsive action for execution by the user device, wherein execution of the instruction causes the synthetic character to perform the responsive action within the entertainment application. 22. The method of claim 19 , wherein the speech processing environment comprises a server, and wherein providing the raw audio waveform to the speech processing environment requires the raw audio waveform be transmitted to the server over a network. | 0.555357 |
9,703,883 | 12 | 17 | 12. A system comprising: at least one processor; at least one computer readable memory, said computer readable memory having program code stored thereon, said program code comprising: program code for receiving a request for a social bookmarking operation; program code for, responsive to said request for said social bookmarking operation, searching a document object model (DOM) of a currently loaded Web page for elements identifying corresponding socially bookmarkable resources displayed within said currently loaded Web page by checking elements in said DOM for elements having a class name matching a predetermined class name, wherein each of said socially bookmarkable resources identified by an element found in said searching is available for performing said requested social bookmarking operation, and modifying said DOM of said currently loaded Web page by placing a resource selection user interface object next to each one of said socially bookmarkable resources identified by elements found in said searching of said DOM; program code for displaying said resource selection user interface display objects within said currently loaded Web page, wherein each of said resource selection user interface display objects visually indicates a corresponding one of said socially bookmarkable resources identified by elements found in said searching of said DOM; program code for detecting a user clicking on one of said resource selection user interface display objects; and program code for performing said requested social bookmarking operation by bookmarking, in an external social bookmarking system, the corresponding one of the socially bookmarkable resources indicated by the resource selection user interface object clicked on by the user. | 12. A system comprising: at least one processor; at least one computer readable memory, said computer readable memory having program code stored thereon, said program code comprising: program code for receiving a request for a social bookmarking operation; program code for, responsive to said request for said social bookmarking operation, searching a document object model (DOM) of a currently loaded Web page for elements identifying corresponding socially bookmarkable resources displayed within said currently loaded Web page by checking elements in said DOM for elements having a class name matching a predetermined class name, wherein each of said socially bookmarkable resources identified by an element found in said searching is available for performing said requested social bookmarking operation, and modifying said DOM of said currently loaded Web page by placing a resource selection user interface object next to each one of said socially bookmarkable resources identified by elements found in said searching of said DOM; program code for displaying said resource selection user interface display objects within said currently loaded Web page, wherein each of said resource selection user interface display objects visually indicates a corresponding one of said socially bookmarkable resources identified by elements found in said searching of said DOM; program code for detecting a user clicking on one of said resource selection user interface display objects; and program code for performing said requested social bookmarking operation by bookmarking, in an external social bookmarking system, the corresponding one of the socially bookmarkable resources indicated by the resource selection user interface object clicked on by the user. 17. The system of claim 12 , wherein said program code for performing said requested social bookmarking operation comprises program code for passing resource information contained in said element in said document object model (DOM) of said currently loaded Web page that identifies said corresponding one of said socially bookmarkable resources visually indicated by said selected one of said resource selection user interface display objects clicked on by the user to an external social bookmarking system. | 0.574664 |
8,380,731 | 13 | 19 | 13. A computer comprising at least a processing device and a memory operable to store executable instructions to be executed by said processing device, said computer programmed to: receive, via a computer interface, a search concept query that includes a plurality of principal words; extract the principal words from the search concept query using a natural language processing utility; amplify at least one of the principal words to a set of semantically similar words; receive, via the computer interface, user input for improving the set of semantically similar words and a degree of membership for individual word within the set of semantically similar words to generate improvement in search results, wherein the user input includes an addition of one or more words to the set of semantically similar words; calculate a degree of membership for each word that reflects a similarity in meaning to the principal word of the set with which each word is associated; perform a document search utilizing each of the set of semantically similar words; compute a score for each search result document at least in part by: determining the degree of membership corresponding to each of the semantically similar words included in the search result document and the at least one of the principal words to create a set of membership weights; and determining which membership weight among the determined set of membership weights is a minimum membership weight; selecting the minimum membership weight among the determined set of membership weights to be the score for the search result; use the computed scores to rank the search result documents; and display the search result documents. | 13. A computer comprising at least a processing device and a memory operable to store executable instructions to be executed by said processing device, said computer programmed to: receive, via a computer interface, a search concept query that includes a plurality of principal words; extract the principal words from the search concept query using a natural language processing utility; amplify at least one of the principal words to a set of semantically similar words; receive, via the computer interface, user input for improving the set of semantically similar words and a degree of membership for individual word within the set of semantically similar words to generate improvement in search results, wherein the user input includes an addition of one or more words to the set of semantically similar words; calculate a degree of membership for each word that reflects a similarity in meaning to the principal word of the set with which each word is associated; perform a document search utilizing each of the set of semantically similar words; compute a score for each search result document at least in part by: determining the degree of membership corresponding to each of the semantically similar words included in the search result document and the at least one of the principal words to create a set of membership weights; and determining which membership weight among the determined set of membership weights is a minimum membership weight; selecting the minimum membership weight among the determined set of membership weights to be the score for the search result; use the computed scores to rank the search result documents; and display the search result documents. 19. The computer according to claim 13 , wherein to calculate a degree of membership, said computer is programmed to adjust the degree of membership for each semantically similar word through execution of a learning utility. | 0.665672 |
7,536,547 | 15 | 16 | 15. A system including at least two image processing devices, and adapted for secure transmission of digital data relating to a document between the at least two image processing devices, the system comprising: a sending station including: a user interface for inputting a session-specific user-defined character string by an operator, a key former for automatically forming an encryption key based on the user- defined character string, an encryption module for encrypting a document file to produce an encrypted document file, using the encryption key, while automatically leaving one or more predetermined specifying header items in the document file as unencrypted, a file former for forming a transmission file including the encrypted document file, and a transmitter for transmitting the transmission file towards a receiving station; and a receiving station including: a receiver for receiving the transmission file from the sending station, a storage unit for storing the received transmission file, a user interface for inputting a user-defined character string by an operator, a second key former for automatically forming a decryption key based on the input user-defined character string, and a decryption module for decrypting the encrypted document file to a decrypted document file, using the decryption key, wherein the sending station further includes: a module for forming an additional file containing metadata relevant for the document file but not including any decryption clue, the additional file having a first part and a second part, and wherein the encryption module also encrypts only one of the first and second parts of the additional file using the same encryption key used for encrypting the document file, and the additional file is included in the transmission file. | 15. A system including at least two image processing devices, and adapted for secure transmission of digital data relating to a document between the at least two image processing devices, the system comprising: a sending station including: a user interface for inputting a session-specific user-defined character string by an operator, a key former for automatically forming an encryption key based on the user- defined character string, an encryption module for encrypting a document file to produce an encrypted document file, using the encryption key, while automatically leaving one or more predetermined specifying header items in the document file as unencrypted, a file former for forming a transmission file including the encrypted document file, and a transmitter for transmitting the transmission file towards a receiving station; and a receiving station including: a receiver for receiving the transmission file from the sending station, a storage unit for storing the received transmission file, a user interface for inputting a user-defined character string by an operator, a second key former for automatically forming a decryption key based on the input user-defined character string, and a decryption module for decrypting the encrypted document file to a decrypted document file, using the decryption key, wherein the sending station further includes: a module for forming an additional file containing metadata relevant for the document file but not including any decryption clue, the additional file having a first part and a second part, and wherein the encryption module also encrypts only one of the first and second parts of the additional file using the same encryption key used for encrypting the document file, and the additional file is included in the transmission file. 16. The system of claim 15 , wherein the receiving station excludes means for checking validity of the user-defined character string inputted at the user interface of the receiving station. | 0.809091 |
8,972,391 | 1 | 2 | 1. A non-transitory computer readable storage medium having a computer program stored thereon, the program comprising instructions that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: analyzing a recent search activity period of a user to determine a short-term category of interest of the user, wherein the analyzing comprises comparing queries submitted by the user during the recent search activity period with categories of selected search results that were selected by the user during the recent search activity period; obtaining a plurality of search results responsive to a query, each of the plurality of search results having a respective score; for each particular search result of a first plurality of the search results: calculating a category selection value for the particular search result, wherein the category selection value for the particular search result is based on a measure of a count of selections of the particular search result as a portion of combined selection counts for search results responsive to the query for a plurality of users for the short-term category of interest; calculating a general selection value for the particular search result, wherein the general selection value for the particular search result is based on a measure of a count of selections of the particular search result as a portion of combined selection counts for search results responsive to the query for a plurality of users for any category of interest; calculating a category relevance for the particular search result, wherein the respective category relevance for the particular search result is based on a difference between the respective category selection value for the search result and the respective general selection value for the particular search result; selecting one or more search results of the plurality of search results, each selected search result being selected based on the selected search result having a category relevance that exceeds a threshold; adjusting the respective score for each of the selected search results based on, at least, the category selection value for each selected search result and the general selection value for each selected search result; and ranking the search results of the plurality of search results according to the respective adjusted scores for the selected search results and the respective scores for search results that were not selected. | 1. A non-transitory computer readable storage medium having a computer program stored thereon, the program comprising instructions that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: analyzing a recent search activity period of a user to determine a short-term category of interest of the user, wherein the analyzing comprises comparing queries submitted by the user during the recent search activity period with categories of selected search results that were selected by the user during the recent search activity period; obtaining a plurality of search results responsive to a query, each of the plurality of search results having a respective score; for each particular search result of a first plurality of the search results: calculating a category selection value for the particular search result, wherein the category selection value for the particular search result is based on a measure of a count of selections of the particular search result as a portion of combined selection counts for search results responsive to the query for a plurality of users for the short-term category of interest; calculating a general selection value for the particular search result, wherein the general selection value for the particular search result is based on a measure of a count of selections of the particular search result as a portion of combined selection counts for search results responsive to the query for a plurality of users for any category of interest; calculating a category relevance for the particular search result, wherein the respective category relevance for the particular search result is based on a difference between the respective category selection value for the search result and the respective general selection value for the particular search result; selecting one or more search results of the plurality of search results, each selected search result being selected based on the selected search result having a category relevance that exceeds a threshold; adjusting the respective score for each of the selected search results based on, at least, the category selection value for each selected search result and the general selection value for each selected search result; and ranking the search results of the plurality of search results according to the respective adjusted scores for the selected search results and the respective scores for search results that were not selected. 2. The non-transitory computer-readable storage medium of claim 1 , wherein analyzing the recent search activity period of the user comprises determining an amount of time elapsed between selection of a first search result in the recent search activity period and selection of a second search result in the recent search activity period. | 0.804297 |
9,679,256 | 13 | 14 | 13. The computer-implemented method of claim 1 , wherein said iterative process further comprises calculating a loss factor that depends on the number of difference training vectors said determining determines are misclassified during a current iteration of said iterative process. | 13. The computer-implemented method of claim 1 , wherein said iterative process further comprises calculating a loss factor that depends on the number of difference training vectors said determining determines are misclassified during a current iteration of said iterative process. 14. The computer-implemented method of claim 13 , wherein said iterative process further comprises calculating a new current timing factor in dependence upon said calculated loss factor. | 0.5 |
8,943,131 | 1 | 7 | 1. A method in a computer system for managing collaborations, the method comprising: receiving, by the computer system, a request for collaboration on a topic; identifying, by the computer system for a collaboration, a plurality of experts that have expertise in the topic, wherein at least two of the plurality of experts have a different one of a plurality of different threshold levels of a likelihood of participation in the collaboration, wherein the likelihood of participation in the collaboration is the percentage based estimation that the expert will participate in the collaboration based on a relative location of the expert to a collaboration site and whether the expert belongs to an organization hosting the collaboration, and wherein the plurality of experts are identified using a number of collections of information; setting the plurality of different threshold levels according to a level of expertise of the plurality of experts; and identifying, by the computer system, particular experts of the plurality of experts that have a respective particular likelihood of participation that exceeds one of the plurality of different threshold levels. | 1. A method in a computer system for managing collaborations, the method comprising: receiving, by the computer system, a request for collaboration on a topic; identifying, by the computer system for a collaboration, a plurality of experts that have expertise in the topic, wherein at least two of the plurality of experts have a different one of a plurality of different threshold levels of a likelihood of participation in the collaboration, wherein the likelihood of participation in the collaboration is the percentage based estimation that the expert will participate in the collaboration based on a relative location of the expert to a collaboration site and whether the expert belongs to an organization hosting the collaboration, and wherein the plurality of experts are identified using a number of collections of information; setting the plurality of different threshold levels according to a level of expertise of the plurality of experts; and identifying, by the computer system, particular experts of the plurality of experts that have a respective particular likelihood of participation that exceeds one of the plurality of different threshold levels. 7. The method according to claim 1 , wherein first ones of the plurality of experts that have a first level of expertise have a first one of the plurality of different threshold levels and second ones of the plurality of experts that have a second level of expertise have a second one of the plurality of different threshold levels, and wherein the first one of the plurality of different threshold levels is higher than the second one of the plurality of different threshold levels, and further wherein the first ones of the plurality of experts have a greater level of expertise in the topic than the second ones of the plurality of experts. | 0.5 |
8,020,091 | 8 | 13 | 8. In a computer system, a method for formatting a plurality of mathematical expressions that occupy one or more lines in a document, comprising: aligning the plurality of mathematical expressions, comprising: initializing and utilizing an expression editing tool to format the plurality of mathematical expressions, the expression editing tool: identifying an anchor point for a first mathematical expression; identifying an alignment point for each line of each mathematical expression; determining a horizontal indent for a first line of a second mathematical expression such that the alignment point of the second mathematical expression and the anchor point of the first mathematical expression have the same horizontal position; inserting the horizontal indent into the first line with the expression editing tool; wherein, during alignment, each line has limitless horizontal space; after the alignment, determining if a portion of the second mathematical expression on the first line crosses a second margin of the document; if the portion of the second mathematical expression crosses the second margin on the first line, forcing an automatic break for the portion of the second mathematical expression crossing the second margin and calculating a total indention to maintain a meaning of the second mathematical expression: determining the amount of an automatic break indention for the portion of the second mathematical expression crossing the second margin, wherein the automatic break indention is the distance on a next line to align a first element of the portion of the second mathematical expression crossing the second margin with a first element on the first line after the alignment point of the second mathematical expression, determining the amount of the alignment indention, and adding with the expression editing tool the amount of the automatic break indention and the alignment indention to calculate the total indention; moving with the expression editing tool the portion of the second mathematical expression that crosses the second margin to the next line of the document; and applying with the expression editing tool the total indention to the moved portion. | 8. In a computer system, a method for formatting a plurality of mathematical expressions that occupy one or more lines in a document, comprising: aligning the plurality of mathematical expressions, comprising: initializing and utilizing an expression editing tool to format the plurality of mathematical expressions, the expression editing tool: identifying an anchor point for a first mathematical expression; identifying an alignment point for each line of each mathematical expression; determining a horizontal indent for a first line of a second mathematical expression such that the alignment point of the second mathematical expression and the anchor point of the first mathematical expression have the same horizontal position; inserting the horizontal indent into the first line with the expression editing tool; wherein, during alignment, each line has limitless horizontal space; after the alignment, determining if a portion of the second mathematical expression on the first line crosses a second margin of the document; if the portion of the second mathematical expression crosses the second margin on the first line, forcing an automatic break for the portion of the second mathematical expression crossing the second margin and calculating a total indention to maintain a meaning of the second mathematical expression: determining the amount of an automatic break indention for the portion of the second mathematical expression crossing the second margin, wherein the automatic break indention is the distance on a next line to align a first element of the portion of the second mathematical expression crossing the second margin with a first element on the first line after the alignment point of the second mathematical expression, determining the amount of the alignment indention, and adding with the expression editing tool the amount of the automatic break indention and the alignment indention to calculate the total indention; moving with the expression editing tool the portion of the second mathematical expression that crosses the second margin to the next line of the document; and applying with the expression editing tool the total indention to the moved portion. 13. A method as defined in claim 8 , wherein a user interface allows a user to select the anchor point for the first mathematical expression. | 0.759386 |
8,024,337 | 1 | 18 | 1. A method of determining query similarity, comprising: logging instances of a first query; logging instances of a second query; deriving a first query distribution using the logged instances of the first query; deriving a second query distribution using the logged instances of the second query; comparing the first and second query distributions, where comparing the first and second query distributions comprises: determining a distance measure between the first query distribution and the second query distribution; comparing the distance measure to a specified threshold; and designating the second query as similar to the first query if the distance measure is below the specified threshold; and determining whether the second query is similar to the first query based on the comparison. | 1. A method of determining query similarity, comprising: logging instances of a first query; logging instances of a second query; deriving a first query distribution using the logged instances of the first query; deriving a second query distribution using the logged instances of the second query; comparing the first and second query distributions, where comparing the first and second query distributions comprises: determining a distance measure between the first query distribution and the second query distribution; comparing the distance measure to a specified threshold; and designating the second query as similar to the first query if the distance measure is below the specified threshold; and determining whether the second query is similar to the first query based on the comparison. 18. The method of claim 1 , wherein the logged instances of the first query are logged over a first time interval and the logged instances of the second query are logged over a second time interval. | 0.652632 |
8,615,664 | 1 | 8 | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 8. The system of claim 1 , wherein the one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message comprise: a magnetoencephalography (MEG) device. | 0.869097 |
9,679,027 | 1 | 2 | 1. A method performed by one or more computers, the method comprising: generating a question graph that includes a respective node for each of a plurality of questions; connecting, with links in the question graph, nodes for questions that are equivalent, comprising: identifying selected resources for each of the plurality of questions based on user selections of search results in response to previous submissions of the question as a search query to a search engine; identifying pairs of questions from the plurality of questions, wherein the questions in each identified pair of questions have at least a first threshold number of common identified selected resources; and for each identified pair, connecting the nodes for the questions in the identified pair with a link in the question graph; receiving a new search query from a user device; obtaining an initial ranking of questions that are related to the new search query; generating a modified ranking of questions that are related to the new search query, comprising, for each question in the initial ranking: determining whether the question is equivalent to any higher-ranked questions in the initial ranking by determining whether a node for the question is connected by a link to any of the nodes for any of the higher-ranked questions in the question graph; and when the question is equivalent to any of the higher-ranked questions, removing the question from the modified ranking; selecting one or more questions from the modified ranking; and transmitting data identifying the selected questions to the user device as part of a response to the new search query. | 1. A method performed by one or more computers, the method comprising: generating a question graph that includes a respective node for each of a plurality of questions; connecting, with links in the question graph, nodes for questions that are equivalent, comprising: identifying selected resources for each of the plurality of questions based on user selections of search results in response to previous submissions of the question as a search query to a search engine; identifying pairs of questions from the plurality of questions, wherein the questions in each identified pair of questions have at least a first threshold number of common identified selected resources; and for each identified pair, connecting the nodes for the questions in the identified pair with a link in the question graph; receiving a new search query from a user device; obtaining an initial ranking of questions that are related to the new search query; generating a modified ranking of questions that are related to the new search query, comprising, for each question in the initial ranking: determining whether the question is equivalent to any higher-ranked questions in the initial ranking by determining whether a node for the question is connected by a link to any of the nodes for any of the higher-ranked questions in the question graph; and when the question is equivalent to any of the higher-ranked questions, removing the question from the modified ranking; selecting one or more questions from the modified ranking; and transmitting data identifying the selected questions to the user device as part of a response to the new search query. 2. The method of claim 1 , wherein two questions are equivalent if the two questions have an equivalent meaning. | 0.912226 |
7,849,416 | 1 | 29 | 1. A computer-implemented method for creating a prototype that includes motion control, machine vision, and Data Acquisition (DAQ) functionality, the method comprising: displaying a graphical user interface (GUI) that provides GUI access to a set of operations, wherein the set of operations includes one or more motion control operations, one or more machine vision operations, and one or more DAQ operations; creating a sequence of operations, wherein creating the sequence comprises including a plurality of operations in the sequence in response to user input selecting each operation in the plurality of operations from the GUI, wherein including the plurality of operations in the sequence in response to the user input selecting each operation in the plurality of operations from the GUI comprises including the plurality of operations in the sequence without receiving user input specifying program code for performing the plurality of operations; wherein the plurality of operations included in the sequence includes at least one motion control operation, at least one machine vision operation, and at least one DAQ operation, wherein at least one of the DAQ operations included in the sequence is operable to control a DAQ measurement device to acquire measurement data of a device under test; wherein the method further comprises storing information representing the sequence of operations in a data structure, wherein the sequence of operations comprises the prototype. | 1. A computer-implemented method for creating a prototype that includes motion control, machine vision, and Data Acquisition (DAQ) functionality, the method comprising: displaying a graphical user interface (GUI) that provides GUI access to a set of operations, wherein the set of operations includes one or more motion control operations, one or more machine vision operations, and one or more DAQ operations; creating a sequence of operations, wherein creating the sequence comprises including a plurality of operations in the sequence in response to user input selecting each operation in the plurality of operations from the GUI, wherein including the plurality of operations in the sequence in response to the user input selecting each operation in the plurality of operations from the GUI comprises including the plurality of operations in the sequence without receiving user input specifying program code for performing the plurality of operations; wherein the plurality of operations included in the sequence includes at least one motion control operation, at least one machine vision operation, and at least one DAQ operation, wherein at least one of the DAQ operations included in the sequence is operable to control a DAQ measurement device to acquire measurement data of a device under test; wherein the method further comprises storing information representing the sequence of operations in a data structure, wherein the sequence of operations comprises the prototype. 29. The method of claim 1 , wherein the plurality of operations included in the sequence includes a plurality of motion control operations; wherein the method further comprises interactively displaying a graph illustrating a spatial trajectory cumulatively performed by the plurality of motion control operations, wherein interactively displaying the graph comprises: for each motion control operation in the plurality of motion control operations included in the sequence, updating the graph in response to including the motion control operation in the sequence in order to visually indicate a change in the spatial trajectory, wherein the change in the spatial trajectory is caused by including the motion control operation in the sequence, wherein updating the graph provides interactive visual feedback to the user indicating the change caused by including the motion control operation in the sequence. | 0.5 |
8,396,586 | 3 | 4 | 3. The method of claim 2 , wherein the at least one criterion comprises a document being a no call bill. | 3. The method of claim 2 , wherein the at least one criterion comprises a document being a no call bill. 4. The method of claim 3 , wherein the at least one criterion comprises a document being a suspect bill. | 0.5 |
9,430,772 | 6 | 8 | 6. A network device to manage a display of an advertisement at a mobile device, comprising: a transceiver to send and receive data over the network; and a processor; a processor-readable storage medium comprising programming logic that comprises logic for: receiving a text message from a user of the mobile device to another user of another computing device the user and the other user having a defined social connection; examining the received text message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing a copy of the detected question comprised in the received text message; monitoring for a response text message from the other user for a timeout time period; refining the detected question from the user by combining at least a portion of the response text message to the detected question received from the other user with at least a portion of the detected question from the user, if the response text message is received within the timeout time period, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing the refined detected question to select a contextual advertisement; modifying the response text message to include link information to the contextual advertisement; and providing the modified response text message to the user of the mobile device. | 6. A network device to manage a display of an advertisement at a mobile device, comprising: a transceiver to send and receive data over the network; and a processor; a processor-readable storage medium comprising programming logic that comprises logic for: receiving a text message from a user of the mobile device to another user of another computing device the user and the other user having a defined social connection; examining the received text message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing a copy of the detected question comprised in the received text message; monitoring for a response text message from the other user for a timeout time period; refining the detected question from the user by combining at least a portion of the response text message to the detected question received from the other user with at least a portion of the detected question from the user, if the response text message is received within the timeout time period, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing the refined detected question to select a contextual advertisement; modifying the response text message to include link information to the contextual advertisement; and providing the modified response text message to the user of the mobile device. 8. The network device of claim 6 , wherein programming logic for refining the detected question further comprises logic for: selecting at least one keyword from the response text message; selecting at least one keyword from the detected question; and combining the at least one selected keyword from the response with the at least one selected keyword from detected question to refine the detected question. | 0.5 |
9,275,139 | 1 | 2 | 1. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; scoring the speech recognition by use of a soft time window, wherein the soft time window comprises a window definable by a spline function; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M. | 1. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; scoring the speech recognition by use of a soft time window, wherein the soft time window comprises a window definable by a spline function; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M. 2. The method of claim 1 , wherein the high score is produced by applying a transform function to at least one of N function inputs. | 0.792453 |
7,529,734 | 23 | 24 | 23. The apparatus of claim 19 , further comprising: a receiving mechanism configured to receive a query to retrieve one or more templates selected by the user; a retrieval mechanism configured to retrieve a template selected by the user; and a communication mechanism configured to communicate the retrieved template to a middle-tier server or a client, thereby allowing the template to be parsed. | 23. The apparatus of claim 19 , further comprising: a receiving mechanism configured to receive a query to retrieve one or more templates selected by the user; a retrieval mechanism configured to retrieve a template selected by the user; and a communication mechanism configured to communicate the retrieved template to a middle-tier server or a client, thereby allowing the template to be parsed. 24. The apparatus of claim 23 , wherein while representing the search-field names and search-field values in a parsable format, the template-generating mechanism is configured to represent the extracted search-field names and search-field values in an XML file and to store the XML file as a CLOB or a BLOB. | 0.5 |
8,401,853 | 13 | 14 | 13. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to generate answers to a spoken query, the instructions comprising: receiving a spoken query from a user; identifying demographic metadata from the spoken query in parallel with speech recognition of the spoken query; and passing the demographic metadata to a question-answering engine that also receives speech recognition output of the spoken query and generates at least one answer in response to the spoken query. | 13. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to generate answers to a spoken query, the instructions comprising: receiving a spoken query from a user; identifying demographic metadata from the spoken query in parallel with speech recognition of the spoken query; and passing the demographic metadata to a question-answering engine that also receives speech recognition output of the spoken query and generates at least one answer in response to the spoken query. 14. The non-transitory computer-readable storage medium of claim 13 , wherein the question-answering engine further outputs the at least one answer to the user. | 0.593909 |
9,582,781 | 9 | 10 | 9. A system for managing operations for organizations over a network, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: when a plurality of Operations events are provided, performing further actions, including: providing one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging the memory for storing the one or more trained models; storing the one or more trained models in the memory; when the one or more real-time Operations events are provided, performing further actions including: retrieving the one or more trained models from the memory; and employing the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: displaying the plurality of Operations events; obtaining user inputs for associating the one or more resolution metrics with the one or more event clusters; and communicating the user inputs to the network computer. | 9. A system for managing operations for organizations over a network, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: when a plurality of Operations events are provided, performing further actions, including: providing one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging the memory for storing the one or more trained models; storing the one or more trained models in the memory; when the one or more real-time Operations events are provided, performing further actions including: retrieving the one or more trained models from the memory; and employing the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: displaying the plurality of Operations events; obtaining user inputs for associating the one or more resolution metrics with the one or more event clusters; and communicating the user inputs to the network computer. 10. The system of claim 9 , wherein the one or more network computer processors execute instructions that perform actions, further comprising, transforming each Operations event in the plurality of Operations events into a common event format. | 0.705097 |
7,855,799 | 14 | 15 | 14. The method of claim 8 , wherein receiving an input identifying a printing option to be performed on the first subset comprises receiving an input identifying printing multiple copies of the subset of the plurality of pages. | 14. The method of claim 8 , wherein receiving an input identifying a printing option to be performed on the first subset comprises receiving an input identifying printing multiple copies of the subset of the plurality of pages. 15. The method of claim 14 , further comprising receiving an input identifying printing at least one of the multiple copies on a media different from any other of the multiple copies. | 0.5 |
7,676,589 | 1 | 2 | 1. A method of automatically creating portlets for a portal system comprising: identifying a location of structured data described by a data model specification; automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; automatically generating a plurality of portlets, wherein each portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically generating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page. | 1. A method of automatically creating portlets for a portal system comprising: identifying a location of structured data described by a data model specification; automatically determining, by a computer, from the data model specification, relationships between a plurality of objects within the structured data, wherein the data model specification is automatically introspected to identify primary keys associated with each of the plurality of objects and foreign key relationships between the plurality of objects; automatically generating a plurality of portlets, wherein each portlet is automatically generated for each object of the plurality of objects according to the relationships specified within the data model specification, wherein at least one function, for querying the structured data, of each portlet is automatically determined by a foreign key relationship of the object associated with each portlet, and wherein automatically generating a plurality of portlets further comprises generating code in at least a first portlet of the plurality of portlets that triggers the action in at least a second portlet of the plurality of portlets according to the relationships specified within the data model specification; and automatically creating at least one communication link between at least two of the plurality of portlets according to the relationships specified within the data model specification, wherein over the communication link the first portlet of the at least two portlets triggers an action within the second portlet of the at least two portlets, and responsive to that action, the second portlet sends data to the first portlet, wherein at least one of the first portlet or the second portlet is displayed within a portal page. 2. The method of claim 1 , wherein automatically determining relationships from the data model specification further comprises identifying selected relationships from a plurality of relationships specified within the data model specification according to a user-specified attribute. | 0.683146 |
6,067,348 | 1 | 3 | 1. An apparatus for creating a personalized message, comprising: a storage area containing a plurality of personal greeting root name segments, with each personal greeting root name segment of said plurality of personal greeting root name segments being associated with a corresponding index number; a call list containing recipient names of at least one recipient who is to receive said message; a match table containing at least one recipient name and a corresponding index number that maps said recipient name to a personal greeting root name segment, wherein said index number corresponds to at least one recipient name; a communication link for transmitting said personalized message; and a message controller for processing said call list and forming said personalized message, and for transmitting said personalized message over said communication link, including means for retrieving an index number from said match table corresponding to a recipient name in said call list, retrieving the personal greeting root name segment associated with said index number from said storage area, and combining said personal greeting root name segment with a stored message body. | 1. An apparatus for creating a personalized message, comprising: a storage area containing a plurality of personal greeting root name segments, with each personal greeting root name segment of said plurality of personal greeting root name segments being associated with a corresponding index number; a call list containing recipient names of at least one recipient who is to receive said message; a match table containing at least one recipient name and a corresponding index number that maps said recipient name to a personal greeting root name segment, wherein said index number corresponds to at least one recipient name; a communication link for transmitting said personalized message; and a message controller for processing said call list and forming said personalized message, and for transmitting said personalized message over said communication link, including means for retrieving an index number from said match table corresponding to a recipient name in said call list, retrieving the personal greeting root name segment associated with said index number from said storage area, and combining said personal greeting root name segment with a stored message body. 3. The apparatus of claim 1, wherein said plurality of personal greeting root name segments include a last name that can be matched to an intended recipient. | 0.615196 |
8,443,295 | 8 | 10 | 8. A method as claimed in claim 1 wherein said state/event model is provided using Unified Modeling Language (UML). | 8. A method as claimed in claim 1 wherein said state/event model is provided using Unified Modeling Language (UML). 10. A method as claimed in claim 8 wherein said UML is extended to provide for a single graphical element to link two or more states which are of different objects. | 0.616822 |
8,856,132 | 17 | 23 | 17. A system for managing and distributing knowledge tips in an organization, the organization comprising one or more members, the system comprising: a. a tips repository configured for storing: i. a knowledge tip received from a first member of the organization for distribution by the system to one or more members of the organization, wherein the knowledge tip is associated with at least one predefined category; and ii. one or more data points corresponding to the knowledge tip, wherein the one or more data points comprise descriptive information corresponding to the knowledge tip; b. a processor implemented interface configured for allowing members of the organization to interact with the tips repository; c. a processor implemented search engine configured for: i. receiving from a second member of the organization, a criterion for selecting a subset of knowledge tips from among the knowledge tips stored in the tips repository, the criterion received from the second member enabling selection of the subset of knowledge tips such that at least one of the knowledge tips within the selected subset has been transmitted to the tips management system by the first member, wherein the subset of knowledge tips is selected for delivery to an intended set of recipients within the organization, and wherein the intended set of recipients are identified by the second member such that said intended set of recipients includes at least one member of the organization other than the first member and the second member; ii. based on the received criterion selectins the subset of knowledge ties from among the knowledge tips stored in the tips repository; and iii. receiving from the second member, delivery parameters, wherein the delivery parameters control transmission of the subset of knowledge tips from the tips repository to the intended set of recipients; d. a processor implemented scheduling module configured for scheduling delivery of the selected at least one knowledge tip to the intended set of recipients using the interface, wherein transmission of the subset of knowledge tips is controlled by delivery parameters received from the second member; and e. a processor implemented delivery module configured for delivering the selected subset of knowledge tips from the tips repository to the intended set of recipients based on the delivery parameters. | 17. A system for managing and distributing knowledge tips in an organization, the organization comprising one or more members, the system comprising: a. a tips repository configured for storing: i. a knowledge tip received from a first member of the organization for distribution by the system to one or more members of the organization, wherein the knowledge tip is associated with at least one predefined category; and ii. one or more data points corresponding to the knowledge tip, wherein the one or more data points comprise descriptive information corresponding to the knowledge tip; b. a processor implemented interface configured for allowing members of the organization to interact with the tips repository; c. a processor implemented search engine configured for: i. receiving from a second member of the organization, a criterion for selecting a subset of knowledge tips from among the knowledge tips stored in the tips repository, the criterion received from the second member enabling selection of the subset of knowledge tips such that at least one of the knowledge tips within the selected subset has been transmitted to the tips management system by the first member, wherein the subset of knowledge tips is selected for delivery to an intended set of recipients within the organization, and wherein the intended set of recipients are identified by the second member such that said intended set of recipients includes at least one member of the organization other than the first member and the second member; ii. based on the received criterion selectins the subset of knowledge ties from among the knowledge tips stored in the tips repository; and iii. receiving from the second member, delivery parameters, wherein the delivery parameters control transmission of the subset of knowledge tips from the tips repository to the intended set of recipients; d. a processor implemented scheduling module configured for scheduling delivery of the selected at least one knowledge tip to the intended set of recipients using the interface, wherein transmission of the subset of knowledge tips is controlled by delivery parameters received from the second member; and e. a processor implemented delivery module configured for delivering the selected subset of knowledge tips from the tips repository to the intended set of recipients based on the delivery parameters. 23. The system of claim 17 wherein the interface is further configured for defining at least one delivery parameter for delivering of the selected subset of knowledge tips, wherein the at least one delivery parameter comprises one or more of pattern of recurrence for sending, range of date for recurrent sending and identity, contact information and media preference of the corresponding member of the organization. | 0.5 |
7,844,464 | 1 | 6 | 1. A method performed by a computer processor executing computer program instructions tangibly stored on a first computer-readable medium to perform a method comprising steps of: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, using the processor, from the stored representation of the likelihood and the stored representation of the measure of relevance, an emphasis factor that modifies emphasis placed on the region of the spoken audio stream when played back, wherein (C) comprises: (C)(1) identifying a rule that identifies the emphasis factor based on the identified likelihood and the identified measure of relevance; and (C)(2) applying the rule to the identified likelihood and the identified measure of relevance to derive the emphasis factor; where (C)(2) comprises: (C)(2)(a) identifying a first weight associated with the identified likelihood; (C)(2)(b) identifying a second weight associated with the measure of relevance; and (C)(2)(c) deriving the emphasis factor from a combination of the identified likelihood and the measure of relevance weighted by the first and second weights, respectively. | 1. A method performed by a computer processor executing computer program instructions tangibly stored on a first computer-readable medium to perform a method comprising steps of: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, using the processor, from the stored representation of the likelihood and the stored representation of the measure of relevance, an emphasis factor that modifies emphasis placed on the region of the spoken audio stream when played back, wherein (C) comprises: (C)(1) identifying a rule that identifies the emphasis factor based on the identified likelihood and the identified measure of relevance; and (C)(2) applying the rule to the identified likelihood and the identified measure of relevance to derive the emphasis factor; where (C)(2) comprises: (C)(2)(a) identifying a first weight associated with the identified likelihood; (C)(2)(b) identifying a second weight associated with the measure of relevance; and (C)(2)(c) deriving the emphasis factor from a combination of the identified likelihood and the measure of relevance weighted by the first and second weights, respectively. 6. The method of claim 1 , further comprising a step of: (D) modifying an emphasis of the region of the spoken audio stream in accordance with the emphasis factor to produce an emphasis-adjusted audio stream. | 0.810909 |
9,779,428 | 1 | 2 | 1. A method for determining the sentiment of a plurality of words as negative or positive, comprising: receiving, by one or more computer processors, a plurality of words from a user interface of a client machine; for each word in the plurality of words, testing whether the word indicates positive or negative sentiment by using a sentiment mining tool; responsive to detecting an indication of positive sentiment of the word, testing whether there is, in the plurality of words, a known negative word that was mined from the text of feedback from one or more ecommerce transaction logs; responsive to detecting that there is, in the plurality of words, no known negative word that was mined from the text of feedback from one or more ecommerce transaction logs, incrementing a positive word counter in one or more hardware processors; responsive to detecting an indication of negative sentiment of the word, testing whether the word is in a list of negative modifiers; and responsive to detecting that the word is not in the list of negative modifiers, incrementing a negative word counter in the one or more hardware processors. | 1. A method for determining the sentiment of a plurality of words as negative or positive, comprising: receiving, by one or more computer processors, a plurality of words from a user interface of a client machine; for each word in the plurality of words, testing whether the word indicates positive or negative sentiment by using a sentiment mining tool; responsive to detecting an indication of positive sentiment of the word, testing whether there is, in the plurality of words, a known negative word that was mined from the text of feedback from one or more ecommerce transaction logs; responsive to detecting that there is, in the plurality of words, no known negative word that was mined from the text of feedback from one or more ecommerce transaction logs, incrementing a positive word counter in one or more hardware processors; responsive to detecting an indication of negative sentiment of the word, testing whether the word is in a list of negative modifiers; and responsive to detecting that the word is not in the list of negative modifiers, incrementing a negative word counter in the one or more hardware processors. 2. The method of claim 1 , the method further comprising: responsive to detecting that all words in the plurality of words have been tested, determining a numerical quantity from a count of the positive word counter and a count of the negative word counter; and testing the numerical quantity and, responsive to detecting the numerical quantity as being equal to or greater than a threshold, marking the plurality of words as positive sentiment, and, responsive to detecting the numerical quantity as being less than the threshold, marking the plurality of words as negative. | 0.5 |
9,967,159 | 13 | 14 | 13. The method of claim 12 , further comprising reporting, by the cloud brokerage computing device, cost consumption data through a graphical user interface on a display device. | 13. The method of claim 12 , further comprising reporting, by the cloud brokerage computing device, cost consumption data through a graphical user interface on a display device. 14. The method of claim 13 , further comprising displaying, by the cloud brokerage computing device, an alert notification through the graphical user interface when a predetermined quota allocation threshold is exceeded, wherein the predetermined quota allocation threshold is determined from the enterprise context data. | 0.5 |
8,032,518 | 15 | 16 | 15. The computer system of claim 13 , the web crawl control instructions further comprising, instructions for: comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is a limiting factor in crawling the respective website. | 15. The computer system of claim 13 , the web crawl control instructions further comprising, instructions for: comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and performing a website crawling management function in accordance with the determination of whether the current crawl rate limit is a limiting factor in crawling the respective website. 16. The computer system of claim 15 , the web crawl control instructions further comprising: instructions for informing the respective owner that a request for a faster crawl rate may not change a current crawl rate for crawling the respective website when the current crawl rate limit is not a limiting factor in crawling the respective website. | 0.5 |
9,271,130 | 23 | 24 | 23. The method of claim 14 , wherein at least one of the first profile and the second profile is accessible by the first user using any one of a plurality of devices. | 23. The method of claim 14 , wherein at least one of the first profile and the second profile is accessible by the first user using any one of a plurality of devices. 24. The method of claim 23 , further comprising registering at least one of the plurality of devices for use with the account. | 0.5 |
9,966,065 | 56 | 58 | 56. The method of claim 26 , wherein determining the first intent associated with the first candidate substring and the second intent associated with the second candidate substring comprises: determining the first intent or the second intent based on information displayed on a display associated with the electronic device. | 56. The method of claim 26 , wherein determining the first intent associated with the first candidate substring and the second intent associated with the second candidate substring comprises: determining the first intent or the second intent based on information displayed on a display associated with the electronic device. 58. The method of claim 56 , wherein the information comprises one or more notifications. | 0.904711 |
8,713,041 | 6 | 10 | 6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. | 6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. 10. The non-transitory computer readable storage medium of claim 6 , wherein the first device and the second device are connected to a peer to peer network. | 0.749196 |
7,613,722 | 10 | 13 | 10. The method of claim 8 , further comprising, selecting a device to which the notification is to be sent, and further comprising, further modifying information in the notification based on properties of the device. | 10. The method of claim 8 , further comprising, selecting a device to which the notification is to be sent, and further comprising, further modifying information in the notification based on properties of the device. 13. The method of claim 10 wherein the notification includes content comprising multiple components, and wherein the information modified in the notification is based on the content components with respect to the content that the device can handle. | 0.695332 |
8,060,492 | 1 | 10 | 1. A method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, at least one topical axis and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. | 1. A method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, at least one topical axis and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. 10. The method of claim 1 wherein if the requesting user is not authorized to view at least one object in the at least one cluster of related data objects, the clustering threshold is reevaluated for the at least one cluster of related data objects. | 0.7969 |
8,543,606 | 5 | 14 | 5. The system of claim 1 , wherein the computer readable instructions further cause the processor to provide an attribute comprising a first field containing a name of the attribute and a second field containing a value of the attribute. | 5. The system of claim 1 , wherein the computer readable instructions further cause the processor to provide an attribute comprising a first field containing a name of the attribute and a second field containing a value of the attribute. 14. The system of claim 5 , wherein the computer readable instructions further cause the processor to provide the name of the attribute, which is a word count for a file or a name of an author of the file. | 0.684615 |
10,152,532 | 9 | 11 | 9. The method defined by claim 8 , wherein the method further comprises selecting a first meaningful expression based on a similarity between a first combination and a second combination, the first combination including a second meaningful term and a third meaningful term, the second combination including the expansion of the second abbreviated term and the expansion of the third abbreviated term, the first meaningful expression including the second meaningful term and the third meaningful term. | 9. The method defined by claim 8 , wherein the method further comprises selecting a first meaningful expression based on a similarity between a first combination and a second combination, the first combination including a second meaningful term and a third meaningful term, the second combination including the expansion of the second abbreviated term and the expansion of the third abbreviated term, the first meaningful expression including the second meaningful term and the third meaningful term. 11. The method defined by claim 9 , wherein the method further comprises: selecting a second meaningful expression including the first meaningful term and a fourth meaningful term, the fourth meaningful term being selected based on a similarity between the fourth meaningful term and an expansion of a fourth abbreviated term associated with the first abbreviated name, the second meaningful expression being selected based on a first collocation and a second collocation, the first collocation being associated with the first meaningful term and the fourth meaningful term, the second collocation being associated with the expansion of the first abbreviated term and the expansion of the fourth abbreviated term; and associating the first abbreviated term and the fourth abbreviated term with the second meaningful expression. | 0.5 |
7,886,264 | 14 | 48 | 14. A program storage medium encoded with instructions that, when executed by a computing device, perform a method for use in a computing programming environment, the method comprising: receiving a plurality of user inputs, each user input specifying an action in a workflow; automatically identifying a data type incompatibility between an output of a first one of the specified actions and an input of a second one of the specified actions; and automatically generating a background script, to run in the background, wherein the background script is adapted to execute the actions in the workflow responsive to the user inputs, the background script adapted to automatically convert data of at least one of the incompatible data types to a compatible data type, wherein automatically converting the data comprises converting data based at least upon a relevance hierarchy of compatible data types. | 14. A program storage medium encoded with instructions that, when executed by a computing device, perform a method for use in a computing programming environment, the method comprising: receiving a plurality of user inputs, each user input specifying an action in a workflow; automatically identifying a data type incompatibility between an output of a first one of the specified actions and an input of a second one of the specified actions; and automatically generating a background script, to run in the background, wherein the background script is adapted to execute the actions in the workflow responsive to the user inputs, the background script adapted to automatically convert data of at least one of the incompatible data types to a compatible data type, wherein automatically converting the data comprises converting data based at least upon a relevance hierarchy of compatible data types. 48. The program storage medium of claim 14 , wherein the encoded method further comprises: determining a context and a data requirement for a potential user input, the potential user input including selecting a graphical element specifying an action in a workflow, from a preceding one of the user inputs; filtering candidates for the potential user input for relevance in light of the context and the data requirement; and presenting the filtered candidates to the user ordered by their relevance. | 0.56162 |
8,560,853 | 1 | 6 | 1. A computer-implemented method, comprising: storing a document as discrete parts in electronic form on a computing device, the document including a document configuration that conveys data related to content of at least one discrete part and a document sequence portion that lists the discrete parts; applying a digital signature to the document stored on the computing device based on a digital signing policy to protect the content of the at least one discrete part with the digital signature while leaving the document sequence portion that lists the discrete parts unprotected by the digital signature; invalidating the digital signature when the content in the at least one discrete part is altered; and indicating that the digital signature is valid when the document sequence portion is altered to list an additional discrete part that is added to the document. | 1. A computer-implemented method, comprising: storing a document as discrete parts in electronic form on a computing device, the document including a document configuration that conveys data related to content of at least one discrete part and a document sequence portion that lists the discrete parts; applying a digital signature to the document stored on the computing device based on a digital signing policy to protect the content of the at least one discrete part with the digital signature while leaving the document sequence portion that lists the discrete parts unprotected by the digital signature; invalidating the digital signature when the content in the at least one discrete part is altered; and indicating that the digital signature is valid when the document sequence portion is altered to list an additional discrete part that is added to the document. 6. The computer-implemented method as recited in claim 1 , further comprising indicating that the digital signature is invalid when the data in the at least one discrete part is altered. | 0.581081 |
7,565,520 | 1 | 3 | 1. A navigation system with switchable multi-language operating interfaces, comprising: a storage unit for storing installation programs and audio databases of the multi-language operating interfaces; a Basic Input/Output System (BIOS) for actuating the navigation system during a boot up thereof and controlling to display a selection interface of settings; a setup module for receiving a user selection from the selection interface; an installation module for loading and installing the corresponding installation program of the multi-language operating interface from the storage unit in accordance with the user selection; and a memory module for storing the installed multi-language operating interfaces, wherein the navigation system is configured such that once the multi-language operating interfaces are installed, there is no need to make a language selection when being warm-booted so that a language is switchable to a desired language without re-cold-booting the navigation system. | 1. A navigation system with switchable multi-language operating interfaces, comprising: a storage unit for storing installation programs and audio databases of the multi-language operating interfaces; a Basic Input/Output System (BIOS) for actuating the navigation system during a boot up thereof and controlling to display a selection interface of settings; a setup module for receiving a user selection from the selection interface; an installation module for loading and installing the corresponding installation program of the multi-language operating interface from the storage unit in accordance with the user selection; and a memory module for storing the installed multi-language operating interfaces, wherein the navigation system is configured such that once the multi-language operating interfaces are installed, there is no need to make a language selection when being warm-booted so that a language is switchable to a desired language without re-cold-booting the navigation system. 3. The navigation system with switchable multi-language operating interfaces of claim 1 , wherein the storage unit is a flash card connected to the navigation system through an expansion interface. | 0.616732 |
7,636,855 | 24 | 26 | 24. A user authentication method, comprising: prompting, by a processor of a secure access control system, a user with multiple, selectable pass-phrases which are formed by selecting one or more pass-phrases from a set of pass-phrases satisfying a rule associated with the user and selecting one or more pass-phrases from a set of pass-phrases that do not satisfy the rule, where the rule associated with the user is determined prior to authentication and is not suggested to the user during authentication; receiving at least one user selection input and recognizing user selection of at least one of the pass-phrases based on the user selection input; making, by the processor of the secure access control system, a match based on biometrics of enrolled users and a user biometric input to yield biometric match result; analyzing, by the processor of the secure access control system, at least one potential user identity based on the match between the pass-phrases in the user selection and the rule associated with the user; recursively prompting, by the processor of the secure access control system, the user with new sets of multiple, selectable pass-phrases randomly assembled from a pass-phrase corpus over multiple dialogue turns; combining, by the processor of the secure access control system, the biometric match results with the selection results from each dialogue turn to yield dialogue turn results; combining, by the processor of the secure access control system, the dialogue turn results over the multiple dialogue turns to form a cumulative result and authorizing the user when the cumulative result exceeds a threshold. | 24. A user authentication method, comprising: prompting, by a processor of a secure access control system, a user with multiple, selectable pass-phrases which are formed by selecting one or more pass-phrases from a set of pass-phrases satisfying a rule associated with the user and selecting one or more pass-phrases from a set of pass-phrases that do not satisfy the rule, where the rule associated with the user is determined prior to authentication and is not suggested to the user during authentication; receiving at least one user selection input and recognizing user selection of at least one of the pass-phrases based on the user selection input; making, by the processor of the secure access control system, a match based on biometrics of enrolled users and a user biometric input to yield biometric match result; analyzing, by the processor of the secure access control system, at least one potential user identity based on the match between the pass-phrases in the user selection and the rule associated with the user; recursively prompting, by the processor of the secure access control system, the user with new sets of multiple, selectable pass-phrases randomly assembled from a pass-phrase corpus over multiple dialogue turns; combining, by the processor of the secure access control system, the biometric match results with the selection results from each dialogue turn to yield dialogue turn results; combining, by the processor of the secure access control system, the dialogue turn results over the multiple dialogue turns to form a cumulative result and authorizing the user when the cumulative result exceeds a threshold. 26. The method of claim 24 , further comprising: determining a user identity based on cumulative results of multiple dialogue turns; recursively assembling new pass-phrases; and prompting the user until the user identity is determined. | 0.852015 |
8,122,015 | 1 | 4 | 1. A method comprising: processing, using a processor, a user query received to identify a set of documents relevant to a user query by comparing the parameters gathered from the user query with a database of documents; receiving, using the processor, the set of documents for ranking, performing, using the processor, an initial ranking on the received documents, each of the documents assigned an initial ranking from a set of rankings, creating, using the processor, a plurality of document pairs from the received documents based on a vector of features that includes a frequency of a term in each document of the set of documents and a length of each document of the set of documents, each document pair including two documents having two different ranks, each rank pair comprising two different ranks of different integer values, generating, using the processor, at least two subsets of the plurality of document pairs, each subset corresponding to a different rank pair, each rank pair comprising two ranks of different ranking values corresponding to respective different ranks; generating, using the processor, multiple hyperplanes comprising multiple base rankers for each rank pair, wherein each base ranker of the multiple base rankers is a single hyperplane including a linear ranking model trained for a particular rank pair using a ranking support vector machine that ranks the documents in each subset, wherein the generating creates a base ranker for each rank pair; and ranking, using the processor, the document pairs within each of the at least two subsets using the base ranker associated with each rank pair; and aggregating, using the processor, the multiple hyperplanes into an ensemble of base rankers comprising the base rankers for each rank pair, and producing, from the ensemble of base rankers, a ranking list that ranks the documents in the set of documents; and creating, using the processor, base rankers only for adjacent rank pairs, each adjacent rank pair comprised of rankings of integer values that directly follow one another in sequence. | 1. A method comprising: processing, using a processor, a user query received to identify a set of documents relevant to a user query by comparing the parameters gathered from the user query with a database of documents; receiving, using the processor, the set of documents for ranking, performing, using the processor, an initial ranking on the received documents, each of the documents assigned an initial ranking from a set of rankings, creating, using the processor, a plurality of document pairs from the received documents based on a vector of features that includes a frequency of a term in each document of the set of documents and a length of each document of the set of documents, each document pair including two documents having two different ranks, each rank pair comprising two different ranks of different integer values, generating, using the processor, at least two subsets of the plurality of document pairs, each subset corresponding to a different rank pair, each rank pair comprising two ranks of different ranking values corresponding to respective different ranks; generating, using the processor, multiple hyperplanes comprising multiple base rankers for each rank pair, wherein each base ranker of the multiple base rankers is a single hyperplane including a linear ranking model trained for a particular rank pair using a ranking support vector machine that ranks the documents in each subset, wherein the generating creates a base ranker for each rank pair; and ranking, using the processor, the document pairs within each of the at least two subsets using the base ranker associated with each rank pair; and aggregating, using the processor, the multiple hyperplanes into an ensemble of base rankers comprising the base rankers for each rank pair, and producing, from the ensemble of base rankers, a ranking list that ranks the documents in the set of documents; and creating, using the processor, base rankers only for adjacent rank pairs, each adjacent rank pair comprised of rankings of integer values that directly follow one another in sequence. 4. The method of claim 1 , wherein the aggregating includes examining the ranking list produced from the ensemble of the base rankers to assign scores in each instance based on a position on the ranking list. | 0.547826 |
9,471,370 | 1 | 4 | 1. A computer-implemented method for batch evaluating a program instruction within a stack evaluator, the method comprising: generating a call frame associated with the program instruction within a call stack that is associated with a program subroutine which includes the program instruction, wherein the call frame includes one or more expressions specified by the program instruction; generating a child frame associated with a first expression of the one or more expressions within the call stack; initiating evaluation of the first expression associated with the child frame; automatically determining, in response to the initiating, whether the first expression associated with the child frame should be sent for batch processing by an application server based on a particular characteristic in common between the first expression and each of one or more other expressions; transitioning the call stack into blocked state, in response to determining that the first expression should be sent for batch processing by the application server; sending the first expression and each of the one or more other expressions to the application server; in response to the application server processing the first expression associated with the child frame, receiving a modification to the child frame that sets a value of the first expression within the child frame; unblocking the call stack; and evaluating the call frame based at least in part on the value of the first expression within the child frame. | 1. A computer-implemented method for batch evaluating a program instruction within a stack evaluator, the method comprising: generating a call frame associated with the program instruction within a call stack that is associated with a program subroutine which includes the program instruction, wherein the call frame includes one or more expressions specified by the program instruction; generating a child frame associated with a first expression of the one or more expressions within the call stack; initiating evaluation of the first expression associated with the child frame; automatically determining, in response to the initiating, whether the first expression associated with the child frame should be sent for batch processing by an application server based on a particular characteristic in common between the first expression and each of one or more other expressions; transitioning the call stack into blocked state, in response to determining that the first expression should be sent for batch processing by the application server; sending the first expression and each of the one or more other expressions to the application server; in response to the application server processing the first expression associated with the child frame, receiving a modification to the child frame that sets a value of the first expression within the child frame; unblocking the call stack; and evaluating the call frame based at least in part on the value of the first expression within the child frame. 4. The method of claim 1 , further comprising generating a second call frame associated with the program instruction within the call stack, wherein the second call frame includes a second expression specified by the program instruction, and generating a child frame associated with the second expression within the call stack. | 0.852087 |
7,991,715 | 11 | 12 | 11. The method of claim 10 , wherein, the learning set of images and the verification set of images are selected via a k-fold cross validation process. | 11. The method of claim 10 , wherein, the learning set of images and the verification set of images are selected via a k-fold cross validation process. 12. The method of claim 11 , further comprising, generating a tree structure from the set of probability values. | 0.5 |
8,694,385 | 1 | 8 | 1. A computer-implemented method for identifying items in response to a query, comprising: under control of one or more computer systems configured with executable instructions, receiving a first query from a first user, the first query including one or more query terms; generating a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determining a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and presenting at least a portion of the first query result for display to the first user according to the ranking values. | 1. A computer-implemented method for identifying items in response to a query, comprising: under control of one or more computer systems configured with executable instructions, receiving a first query from a first user, the first query including one or more query terms; generating a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determining a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and presenting at least a portion of the first query result for display to the first user according to the ranking values. 8. The computer-implemented method of claim 1 , wherein the selection actions are performed by previous users during a first time frame. | 0.732283 |
8,131,546 | 1 | 2 | 1. A method for adaptive sentence boundary disambiguation, comprising: receiving, from a natural language processing system, a document containing text; identifying, by a first heuristic algorithm, sentence text in the document; identifying, by a second heuristic algorithm, non-sentence text in the document, wherein the second heuristic algorithm is operable to identify one of non-sentence texts in a group consisting of lists, tables, names of people, addresses, text without a sentence structure, text included as a list and spatially separated data as non-sentence text; parsing said non-sentence text into one or more logical constructs, wherein each logical construct comprises a set of words; inserting a disambiguator after each of said one or more logical constructs to define a sentence boundary for the logical construct based on one or more natural language structures; and sending the disambiguated document to the natural language processing system, wherein the disambiguated document consists of disambiguated sentences, each disambiguated sentence having a defined boundary and including related contextual information, and the disambiguator is used to signal the natural language processing system the presence of a logical construct to be evaluated independently of other logical constructs. | 1. A method for adaptive sentence boundary disambiguation, comprising: receiving, from a natural language processing system, a document containing text; identifying, by a first heuristic algorithm, sentence text in the document; identifying, by a second heuristic algorithm, non-sentence text in the document, wherein the second heuristic algorithm is operable to identify one of non-sentence texts in a group consisting of lists, tables, names of people, addresses, text without a sentence structure, text included as a list and spatially separated data as non-sentence text; parsing said non-sentence text into one or more logical constructs, wherein each logical construct comprises a set of words; inserting a disambiguator after each of said one or more logical constructs to define a sentence boundary for the logical construct based on one or more natural language structures; and sending the disambiguated document to the natural language processing system, wherein the disambiguated document consists of disambiguated sentences, each disambiguated sentence having a defined boundary and including related contextual information, and the disambiguator is used to signal the natural language processing system the presence of a logical construct to be evaluated independently of other logical constructs. 2. The method according to claim 1 , wherein metadata indicates the document includes a list. | 0.831522 |
7,570,261 | 20 | 21 | 20. A method of creating a computer-implemented three-dimensional data model of an actual environment on a computer storage medium, the method comprising: collecting, storing, and analyzing element display data, said element display data enabling a processor to cause a display of a three-dimensional representation of each of a plurality of actual elements and the position of said elements in relation to one another in the actual environment, at least two of said actual elements being anchor city elements having identifiable architectural characteristics within said actual environment, the display including at least one image skin applied to at least one three-dimensional structure; collecting and storing element information predetermined to be associated with at least one of the elements, wherein said element is a place of business of an advertiser; soliciting and collecting a recurring predetermined lease payment from the advertiser during a corresponding lease period and, in exchange, enabling the advertiser to control at least a portion of the element information associated with said element during said lease period; generating a user-executable version of the data model of the actual environment from the element data and the element information, wherein at least a portion of the element information controlled by the advertiser is displayable to a user of the data model, wherein said anchor city elements encourage the user to explore any actual elements between said anchor city elements, and wherein at least a portion of the display of the three-dimensional representation of each of the plurality of actual elements includes a boundary display effect for increasingly obscuring said portion of the display; and storing said user-executable version of the data model of the actual environment on said computer storage medium. | 20. A method of creating a computer-implemented three-dimensional data model of an actual environment on a computer storage medium, the method comprising: collecting, storing, and analyzing element display data, said element display data enabling a processor to cause a display of a three-dimensional representation of each of a plurality of actual elements and the position of said elements in relation to one another in the actual environment, at least two of said actual elements being anchor city elements having identifiable architectural characteristics within said actual environment, the display including at least one image skin applied to at least one three-dimensional structure; collecting and storing element information predetermined to be associated with at least one of the elements, wherein said element is a place of business of an advertiser; soliciting and collecting a recurring predetermined lease payment from the advertiser during a corresponding lease period and, in exchange, enabling the advertiser to control at least a portion of the element information associated with said element during said lease period; generating a user-executable version of the data model of the actual environment from the element data and the element information, wherein at least a portion of the element information controlled by the advertiser is displayable to a user of the data model, wherein said anchor city elements encourage the user to explore any actual elements between said anchor city elements, and wherein at least a portion of the display of the three-dimensional representation of each of the plurality of actual elements includes a boundary display effect for increasingly obscuring said portion of the display; and storing said user-executable version of the data model of the actual environment on said computer storage medium. 21. The method of claim 20 , which includes updating the element data and the element information. | 0.671141 |
8,527,518 | 18 | 19 | 18. An article as in claim 11 , wherein the operations further comprise: ranking term frequencies based on lengths of the inverted lists retrieved from the terms inverted positional index. | 18. An article as in claim 11 , wherein the operations further comprise: ranking term frequencies based on lengths of the inverted lists retrieved from the terms inverted positional index. 19. An article as in claim 18 , wherein the ranked inverted lists are searched according to the ranking and wherein the identified documents are identified according to the ranking. | 0.5 |
8,954,360 | 1 | 6 | 1. A cascading learning system comprising: a request analyzer configured to receive a request for search terms from a client application, the request analyzer having a normalization manager, a semantic parser, and a context builder, the normalization manager configured to normalize the search terms, the semantic parser configured to parse the normalized search terms to determine semantic concepts, definitions, and relations, the context builder configured to build context into the normalized search terms using the semantic concepts, definitions, and relations and to generate a normalized semantic request based on the context; a request dispatcher and classifier configured to classify and dispatch the normalized semantic request to a corresponding domain-specific module; a search module container comprising a plurality of domain-specific modules, each domain-specific module configured to generate a prediction with a trained probability of an expected output; a terminology manager configured to receive the normalized semantic request from the request dispatcher and classifier, and to manage terminology stored in a contextual network; and a cluster manager configured to control data flow between the request dispatcher and classifier, the search module container, the terminology manager, and a business data source system. | 1. A cascading learning system comprising: a request analyzer configured to receive a request for search terms from a client application, the request analyzer having a normalization manager, a semantic parser, and a context builder, the normalization manager configured to normalize the search terms, the semantic parser configured to parse the normalized search terms to determine semantic concepts, definitions, and relations, the context builder configured to build context into the normalized search terms using the semantic concepts, definitions, and relations and to generate a normalized semantic request based on the context; a request dispatcher and classifier configured to classify and dispatch the normalized semantic request to a corresponding domain-specific module; a search module container comprising a plurality of domain-specific modules, each domain-specific module configured to generate a prediction with a trained probability of an expected output; a terminology manager configured to receive the normalized semantic request from the request dispatcher and classifier, and to manage terminology stored in a contextual network; and a cluster manager configured to control data flow between the request dispatcher and classifier, the search module container, the terminology manager, and a business data source system. 6. The cascading learning system of claim 1 , wherein the request dispatcher and classifier comprises an artificial neural network (ANN) configured to implement a classification algorithm to classify the normalized request data to the corresponding domain-specific module. | 0.612536 |
9,218,810 | 9 | 11 | 9. The system of claim 8 , wherein the semantic and syntactic graph further comprises lexical information. | 9. The system of claim 8 , wherein the semantic and syntactic graph further comprises lexical information. 11. The system of claim 9 , wherein the semantic and syntactic graph further comprises one of speech tags and a syntactic parse of the utterance. | 0.5 |
9,620,128 | 33 | 56 | 33. A computationally-implemented method, comprising: storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party; testing an availability of the adaptation data by comparing a property of the adaptation data located at the referenced location with an expected value of the property of the adaptation data; facilitating transmission of the adaptation data to a target device when there is an indication of a speech-facilitated transaction between the target device and the particular party, wherein the adaptation data is configured to be applied to the target device to assist in execution of the speech-facilitated transaction; and facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data. | 33. A computationally-implemented method, comprising: storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party; testing an availability of the adaptation data by comparing a property of the adaptation data located at the referenced location with an expected value of the property of the adaptation data; facilitating transmission of the adaptation data to a target device when there is an indication of a speech-facilitated transaction between the target device and the particular party, wherein the adaptation data is configured to be applied to the target device to assist in execution of the speech-facilitated transaction; and facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data. 56. The computationally-implemented method of claim 33 , wherein said facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: facilitating the acquisition of the adaptation result data that is based on at least one aspect of the speech-facilitated transaction, wherein the adaptation result data includes a numeric score that is a computer-generated estimate of a success of the speech-facilitated transaction based on an objective aspect of the speech-facilitated transaction. | 0.888558 |
8,019,657 | 8 | 9 | 8. The method according to claim 7 , wherein the product database further comprises the number of recent update for each related keyword of each product. | 8. The method according to claim 7 , wherein the product database further comprises the number of recent update for each related keyword of each product. 9. The method according to claim 8 , the algorithm further comprising deleting related keywords where the first priority values and the number of recent update are low. | 0.5 |
9,495,133 | 5 | 11 | 5. A method of adding a BIOS component to a basic input/output system (BIOS) project, the method comprising: receiving a request to create the BIOS component, the request comprising a component category categorized according to a physical aspect of the BIOS component, a logical aspect of the BIOS component, or a functional aspect of the BIOS component, wherein the BIOS project is a BIOS implementation tailored to a particular motherboard, hardware, or software; in response to the request, searching a project template file for component template files associated with the component category, the component template files comprising templates of at least one required file for the BIOS component, wherein the project template file comprises a resource-only dynamic link library file that contains a file structure encoded within a cabinet file, wherein the project template file comprises an initial file that constitutes the BIOS component, and wherein searching the project template the for the component template files associated with the component category comprises selecting, in the project template file, a project type folder corresponding to a specific type of BIOS project, presenting a user interface in response to selecting, the project type folder; searching, in the project type folder, for a component category folder associated with a component category, selecting a component category folder from a first drop-down menu in the user interface; searching, in the selected component category folder, for component template folders associated with the selected component category, populating a second drop-down menu with the component template folders; requesting, a selection, of a component template folder from the second drop-down menu, receiving the selection of the component template folder as a selected component template folder, searching, in the selected component template folder, for component template file requesting a selection of a component template file from the at least one component template file from the selected component template folder as a selected component template file, receiving the selected component template file; copying the selected component template file to a directory, the selected component template file comprising instructions for building the BIOS component and a token for activating or deactivating functionality associated with the BIOS component; and creating a component file comprising a reference to the selected component template file in the directory. | 5. A method of adding a BIOS component to a basic input/output system (BIOS) project, the method comprising: receiving a request to create the BIOS component, the request comprising a component category categorized according to a physical aspect of the BIOS component, a logical aspect of the BIOS component, or a functional aspect of the BIOS component, wherein the BIOS project is a BIOS implementation tailored to a particular motherboard, hardware, or software; in response to the request, searching a project template file for component template files associated with the component category, the component template files comprising templates of at least one required file for the BIOS component, wherein the project template file comprises a resource-only dynamic link library file that contains a file structure encoded within a cabinet file, wherein the project template file comprises an initial file that constitutes the BIOS component, and wherein searching the project template the for the component template files associated with the component category comprises selecting, in the project template file, a project type folder corresponding to a specific type of BIOS project, presenting a user interface in response to selecting, the project type folder; searching, in the project type folder, for a component category folder associated with a component category, selecting a component category folder from a first drop-down menu in the user interface; searching, in the selected component category folder, for component template folders associated with the selected component category, populating a second drop-down menu with the component template folders; requesting, a selection, of a component template folder from the second drop-down menu, receiving the selection of the component template folder as a selected component template folder, searching, in the selected component template folder, for component template file requesting a selection of a component template file from the at least one component template file from the selected component template folder as a selected component template file, receiving the selected component template file; copying the selected component template file to a directory, the selected component template file comprising instructions for building the BIOS component and a token for activating or deactivating functionality associated with the BIOS component; and creating a component file comprising a reference to the selected component template file in the directory. 11. The method of claim 5 , wherein the logical aspect comprises a core module that is generic from one BIOS project to a second BIOS project, or, a module related to a particular function. | 0.66129 |
9,275,018 | 18 | 29 | 18. A server, comprising: a communication device configured to: intercept a first request for a source document representing a web page, the first request being transmitted from a computing device to a web server via a network, the first request including web browser information indicating web browser software executing on the computing device, and intercept the source document being transmitted from the web server to the computing device via the network in response to the first request, the source document specifying one or more fonts in which to display a text in the source document; and one or more processors configured to: render the web page using the source document, the web page including the text displayed in the one or more fonts, determine unique characters displayed at the web page for each of the one or more fonts in which the text is displayed, and obtain one or more font subsets based on the unique characters, wherein at least one of the one or more font subsets includes the unique characters in the source document and one or more additional characters related to the unique characters in the source document, and wherein the one or more additional characters related to the unique characters include at least one of (i) one or more characters having a different case than one or more of the unique characters and (ii) one or more characters having a different accent than one or more of the unique characters wherein the communication device is further configured to: transmit information to the computing device based on whether the web browser software indicated by the web browser information is capable of displaying a font family having a plurality of fonts, the information specifying the one or more font subsets, and receive a second request from the computing device, the second request being for one or more missing font subsets from the one or more font subsets specified by the information, the one or more missing font subsets being font subsets that the computing device does not have, wherein the one or more processors are further configured to embed the one or more missing font subsets in the source document to obtain a modified source document, and wherein the communication device is further configured to transmit the modified source document to the computing device. | 18. A server, comprising: a communication device configured to: intercept a first request for a source document representing a web page, the first request being transmitted from a computing device to a web server via a network, the first request including web browser information indicating web browser software executing on the computing device, and intercept the source document being transmitted from the web server to the computing device via the network in response to the first request, the source document specifying one or more fonts in which to display a text in the source document; and one or more processors configured to: render the web page using the source document, the web page including the text displayed in the one or more fonts, determine unique characters displayed at the web page for each of the one or more fonts in which the text is displayed, and obtain one or more font subsets based on the unique characters, wherein at least one of the one or more font subsets includes the unique characters in the source document and one or more additional characters related to the unique characters in the source document, and wherein the one or more additional characters related to the unique characters include at least one of (i) one or more characters having a different case than one or more of the unique characters and (ii) one or more characters having a different accent than one or more of the unique characters wherein the communication device is further configured to: transmit information to the computing device based on whether the web browser software indicated by the web browser information is capable of displaying a font family having a plurality of fonts, the information specifying the one or more font subsets, and receive a second request from the computing device, the second request being for one or more missing font subsets from the one or more font subsets specified by the information, the one or more missing font subsets being font subsets that the computing device does not have, wherein the one or more processors are further configured to embed the one or more missing font subsets in the source document to obtain a modified source document, and wherein the communication device is further configured to transmit the modified source document to the computing device. 29. The server of claim 18 , wherein the one or more processors are further configured to generate the one or more missing font subsets, and wherein the communication device is further configured to transmit the one or more missing font subsets to the computing device. | 0.582298 |
7,949,007 | 1 | 12 | 1. A processor-implemented method of generating a plurality of clusters of a plurality of actions for manipulating a plurality of packets of a communication protocol, comprising: inputting a declarative description of a processor of the packets of the communication protocol, the declarative description specifying a hierarchical tree structure including a plurality of modules, the modules including a plurality of respective leaf modules for the actions for manipulating the packets of the communication protocol and a plurality of instance modules; wherein one of the instance modules is a root of the hierarchical tree structure and each of the respective leaf and instance modules other than the root is a child of one of the instance modules; inputting a constraint-specification of at least one dependent pair of the actions; for each respective leaf module, generating a cluster that includes the action of the respective leaf module; for each instance module, generating at least one cluster that collectively includes the actions in each cluster of each child of the instance module; wherein for each cluster of each child of the instance module, the actions in the cluster are included in a same one of the at least one cluster, and each dependent pair of the actions are not included in a same one of the at least one cluster; and outputting a cluster-specification of the at least one cluster of the root. | 1. A processor-implemented method of generating a plurality of clusters of a plurality of actions for manipulating a plurality of packets of a communication protocol, comprising: inputting a declarative description of a processor of the packets of the communication protocol, the declarative description specifying a hierarchical tree structure including a plurality of modules, the modules including a plurality of respective leaf modules for the actions for manipulating the packets of the communication protocol and a plurality of instance modules; wherein one of the instance modules is a root of the hierarchical tree structure and each of the respective leaf and instance modules other than the root is a child of one of the instance modules; inputting a constraint-specification of at least one dependent pair of the actions; for each respective leaf module, generating a cluster that includes the action of the respective leaf module; for each instance module, generating at least one cluster that collectively includes the actions in each cluster of each child of the instance module; wherein for each cluster of each child of the instance module, the actions in the cluster are included in a same one of the at least one cluster, and each dependent pair of the actions are not included in a same one of the at least one cluster; and outputting a cluster-specification of the at least one cluster of the root. 12. The processor-implemented method of claim 1 , wherein the inputting of the constraint-specification includes: inputting a constraint specifying a dependency between from a first one of the modules to a second one of the modules; and determining the at least one dependent pair that is all pairs of one of the actions within the hierarchical tree structure of the first module and one of the actions within the hierarchical tree structure of the second module. | 0.5 |
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