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8,060,574 | 19 | 20 |
19. The central server of claim 14 wherein in order to effect review of the digital content, the control system is further configured to: effect transfer of the digital content to user devices associated with the group of reviewers, wherein feedback from the group of reviewers is provided to the one of the plurality of authors.
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19. The central server of claim 14 wherein in order to effect review of the digital content, the control system is further configured to: effect transfer of the digital content to user devices associated with the group of reviewers, wherein feedback from the group of reviewers is provided to the one of the plurality of authors. 20. The central server of claim 19 wherein the metadata for the digital content includes information describing the digital content, and the control system is further configured to select the group of reviewers from the others of the plurality of authors based on the information describing the digital content and the reviewer credentials of the others of the plurality of authors.
| 0.5 |
7,512,874 | 1 | 2 |
1. An information processing apparatus which receives a search key for inputting an unspecified number of documents on the Internet into a specific search engine which targets the documents for a search, the information processing apparatus comprising: a storage unit that stores a plurality of pieces of specific information in which information concerning the documents is stored; a selecting unit that selects any word in the documents as a desired word, wherein information in the desired word is the search key; an area receiving unit that receives a selecting of the desired word in the documents; a displaying unit that displays a list of databases relating to the plurality of pieces of specific information stored in the storage unit upon receiving the desired word selection; a database election receiving unit that receives an election of a desired database from the list of databases displayed; and a searching unit that makes the specific search engine search using the search key by sending the information concerning the desired word received by the area receiving unit as the search key to the search engine for outputting a search result.
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1. An information processing apparatus which receives a search key for inputting an unspecified number of documents on the Internet into a specific search engine which targets the documents for a search, the information processing apparatus comprising: a storage unit that stores a plurality of pieces of specific information in which information concerning the documents is stored; a selecting unit that selects any word in the documents as a desired word, wherein information in the desired word is the search key; an area receiving unit that receives a selecting of the desired word in the documents; a displaying unit that displays a list of databases relating to the plurality of pieces of specific information stored in the storage unit upon receiving the desired word selection; a database election receiving unit that receives an election of a desired database from the list of databases displayed; and a searching unit that makes the specific search engine search using the search key by sending the information concerning the desired word received by the area receiving unit as the search key to the search engine for outputting a search result. 2. The apparatus according to claim 1 , wherein the plurality of pieces of specific information stored in the storage unit is specified in accordance with a category of the databases.
| 0.5 |
6,031,174 | 10 | 11 |
10. A method according to claim 1, wherein said step (b) starts reading performance data in response to manipulation of the phrase select operator.
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10. A method according to claim 1, wherein said step (b) starts reading performance data in response to manipulation of the phrase select operator. 11. A method according to claim 10, wherein said step (b) starts or stops reading performance data in response to manipulation of the phrase select operator.
| 0.5 |
10,133,945 | 2 | 4 |
2. The gaze based error recognition system as set forth in claim 1 , wherein the machine learning algorithm used for said classifier is support vector machines (SVM) with radial basis kernel function (RBF).
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2. The gaze based error recognition system as set forth in claim 1 , wherein the machine learning algorithm used for said classifier is support vector machines (SVM) with radial basis kernel function (RBF). 4. The gaze based error recognition system as set forth in claim 2 , wherein the optimization of support vector machines (SVM) parameters consist of 5-fold cross validation.
| 0.778205 |
3,975,598 | 5 | 11 |
5. The apparatus according to claim 1 wherein said plurality of spaced-apart analog data storage tracks each comprise a variable width track lying below the surface of said target means and exposed to said electron beam.
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5. The apparatus according to claim 1 wherein said plurality of spaced-apart analog data storage tracks each comprise a variable width track lying below the surface of said target means and exposed to said electron beam. 11. The apparatus according to claim 5 wherein said spaced-apart analog data storage tracks each representing an analog record of an audio signal, said apparatus further comprising filter means receiving the electrical signal from said means for producing, and means for amplifying the signal from said means for filtering.
| 0.53592 |
5,509,104 | 13 | 14 |
13. The speech recognition system of claim 12 wherein at least one of said two extraneous sound training tokens is a spoken utterance which is different from any of said key utterances.
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13. The speech recognition system of claim 12 wherein at least one of said two extraneous sound training tokens is a spoken utterance which is different from any of said key utterances. 14. The speech recognition system of claim 13 wherein said extraneous sound training tokens include at least two of the utterances "um," "please," and "call."
| 0.5 |
5,586,242 | 1 | 15 |
1. A method for managing a plurality of fonts installed in an operating system running on a computer, comprising the steps of: (a) installing a font manager program for use with the operating system running on the computer, said font manager program managing access by a user to the plurality of fonts installed in the operating system, within different applications; (b) enabling the user to create a subset of the plurality of fonts installed in the operating system by selecting specific fonts from among said plurality of fonts using the font manager program, said plurality of fonts being available for access and use in documents by the different applications running on the computer even though not included in the subset created by the user with the font manager program; (c) enabling a user to respectively add and delete fonts to and from the subset using the font manager program, without affecting the plurality of fonts installed in the operating system and without affecting the availability of the plurality of fonts for use in documents by any of the different applications running on the computer; and (d) displaying only the subset of fonts that were defined by the user using the font manager program when the user elects to select a font for use in a document, said subset reducing confusion of the user in selecting said font by displaying less than all of the plurality of fonts installed in the operating system when the user selects the font.
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1. A method for managing a plurality of fonts installed in an operating system running on a computer, comprising the steps of: (a) installing a font manager program for use with the operating system running on the computer, said font manager program managing access by a user to the plurality of fonts installed in the operating system, within different applications; (b) enabling the user to create a subset of the plurality of fonts installed in the operating system by selecting specific fonts from among said plurality of fonts using the font manager program, said plurality of fonts being available for access and use in documents by the different applications running on the computer even though not included in the subset created by the user with the font manager program; (c) enabling a user to respectively add and delete fonts to and from the subset using the font manager program, without affecting the plurality of fonts installed in the operating system and without affecting the availability of the plurality of fonts for use in documents by any of the different applications running on the computer; and (d) displaying only the subset of fonts that were defined by the user using the font manager program when the user elects to select a font for use in a document, said subset reducing confusion of the user in selecting said font by displaying less than all of the plurality of fonts installed in the operating system when the user selects the font. 15. The method of claim 1, further comprising the step of generating a replacement font having characteristics matching a font requested by one of the applications when said font that is requested is not among the plurality of fonts installed in the operating system.
| 0.801043 |
9,672,206 | 27 | 28 |
27. The method according to claim 26 where tokens are decorated with additional data.
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27. The method according to claim 26 where tokens are decorated with additional data. 28. The method according to claim 27 where said additional data is selected from the group consisting of part-of-speech, syntactic, named-entity and semantic labels.
| 0.5 |
6,023,670 | 13 | 16 |
13. The system as recited in claim 12 wherein the comparing, accumulating, correlating and identifying means for a plurality of candidate languages each with a respective word list and a respective reference count and the language of the document is identified as the candidate language having a reference count which generates a highest correlation score.
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13. The system as recited in claim 12 wherein the comparing, accumulating, correlating and identifying means for a plurality of candidate languages each with a respective word list and a respective reference count and the language of the document is identified as the candidate language having a reference count which generates a highest correlation score. 16. The system as recited in claim 13 wherein the system stops when a highest correlation score for a first respective candidate language exceeds a next highest correlation score for a second candidate language by a predetermined amount.
| 0.526 |
8,880,495 | 1 | 9 |
1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query.
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1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query. 9. The method of claim 1 , wherein processing the portion of the audio information is performed at the computing device responsive to a further triggering condition, the further triggering condition including a waking of the computing device from an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed to an active state or a non-sleep state in which the graphical display of the computing device is on or substantially brightened.
| 0.612676 |
7,782,203 | 17 | 19 |
17. A computer-implemented method that facilitates maintaining data consistency related to a radio frequency identification (RFID) process, comprising: employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts: receiving data associated with an RFID process; specifying a specification that specifies a type of an event based at least in part upon the received data; and utilizing the specification for a component to at least one of consume or generate the event.
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17. A computer-implemented method that facilitates maintaining data consistency related to a radio frequency identification (RFID) process, comprising: employing a processor to execute computer executable instructions stored on a computer readable storage medium to implement the following acts: receiving data associated with an RFID process; specifying a specification that specifies a type of an event based at least in part upon the received data; and utilizing the specification for a component to at least one of consume or generate the event. 19. The method of claim 17 , further comprising employing the specification at design time, the design time is a process of conceptualizing the RFID process by specifying at least one of the following: a logical device element; a logical source as a container for the logical device element; or a processing pipeline with a pipeline component configured to receive the event from a logical source.
| 0.56181 |
8,250,004 | 14 | 15 |
14. A computer implemented method for machine learning by a first entity supporting a rule based system, wherein each rule is associated with a centre of a cluster of data points in a combined rule input and rule output data space, the method comprising: receiving a time series data item as input; determining whether a data point for the time series input data item increases or decreases the spatial density for each previously existing rule; if the data point does increase or decrease the spatial density for every previously existing cluster, then creating a new cluster and associated rule, otherwise, if the data point does not increase the spatial density for every previously existing cluster, or does not decrease the spatial density for every previously existing cluster, then not creating a new cluster; and repeating the method for a next time series data item received.
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14. A computer implemented method for machine learning by a first entity supporting a rule based system, wherein each rule is associated with a centre of a cluster of data points in a combined rule input and rule output data space, the method comprising: receiving a time series data item as input; determining whether a data point for the time series input data item increases or decreases the spatial density for each previously existing rule; if the data point does increase or decrease the spatial density for every previously existing cluster, then creating a new cluster and associated rule, otherwise, if the data point does not increase the spatial density for every previously existing cluster, or does not decrease the spatial density for every previously existing cluster, then not creating a new cluster; and repeating the method for a next time series data item received. 15. The method of claim 14 , further comprising: determining if the newly created rule is similar to any of the previously existing rules, and if so then removing the previously existing rule or rules from the rule base.
| 0.73747 |
8,255,351 | 7 | 8 |
7. The system of claim 6 , wherein the context pattern learner generates a correlation probability table corresponding to the new knowledge rules.
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7. The system of claim 6 , wherein the context pattern learner generates a correlation probability table corresponding to the new knowledge rules. 8. The system of claim 7 , wherein the fault predictor analyzes the correlation between the correlation probability table corresponding to the new knowledge rules and the context information collected in real time.
| 0.5 |
9,519,463 | 1 | 22 |
1. A method for generating a flowchart for a test program, comprising: selecting, using a processor, one of a plurality of programming language configuration files stored in at least one memory component, based on a programming language of the test program, each of the programming language configuration files being specific to one programming language and including regular expressions to identify lines of program code of the test program using keywords and constructs of the programming language; selecting, using a processor, one of a plurality of test station configuration files stored in at least one memory component, based on a test station for which the test program is written, each of the test station configuration files being specific to one test station and including regular expressions to identify lines of code of the test program that use application programming interfaces (APIs) to control specific instruments of the test station; parsing the test program into parsed data, using a processor and the regular expressions in the selected one of the programming language configuration files and the regular expressions in the selected one of the test station configuration files; and interpreting, using a processor, the parsed data to enable generation of the flowchart.
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1. A method for generating a flowchart for a test program, comprising: selecting, using a processor, one of a plurality of programming language configuration files stored in at least one memory component, based on a programming language of the test program, each of the programming language configuration files being specific to one programming language and including regular expressions to identify lines of program code of the test program using keywords and constructs of the programming language; selecting, using a processor, one of a plurality of test station configuration files stored in at least one memory component, based on a test station for which the test program is written, each of the test station configuration files being specific to one test station and including regular expressions to identify lines of code of the test program that use application programming interfaces (APIs) to control specific instruments of the test station; parsing the test program into parsed data, using a processor and the regular expressions in the selected one of the programming language configuration files and the regular expressions in the selected one of the test station configuration files; and interpreting, using a processor, the parsed data to enable generation of the flowchart. 22. The method of claim 1 , further comprising selecting, using the processor or a different processor, one of a plurality of flowcharting configuration files, based on the selected one of the test station configuration files; and interpreting, using the processor or a different processor and the selected one of the flowcharting configuration files, the parsed data with algorithms that cause generation of the flowchart according to definitions defined in the selected one of the flowcharting configuration files.
| 0.507634 |
9,066,128 | 10 | 16 |
10. A system for interacting with a media guidance application in multiple languages, the method comprising control circuitry figured to: receive, from a user device, a first user selection of a first language for interacting with an interactive media guidance application; in response to receiving the first user selection of the first language, transmit, from a server that is remote to the user device, a first media guidance data associated with the first language; receive, from the user device, a second user selection to switch the first language to a second language for interacting with the interactive media guidance application; and in response to receiving the selected second language, transmit, from the server to the user device, a second media guidance data associated with the selected second language.
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10. A system for interacting with a media guidance application in multiple languages, the method comprising control circuitry figured to: receive, from a user device, a first user selection of a first language for interacting with an interactive media guidance application; in response to receiving the first user selection of the first language, transmit, from a server that is remote to the user device, a first media guidance data associated with the first language; receive, from the user device, a second user selection to switch the first language to a second language for interacting with the interactive media guidance application; and in response to receiving the selected second language, transmit, from the server to the user device, a second media guidance data associated with the selected second language. 16. The system of claim 10 , wherein the control circuitry is further configured to: receive a third user selection of a media asset, wherein the media asset has a plurality of associated tracks having content in at least two different languages; in response to the third user selection of the media asset and the second user selection to switch the first language to the second language for interacting with the interactive media guidance application, transmit to the user device only a track, from the plurality of associated tracks, that is associated with the selected second language.
| 0.5 |
8,145,992 | 2 | 3 |
2. The method of claim 1 , further comprising associating a waypoint with the at least one conversion component in the conversion chain.
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2. The method of claim 1 , further comprising associating a waypoint with the at least one conversion component in the conversion chain. 3. The method of claim 2 , wherein the validation results comprise a document status for each document in the document collection, wherein each document is indicated as being valid if the conversion component associated with the waypoint was successfully executed on the document, and invalid otherwise.
| 0.5 |
8,856,153 | 11 | 15 |
11. A computer system comprising: one or more processors; one or more non-transitory computer-readable storage media storing instructions, which, when executed by the one or more processors, cause: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type; wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance.
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11. A computer system comprising: one or more processors; one or more non-transitory computer-readable storage media storing instructions, which, when executed by the one or more processors, cause: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type; wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance. 15. The computer system of claim 11 , wherein the instructions, when executed, further cause receiving user input that defines the object type, the first property type, and the second property type before storing the particular parser definition.
| 0.719178 |
8,762,385 | 14 | 15 |
14. The computer-readable memory as in claim 13 , wherein the sets of instructions when further executed by the computer, cause the computer to receive input of a toggle button/key configured to retrieve associated email addresses.
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14. The computer-readable memory as in claim 13 , wherein the sets of instructions when further executed by the computer, cause the computer to receive input of a toggle button/key configured to retrieve associated email addresses. 15. The computer-readable memory as in claim 14 , wherein the sets of instructions when further executed by the computer, cause the computer to display each of the recipient template which include the one or more entered email addresses.
| 0.5 |
8,272,009 | 1 | 3 |
1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot.
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1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot. 3. The method of claim 1 , wherein monitoring is performed prior to said programming being broadcast via the broadcast network.
| 0.90109 |
6,122,661 | 21 | 22 |
21. A method according to claim 19, further comprising: storing computer display information representing a plurality of computer displays into the presentation space buffer; receiving the presentation space data stream containing the computer display information representing the plurality of computer displays into the display control of the server application framework of the server computer; and converting substantially the entire presentation space data stream containing the computer display information representing the plurality of computer displays into a single markup language document using the host extension of the server application framework of the serve computer.
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21. A method according to claim 19, further comprising: storing computer display information representing a plurality of computer displays into the presentation space buffer; receiving the presentation space data stream containing the computer display information representing the plurality of computer displays into the display control of the server application framework of the server computer; and converting substantially the entire presentation space data stream containing the computer display information representing the plurality of computer displays into a single markup language document using the host extension of the server application framework of the serve computer. 22. A method according to claim 21, wherein the plurality of computer displays comprises a single session running on the host computer.
| 0.521277 |
8,015,041 | 1 | 3 |
1. A computer implemented method of generating an electronic database comprising a collection of transaction data sets that identify multiple independent transaction data sets to a single purchasing contract, said method comprising the steps of: creating a Transaction Detail Database for storing data sets representing transactions, including defining data storage adapted to storing the data sets in accordance with a common data format; collecting transaction data for each of a plurality of transactions from one or more sources; electronically storing, in the Transaction Detail Database, the collected transaction data as a transaction data set in accordance with the common data format; repeating the collecting and electronically storing steps multiple times to populate the Transaction Detail Database with a population of transaction data sets; selecting a contract term of a purchasing contract, from a Contract Registry Database storing a plurality of contract terms, wherein the contract term is associated in the Contract Registry Database with one or more contract term criteria defining the contract term; executing a computer program to identify a plurality of transaction data sets from the population of transaction data sets stored in the Transaction Detail Database with the contract term, including electronically comparing data elements of the transaction data sets with the contract term criteria; and generating a collection of contract-specific transaction data sets including each identified transaction data set; and wherein said step of executing a computer program to identify a plurality of transaction data sets with the contract term, includes: electronically comparing a data element of the transaction data sets with contract term customer criteria, electronically comparing a data element of the transaction data sets with contract term market criteria, electronically comparing a data element of the transaction data sets with contract term supplier criteria, and electronically comparing a data element of the transaction data sets with contract term product criteria.
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1. A computer implemented method of generating an electronic database comprising a collection of transaction data sets that identify multiple independent transaction data sets to a single purchasing contract, said method comprising the steps of: creating a Transaction Detail Database for storing data sets representing transactions, including defining data storage adapted to storing the data sets in accordance with a common data format; collecting transaction data for each of a plurality of transactions from one or more sources; electronically storing, in the Transaction Detail Database, the collected transaction data as a transaction data set in accordance with the common data format; repeating the collecting and electronically storing steps multiple times to populate the Transaction Detail Database with a population of transaction data sets; selecting a contract term of a purchasing contract, from a Contract Registry Database storing a plurality of contract terms, wherein the contract term is associated in the Contract Registry Database with one or more contract term criteria defining the contract term; executing a computer program to identify a plurality of transaction data sets from the population of transaction data sets stored in the Transaction Detail Database with the contract term, including electronically comparing data elements of the transaction data sets with the contract term criteria; and generating a collection of contract-specific transaction data sets including each identified transaction data set; and wherein said step of executing a computer program to identify a plurality of transaction data sets with the contract term, includes: electronically comparing a data element of the transaction data sets with contract term customer criteria, electronically comparing a data element of the transaction data sets with contract term market criteria, electronically comparing a data element of the transaction data sets with contract term supplier criteria, and electronically comparing a data element of the transaction data sets with contract term product criteria. 3. The method of claim 1 , wherein the purchasing contract is identified by a common carrier entity and customer entity, said step of executing a computer program to identify a plurality of transaction data sets with the contract term, includes electronically comparing a data element of the stored transaction data set with a contract term criterion selected from the group of term criteria consisting of: customer criteria; market criteria; supplier criteria; product criteria; and derivatives thereof.
| 0.511628 |
9,200,922 | 1 | 15 |
1. A method comprising: presenting a map including a viewport showing a first location; receiving a first indication that a user is interacting with the map, including one or more first panning, scrolling, repositioning, or zooming interactions, to enable one or more intermediate locations to be visible in the viewport, without submitting a query for any of the intermediate locations; receiving a second indication that the user is continuing to interact with the map, including one or more second panning, scrolling, repositioning, or zooming interactions, to enable a location of interest to be visible in the viewport; determining, by one or more processors, that the user has arrived at the location of interest, the location of interest being visible in the viewport as a result of the second panning, scrolling, repositioning, or zooming interactions, the determining based at least in part on evaluating the first and second interactions; based on determining that the user has arrived at the location of interest, automatically submitting a query for the location of interest; receiving query results responsive to the query; and presenting the query results along with the viewport showing the location of interest.
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1. A method comprising: presenting a map including a viewport showing a first location; receiving a first indication that a user is interacting with the map, including one or more first panning, scrolling, repositioning, or zooming interactions, to enable one or more intermediate locations to be visible in the viewport, without submitting a query for any of the intermediate locations; receiving a second indication that the user is continuing to interact with the map, including one or more second panning, scrolling, repositioning, or zooming interactions, to enable a location of interest to be visible in the viewport; determining, by one or more processors, that the user has arrived at the location of interest, the location of interest being visible in the viewport as a result of the second panning, scrolling, repositioning, or zooming interactions, the determining based at least in part on evaluating the first and second interactions; based on determining that the user has arrived at the location of interest, automatically submitting a query for the location of interest; receiving query results responsive to the query; and presenting the query results along with the viewport showing the location of interest. 15. The method of claim 1 where the map is displayed on a touchscreen device.
| 0.916304 |
8,669,888 | 15 | 16 |
15. The Hangeul input method of claim 12 , wherein the selected basic consonant, extended consonant, basic vowel, and combined vowel are displayed on a display screen, the display screen including: an input window for displaying the selected basic consonant, extended consonant, basic vowel, and combined vowel; and an input candidate group display window for sequentially displaying the basic consonants and basic vowels assigned respectively to the consonant keys and vowel keys when selecting the consonant keys and vowel keys, and displaying the extended consonants converted from the corresponding basic convertible consonants by the shift key in the sequence of an aspirate of the corresponding basic convertible consonants and a fortis of the corresponding basic convertible consonants when selecting the shift key.
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15. The Hangeul input method of claim 12 , wherein the selected basic consonant, extended consonant, basic vowel, and combined vowel are displayed on a display screen, the display screen including: an input window for displaying the selected basic consonant, extended consonant, basic vowel, and combined vowel; and an input candidate group display window for sequentially displaying the basic consonants and basic vowels assigned respectively to the consonant keys and vowel keys when selecting the consonant keys and vowel keys, and displaying the extended consonants converted from the corresponding basic convertible consonants by the shift key in the sequence of an aspirate of the corresponding basic convertible consonants and a fortis of the corresponding basic convertible consonants when selecting the shift key. 16. The Hangeul input method of claim 15 , wherein the corresponding basic consonant is also displayed on the input candidate group display window in the sequence of the corresponding basic consonants, aspirate of the corresponding basic consonants, and fortis of the corresponding basic consonants when selecting the conversion key.
| 0.5 |
7,886,228 | 2 | 3 |
2. The method of claim 1 , further comprising recording the audio to be associated with one or more of the first set of the reduced graphical representations.
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2. The method of claim 1 , further comprising recording the audio to be associated with one or more of the first set of the reduced graphical representations. 3. The method of claim 2 , further comprising displaying a non-numeric graphical representation associated with the recorded audio, the non-numeric graphical representation representing a length of the recorded audio.
| 0.5 |
9,195,379 | 1 | 4 |
1. A method comprising: receiving a package specification unit (PU) representative of a design of a converged infrastructure (CI) including compute, storage, network, and virtualization components, the package specification unit including compiled component readable tasks that perform operations on the CI components, the package specification unit further including: an inventory task model associated with tasks to read inventory information from the CI components; an assessment task model associated with tasks to assess the CI components; a configuration task model associated with tasks to configure the CI components; and a user input model to generate prompts to solicit and receive CI component information from a user, and provide the received information to the other package specification unit models; displaying a package specification unit model menu from which the package specification unit models may be selected; receiving a selection of one of the package specification unit models through the package specification unit model menu; and executing one or more tasks associated with the selected package specification unit model to perform corresponding operations on the CI components.
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1. A method comprising: receiving a package specification unit (PU) representative of a design of a converged infrastructure (CI) including compute, storage, network, and virtualization components, the package specification unit including compiled component readable tasks that perform operations on the CI components, the package specification unit further including: an inventory task model associated with tasks to read inventory information from the CI components; an assessment task model associated with tasks to assess the CI components; a configuration task model associated with tasks to configure the CI components; and a user input model to generate prompts to solicit and receive CI component information from a user, and provide the received information to the other package specification unit models; displaying a package specification unit model menu from which the package specification unit models may be selected; receiving a selection of one of the package specification unit models through the package specification unit model menu; and executing one or more tasks associated with the selected package specification unit model to perform corresponding operations on the CI components. 4. The method of claim 1 , wherein the selected task model is the inventory task model and the executing includes executing one or more tasks associated with the inventory task model to solicit and receive inventory information from one or more of the compute, storage, network, and virtualization components, the method further comprising displaying the received inventory information.
| 0.716176 |
9,613,364 | 1 | 4 |
1. A computing device configured to identify a concept of a good or service for an unmet market potential, the device comprising: a hardware processor; a non-transitory storage device; a program stored in the storage device; wherein execution of the program by the processor configures the computing device to perform functions, including functions to: read a Global User Search Data (GUSD) comprising information related to a search object; determine an un-successfulness of the search object; assign a first score based on the unsuccessfulness; wherein a higher first score is assigned the more un-successful the search object is; determine from the GUSD one or more locations from which similar search objects originated; assign a second score based on a geographic dispersion of the one or more searcher locations, wherein a higher second score is assigned the higher the geographic dispersion of the one or more locations: identify a morpheme combination in the search object from the GUSD; compare the morpheme combination to a first set of pre-existing terms; assign a third score to the search object based on the comparison, wherein a higher third score is assigned if the morpheme combination is not found in the first set of pre-existing terms; compare an aggregate of the first score, reflecting the un-successfulness of the search object, the second score, reflecting the geographic disparity of the one or more locations from which the similar search objects originated, and the third score, reflecting the likelihood that the morpheme combination is not found in the first set of pre-existing terms, for a search term to a predetermined threshold; and identify the search term as indicative of the concept of good or service for an unmet market potential if the aggregate of the first score, the second score, and the third score is above the predetermined threshold.
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1. A computing device configured to identify a concept of a good or service for an unmet market potential, the device comprising: a hardware processor; a non-transitory storage device; a program stored in the storage device; wherein execution of the program by the processor configures the computing device to perform functions, including functions to: read a Global User Search Data (GUSD) comprising information related to a search object; determine an un-successfulness of the search object; assign a first score based on the unsuccessfulness; wherein a higher first score is assigned the more un-successful the search object is; determine from the GUSD one or more locations from which similar search objects originated; assign a second score based on a geographic dispersion of the one or more searcher locations, wherein a higher second score is assigned the higher the geographic dispersion of the one or more locations: identify a morpheme combination in the search object from the GUSD; compare the morpheme combination to a first set of pre-existing terms; assign a third score to the search object based on the comparison, wherein a higher third score is assigned if the morpheme combination is not found in the first set of pre-existing terms; compare an aggregate of the first score, reflecting the un-successfulness of the search object, the second score, reflecting the geographic disparity of the one or more locations from which the similar search objects originated, and the third score, reflecting the likelihood that the morpheme combination is not found in the first set of pre-existing terms, for a search term to a predetermined threshold; and identify the search term as indicative of the concept of good or service for an unmet market potential if the aggregate of the first score, the second score, and the third score is above the predetermined threshold. 4. The computing device of claim 1 , wherein execution of the program further configures the computing device to perform functions to: Determine from the GUSD a number of times in a predetermined period a similar combination of morphemes is found and assign a fifth score based on the number of times in the predetermined period the similar combination of morphemes is found, wherein a higher fifth score is assigned the lower the number of times in the predetermined period the similar combination of morphemes is searched, and a lower fifth score is assigned the higher the number of times in the predetermined period the similar combination of morphemes is searched.
| 0.5 |
8,301,624 | 1 | 2 |
1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions.
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1. A method comprising: determining a set of item-item affinities between a first item and a first plurality of items from a set of user-item data; determining a first set of nearest neighbor items from the first plurality of items based in part on the set of item-item affinities; determining a set of user feature-item affinities between a second plurality of items and a set of user features; determining a second set of nearest neighbor items based at least in part on the set of user feature-item affinities; determining affinity weights for a set of candidate items, the set of candidate items to be determined at least in part on the first set of nearest neighbor items and the second set of nearest neighbor items; and presenting to a user as a recommendation a candidate item from the set of candidate items, the candidate item to be determined at least in part based on an affinity weight of the candidate item; wherein determining the set of item-item affinities between the first item and the first plurality of items comprises for each particular column of a user-item matrix, setting an item-item affinity between the first item and another item represented by the particular column equal to a cosine similarity between the particular column and a first column of the user-item matrix representing the first item; wherein said each particular column of the user-item matrix indicates multiple ratings that multiple users have given to an item represented by said each particular column; wherein determining the set of user feature-item affinities between the second plurality of items and the set of user features comprises performing least square regression relative to an equation involving both said user-item matrix and a user profile matrix that is separate from said user-item matrix; wherein each particular column of the user profile matrix corresponds to a different user feature of a plurality of user features; wherein all user features in said plurality of user features differ from all items represented by columns of said user-item matrix; wherein each particular row of said user profile matrix corresponds to a different user of a plurality of users; and wherein the method is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions. 2. The method of claim 1 , wherein the set of item-item affinities is determined at least based in part on user ratings of the first plurality of items.
| 0.836559 |
7,761,408 | 9 | 14 |
9. A system for selecting customized content for a user device, comprising: a processor; an information extractor when executed by the processor configured to obtain at least one keyword from analyzing data entered into the user, device the data comprising text entered into a messaging program at the user device; a behavioral engine when executed by the processor configured to obtain at least one keyword from analyzing a behavior of a user of the user device; and a keyword manager when executed by the processor configured to receive at least two keywords from at least one of the information extractor and the behavioral engine, the keyword manager further configured to analyze the at least two keywords to obtain a prioritized list of keywords and to provide the prioritized list of keywords to a component configured to select customized content for the user device based on the prioritized list of keywords.
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9. A system for selecting customized content for a user device, comprising: a processor; an information extractor when executed by the processor configured to obtain at least one keyword from analyzing data entered into the user, device the data comprising text entered into a messaging program at the user device; a behavioral engine when executed by the processor configured to obtain at least one keyword from analyzing a behavior of a user of the user device; and a keyword manager when executed by the processor configured to receive at least two keywords from at least one of the information extractor and the behavioral engine, the keyword manager further configured to analyze the at least two keywords to obtain a prioritized list of keywords and to provide the prioritized list of keywords to a component configured to select customized content for the user device based on the prioritized list of keywords. 14. The system of claim 9 , further comprising a translator operable to translate at least one keyword in the prioritized list of keywords into a format usable by an application on the user device.
| 0.742147 |
9,015,099 | 12 | 13 |
12. The method of claim 10 , wherein the execution of the automated response comprises sending a communication relating to the inferred user-specific context to another electronic device.
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12. The method of claim 10 , wherein the execution of the automated response comprises sending a communication relating to the inferred user-specific context to another electronic device. 13. The method of claim 12 , comprising determining, from the selected user-specific context, one or more recipients for the communication and sending the communication to the one or more recipients over an electronic network.
| 0.5 |
8,364,750 | 1 | 6 |
1. A computer-implemented method of invoking services of a service host the method comprising: upon receiving a first logic comprising a language integrated query and at least two service invocations specified in a first language that does not support a batching of service invocations: translating respective service invocations in the first language into translated service invocations specified in a second language that supports the batching of service invocations and translating the language integrated query into an expression tree specified in the second language, wherein the expression tree comprises at least one lambda expression generated from the first logic; generating a batch logic specified in the second language and comprising the at least two service invocations of the service; and sending the batch logic to the service host.
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1. A computer-implemented method of invoking services of a service host the method comprising: upon receiving a first logic comprising a language integrated query and at least two service invocations specified in a first language that does not support a batching of service invocations: translating respective service invocations in the first language into translated service invocations specified in a second language that supports the batching of service invocations and translating the language integrated query into an expression tree specified in the second language, wherein the expression tree comprises at least one lambda expression generated from the first logic; generating a batch logic specified in the second language and comprising the at least two service invocations of the service; and sending the batch logic to the service host. 6. The method of claim 1 , comprising: receiving a service invocation result from the service host in response to the batch logic.
| 0.630682 |
8,250,046 | 20 | 21 |
20. A system for performing cross-language search, comprising: a data processing apparatus; a data store storing instructions that, when executed by the data processing apparatus, cause the data processing apparatus to define: an input module operable to receive an original search query in a first language from a user; a query evaluation module operable to determine that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtain a translated search query for the original search query, the translated search query being in the second language; determine that the translated search query is a candidate for a cross-language search, wherein the determining comprises: obtaining a number of previous queries that correspond to the translated search query; comparing the number of previous queries to a threshold number of queries; determining that the number of previous queries exceeds the threshold number of queries; and determining that the translated search query is a candidate for a cross-language search in response to determining that the number of previous queries exceeds the threshold number of queries; and an output module operable to generate search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search.
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20. A system for performing cross-language search, comprising: a data processing apparatus; a data store storing instructions that, when executed by the data processing apparatus, cause the data processing apparatus to define: an input module operable to receive an original search query in a first language from a user; a query evaluation module operable to determine that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtain a translated search query for the original search query, the translated search query being in the second language; determine that the translated search query is a candidate for a cross-language search, wherein the determining comprises: obtaining a number of previous queries that correspond to the translated search query; comparing the number of previous queries to a threshold number of queries; determining that the number of previous queries exceeds the threshold number of queries; and determining that the translated search query is a candidate for a cross-language search in response to determining that the number of previous queries exceeds the threshold number of queries; and an output module operable to generate search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search. 21. The system of claim 20 , determining that the translated search query is a candidate for a cross-language search further comprises: identifying a set of web pages responsive to the translated search query and a set of relevance scores for the set of web pages; comparing the relevance score to a threshold relevance score; determining that the relevance score exceeds the threshold relevance score; and determining that the translated search query is a candidate for a cross-language search in response to determining that the relevance score exceeds the threshold relevance score.
| 0.5 |
9,436,779 | 15 | 17 |
15. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause: executing an index generation statement identifying a plurality of path expressions and a plurality of columns of a first table for indexing a collection of documents wherein said plurality of path expressions identify less than all nodes in the collection of documents wherein for each column of said plurality of columns, said index generation statement specifies an association between said each column and a respective path expression of said plurality of path expressions; wherein execution of said index generation statement causes generation of said first table, wherein the first table comprises a first set of entries; wherein for each column of the plurality of columns of said first table, each entry of the first set of entries contains a node value of a node identified by the respective path expression of said each column, said node value being from a document of said collection of documents; wherein the collection of documents is also indexed by a second table, wherein the second table comprises a second set of entries, each entry in the second set of entries: being associated with a given node of a document in the collection of documents, and including location data for locating content in the document, wherein the content is associated with the given node and path data that corresponds to a path to the given node in the document; and intercepting, by a database system, a query for first information from a collection of documents, wherein the query for first information does not reference said first table and said second table; said database system rewriting the query for first information to generate a rewritten query that references said first table and said second table; wherein the query comprises one or more predicates; based on the rewritten query, said database system generating a first query plan using both the first table and the second table, wherein the first query plan, when executed by the database system, causes the database system to perform: identifying one or more first entries from the first table that contain a node value that satisfies the one or more predicates; extracting second information from the one or more first entries identified from the first table; extracting, using the second information, the first information from one or more second entries in the second table wherein the first table and the second table are two different tables.
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15. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause: executing an index generation statement identifying a plurality of path expressions and a plurality of columns of a first table for indexing a collection of documents wherein said plurality of path expressions identify less than all nodes in the collection of documents wherein for each column of said plurality of columns, said index generation statement specifies an association between said each column and a respective path expression of said plurality of path expressions; wherein execution of said index generation statement causes generation of said first table, wherein the first table comprises a first set of entries; wherein for each column of the plurality of columns of said first table, each entry of the first set of entries contains a node value of a node identified by the respective path expression of said each column, said node value being from a document of said collection of documents; wherein the collection of documents is also indexed by a second table, wherein the second table comprises a second set of entries, each entry in the second set of entries: being associated with a given node of a document in the collection of documents, and including location data for locating content in the document, wherein the content is associated with the given node and path data that corresponds to a path to the given node in the document; and intercepting, by a database system, a query for first information from a collection of documents, wherein the query for first information does not reference said first table and said second table; said database system rewriting the query for first information to generate a rewritten query that references said first table and said second table; wherein the query comprises one or more predicates; based on the rewritten query, said database system generating a first query plan using both the first table and the second table, wherein the first query plan, when executed by the database system, causes the database system to perform: identifying one or more first entries from the first table that contain a node value that satisfies the one or more predicates; extracting second information from the one or more first entries identified from the first table; extracting, using the second information, the first information from one or more second entries in the second table wherein the first table and the second table are two different tables. 17. The medium of claim 15 , wherein the one or more sequences of instructions further comprise instructions which, when executed by one or more processors, causes the one or more processors to perform a joining of the first table and the second table based on one or more columns indexed by a secondary index.
| 0.735495 |
7,831,597 | 40 | 41 |
40. The method of claim 39 , further comprising highlighting at least one of a query term and a secondary term in the returned text summarization segment.
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40. The method of claim 39 , further comprising highlighting at least one of a query term and a secondary term in the returned text summarization segment. 41. The method of claim 40 , wherein the form of highlighting of each highlighted term is based upon the respective computed weight.
| 0.5 |
8,862,661 | 7 | 11 |
7. A method of processing content in a plurality of languages, the method comprising: establish a bind relationship between content in an embedded database, wherein the embedded database stores and retrieves content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language, at a client computer and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generating, by the application program at the client computer, a request to the server computer for first content which is in a first language, if the first content is not stored in an embedded database of the client computer; and automatically receiving from the server computer updated first content in the first language, if there is a change in second content which is content in a second language translated from the first language; storing the first content in the embedded database at the client computer; retrieving the first content from the embedded database at the client computer; displaying the first content on a window of the application program at the client computer; and overlaying the displayed first content with the updated first content.
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7. A method of processing content in a plurality of languages, the method comprising: establish a bind relationship between content in an embedded database, wherein the embedded database stores and retrieves content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language, at a client computer and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generating, by the application program at the client computer, a request to the server computer for first content which is in a first language, if the first content is not stored in an embedded database of the client computer; and automatically receiving from the server computer updated first content in the first language, if there is a change in second content which is content in a second language translated from the first language; storing the first content in the embedded database at the client computer; retrieving the first content from the embedded database at the client computer; displaying the first content on a window of the application program at the client computer; and overlaying the displayed first content with the updated first content. 11. The method of claim 7 further comprising notifying translators of changes as developers add new content to the application program.
| 0.866864 |
7,542,934 | 1 | 11 |
1. A method of analyzing a waveform of a stock to detect predetermined patterns in said waveform using a computer system comprising: providing a data record array to said computer system that includes price and volume data of said stock; providing constants to said computer system relating to a definition of said specified predetermined patterns; analyzing said data record array in said computer system to determine if a base has formed that has a top of base value and a bottom of base value that are separated by a specified amount and a temporal length greater than a minimum base length; analyzing said data record array in said computer system to determine the existence of specified said predetermined patterns in said base; analyzing said data record array in said computer system to determine the existence of specified said predetermined patterns that are attached to said base; displaying said predetermined patterns in said base and said predetermined patterns attached to said base.
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1. A method of analyzing a waveform of a stock to detect predetermined patterns in said waveform using a computer system comprising: providing a data record array to said computer system that includes price and volume data of said stock; providing constants to said computer system relating to a definition of said specified predetermined patterns; analyzing said data record array in said computer system to determine if a base has formed that has a top of base value and a bottom of base value that are separated by a specified amount and a temporal length greater than a minimum base length; analyzing said data record array in said computer system to determine the existence of specified said predetermined patterns in said base; analyzing said data record array in said computer system to determine the existence of specified said predetermined patterns that are attached to said base; displaying said predetermined patterns in said base and said predetermined patterns attached to said base. 11. The method of claim 1 wherein said process of displaying said predetermined patterns comprises: displaying said predetermined patterns as annotated waveforms.
| 0.926364 |
10,097,631 | 1 | 9 |
1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain.
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1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain. 9. The method of claim 1 , wherein selecting the second document comprises: for a first document shared by an entity associated with the social-networking system, determining an application ID corresponding to the entity; and determining whether the second document is shared by an entity corresponding to the application ID.
| 0.701287 |
7,788,254 | 1 | 12 |
1. A method of analyzing web pages, comprising: accessing a plurality of web pages; generating a plurality of different graphical representations of the web pages, each graphical representation having nodes that represent the web pages and links between the nodes, the nodes in each of the graphical representations representing a same set of the web pages as represented in other of the graphical representations, and the links in each graphical representation representing different relationships between the nodes in each graphical representation from the other graphical representations; generating a model that models a random walk through all of the different graphical representations; receiving training pages, wherein each of a plurality of training nodes, in the graphical representations, corresponding to a training page has a target function value indicative of a label for the corresponding training page, the label indicating the corresponding training page belongs to one of a plurality of different groups; generating a classifier based on the model, based on classifier function values of nodes in the graphical representations, and based on the target function values of the training pages; and grouping the web pages into groups with the classifier.
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1. A method of analyzing web pages, comprising: accessing a plurality of web pages; generating a plurality of different graphical representations of the web pages, each graphical representation having nodes that represent the web pages and links between the nodes, the nodes in each of the graphical representations representing a same set of the web pages as represented in other of the graphical representations, and the links in each graphical representation representing different relationships between the nodes in each graphical representation from the other graphical representations; generating a model that models a random walk through all of the different graphical representations; receiving training pages, wherein each of a plurality of training nodes, in the graphical representations, corresponding to a training page has a target function value indicative of a label for the corresponding training page, the label indicating the corresponding training page belongs to one of a plurality of different groups; generating a classifier based on the model, based on classifier function values of nodes in the graphical representations, and based on the target function values of the training pages; and grouping the web pages into groups with the classifier. 12. The method of claim 1 wherein grouping the web pages into groups comprises: identifying a community of web pages based on usage of the web pages.
| 0.697154 |
8,418,135 | 9 | 11 |
9. A non-transitory machine-readable medium that stores instructions that, if executed by a processing device, will cause the processing device to perform operations comprising: identifying, by a first driver executed by the processing device, a first file comprising a first plurality of rules written in a first rule language, wherein the first driver corresponds to the first rule language; converting, by the first driver, the first plurality of rules written in the first rule language in a plurality of descriptor classes using a plurality of rule patterns, wherein the plurality of descriptor classes are used to model rule concepts supported by a rule engine; generating, by the first driver, an intermediate structure comprising an abstract syntax tree of the plurality of descriptor classes; inputting, by the processing device, the intermediate structure to a second driver, wherein the second driver corresponds to a second rule language; translating, by the second driver executed by the processing device, the plurality of descriptor classes in the abstract syntax tree in the intermediate structure into a second plurality of rules written in the second rule language; and generating, by the second driver, a second file comprising the second plurality of rules written in the second rule language.
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9. A non-transitory machine-readable medium that stores instructions that, if executed by a processing device, will cause the processing device to perform operations comprising: identifying, by a first driver executed by the processing device, a first file comprising a first plurality of rules written in a first rule language, wherein the first driver corresponds to the first rule language; converting, by the first driver, the first plurality of rules written in the first rule language in a plurality of descriptor classes using a plurality of rule patterns, wherein the plurality of descriptor classes are used to model rule concepts supported by a rule engine; generating, by the first driver, an intermediate structure comprising an abstract syntax tree of the plurality of descriptor classes; inputting, by the processing device, the intermediate structure to a second driver, wherein the second driver corresponds to a second rule language; translating, by the second driver executed by the processing device, the plurality of descriptor classes in the abstract syntax tree in the intermediate structure into a second plurality of rules written in the second rule language; and generating, by the second driver, a second file comprising the second plurality of rules written in the second rule language. 11. The non-transitory machine-readable medium of claim 9 , wherein the first rule language is a C Library Integrated Production System (CLIPS) language.
| 0.586486 |
8,086,697 | 1 | 5 |
1. A method comprising: (A) receiving, from a client computer, a request for an impression to be displayed in a placement of a web page, the request being made by the client computer as a result of said client computer receiving the web page; (B) receiving from the client computer a placement identifier particularly identifying a placement for the impression in the web page, the placement identifier having been embedded in the web page received at the client computer; (C) receiving behavioral data from the client computer, the behavioral data being indicative of client actions taken on multiple websites previously visited by the client computer and indicative of impressions previously received at the client computer; (D) determining a plurality of candidate impressions that may be displayed in the placement of the web page, based, at least in part, on the behavioral data; (E) determining a learning mode of each impression in the plurality of candidate impressions, the learning mode of each said impression being indicative of a number of times said each impression in the plurality of candidate impressions has been served to web pages in client computers on the Internet, wherein said learning mode is one of a plurality of learning modes, said plurality of learning modes comprising at least a first learning mode, a second learning mode, and a third learning mode, wherein, impressions that have been served less than a first predetermined threshold number of times are in said first learning mode, and wherein impressions that have been served more than said first predetermined number of times and less than a second predetermined threshold number of times are in said second learning mode, and wherein impressions that have been served more than a third predetermined threshold number of times are in a third learning mode, said second predetermined threshold being greater than said first predetermined threshold, and said third predetermined threshold being greater than said second predetermined threshold; (F) selecting a selected impression from the plurality of candidate impressions based at least in part on the learning mode of each of the impressions; and (G) serving the selected impression to the client computer, wherein selecting the selected impression from the plurality of candidate impressions in (F) comprises: (f1) if all impressions in the plurality of candidate impressions are in said first learning mode, then randomly selecting the selected impression from the plurality of candidate impressions; and (f2) if all impressions in the plurality of candidate impressions are in said second learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f3) if all of the impressions in the plurality of candidate impressions are in said third learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f4) if at least some impressions in the plurality of candidate impressions are in different learning modes, then selecting, as a final set of candidate impressions, impressions in the plurality of candidate impressions that are either; (i) all in the first learning mode, or (ii) all in the second learning mode, or (iii) all in the third learning mode, and then selecting the selected impression from the final set of candidate impressions.
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1. A method comprising: (A) receiving, from a client computer, a request for an impression to be displayed in a placement of a web page, the request being made by the client computer as a result of said client computer receiving the web page; (B) receiving from the client computer a placement identifier particularly identifying a placement for the impression in the web page, the placement identifier having been embedded in the web page received at the client computer; (C) receiving behavioral data from the client computer, the behavioral data being indicative of client actions taken on multiple websites previously visited by the client computer and indicative of impressions previously received at the client computer; (D) determining a plurality of candidate impressions that may be displayed in the placement of the web page, based, at least in part, on the behavioral data; (E) determining a learning mode of each impression in the plurality of candidate impressions, the learning mode of each said impression being indicative of a number of times said each impression in the plurality of candidate impressions has been served to web pages in client computers on the Internet, wherein said learning mode is one of a plurality of learning modes, said plurality of learning modes comprising at least a first learning mode, a second learning mode, and a third learning mode, wherein, impressions that have been served less than a first predetermined threshold number of times are in said first learning mode, and wherein impressions that have been served more than said first predetermined number of times and less than a second predetermined threshold number of times are in said second learning mode, and wherein impressions that have been served more than a third predetermined threshold number of times are in a third learning mode, said second predetermined threshold being greater than said first predetermined threshold, and said third predetermined threshold being greater than said second predetermined threshold; (F) selecting a selected impression from the plurality of candidate impressions based at least in part on the learning mode of each of the impressions; and (G) serving the selected impression to the client computer, wherein selecting the selected impression from the plurality of candidate impressions in (F) comprises: (f1) if all impressions in the plurality of candidate impressions are in said first learning mode, then randomly selecting the selected impression from the plurality of candidate impressions; and (f2) if all impressions in the plurality of candidate impressions are in said second learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f3) if all of the impressions in the plurality of candidate impressions are in said third learning mode, then selecting a highest revenue generating impression in the plurality of candidate impressions as the selected impression; and (f4) if at least some impressions in the plurality of candidate impressions are in different learning modes, then selecting, as a final set of candidate impressions, impressions in the plurality of candidate impressions that are either; (i) all in the first learning mode, or (ii) all in the second learning mode, or (iii) all in the third learning mode, and then selecting the selected impression from the final set of candidate impressions. 5. The method of claim 1 wherein each impression in the plurality of candidate impressions comprises a message and an associated creative, the creative being a design of how the message is to be presented to the end-user.
| 0.80477 |
8,371,857 | 1 | 3 |
1. A system for teaching a user pronunciation, comprising: a voice portal arrangement; a communication arrangement adapted to be coupled with the voice portal arrangement; an application server adapted to be coupled with the voice portal arrangement; and a geo-server for determining a location; wherein: the geo-server determines a location of the user and a dominant language and a regional dialect prevailing at the determined location of the user; the voice portal arrangement provides the user a prompt in the determined regional dialect of the dominant language, and compares at least one word spoken by the user in response to the prompt to determine a confidence lever; the at least one word spoken by the user is associated in memory with a plurality of valid pronunciations; and one of the plurality of valid pronunciations used by the user for the at least one word spoken by the user is determined to be incorrect based on the regional dialect.
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1. A system for teaching a user pronunciation, comprising: a voice portal arrangement; a communication arrangement adapted to be coupled with the voice portal arrangement; an application server adapted to be coupled with the voice portal arrangement; and a geo-server for determining a location; wherein: the geo-server determines a location of the user and a dominant language and a regional dialect prevailing at the determined location of the user; the voice portal arrangement provides the user a prompt in the determined regional dialect of the dominant language, and compares at least one word spoken by the user in response to the prompt to determine a confidence lever; the at least one word spoken by the user is associated in memory with a plurality of valid pronunciations; and one of the plurality of valid pronunciations used by the user for the at least one word spoken by the user is determined to be incorrect based on the regional dialect. 3. The system of claim 1 , wherein the communication arrangement is adapted to be coupled with the voice portal server.
| 0.791228 |
9,720,738 | 1 | 7 |
1. A computer-implemented machine learning method for scheduling a computational task by a scheduling entity in a datacenter environment, wherein the datacenter includes a plurality of computing entities and the scheduling entity includes a first and second parameter processing entities, the method comprising: receiving feedback information from the datacenter by the scheduling entity, wherein the feedback information includes: historical selections of the plurality of computing entities for processing historical computing tasks, and historical processing results of the historical computing tasks as processed by the historical computing entities; receiving and processing at the first parameter processing entity incoming data corresponding to a new computational task to be processed by the datacenter environment, wherein the incoming data includes: a set of computational task parameters specifying characteristics of the new computational task, and a set of computational tasks requirements specifying criteria which have to be fulfilled by a computer entity for processing the new computational task; receiving and processing at the second parameter processing entity a first and second set of computing entity parameters; wherein the first set of computing entity parameters specifies characteristics of the computing entities of the plurality of computing entities, and the second set of computing entity parameters specifies load parameters of the plurality of computing entities; providing processing result from the first and second parameter processing entities to machine logic of the scheduling entity; identifying, by a self-learning mechanism of the scheduling entity based on the processing result and the feedback information, features from one or more computing entities among the plurality of computing entities that have similar characteristics to the received set of computing entity parameters in the processing result; creating a contextual model that corresponds to the identified features of the one or more of the computing entities; responsive to detecting changes in the information deriving from the received feedback information, the processing result from the first and second parameter processing entities, and the created contextual model, modifying the set of identified features by increasing or decreasing the effect of one or more parameters; selecting, by machine logic of the scheduling entity, one or more computing entities of the plurality of computing entities for processing the new computational task based, at least in part, upon: the processing result from the first parameter processing entity, the processing result from the second parameter entity, the received feedback information, and the created contextual model; and processing the computational task on the selected one or more computing entities.
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1. A computer-implemented machine learning method for scheduling a computational task by a scheduling entity in a datacenter environment, wherein the datacenter includes a plurality of computing entities and the scheduling entity includes a first and second parameter processing entities, the method comprising: receiving feedback information from the datacenter by the scheduling entity, wherein the feedback information includes: historical selections of the plurality of computing entities for processing historical computing tasks, and historical processing results of the historical computing tasks as processed by the historical computing entities; receiving and processing at the first parameter processing entity incoming data corresponding to a new computational task to be processed by the datacenter environment, wherein the incoming data includes: a set of computational task parameters specifying characteristics of the new computational task, and a set of computational tasks requirements specifying criteria which have to be fulfilled by a computer entity for processing the new computational task; receiving and processing at the second parameter processing entity a first and second set of computing entity parameters; wherein the first set of computing entity parameters specifies characteristics of the computing entities of the plurality of computing entities, and the second set of computing entity parameters specifies load parameters of the plurality of computing entities; providing processing result from the first and second parameter processing entities to machine logic of the scheduling entity; identifying, by a self-learning mechanism of the scheduling entity based on the processing result and the feedback information, features from one or more computing entities among the plurality of computing entities that have similar characteristics to the received set of computing entity parameters in the processing result; creating a contextual model that corresponds to the identified features of the one or more of the computing entities; responsive to detecting changes in the information deriving from the received feedback information, the processing result from the first and second parameter processing entities, and the created contextual model, modifying the set of identified features by increasing or decreasing the effect of one or more parameters; selecting, by machine logic of the scheduling entity, one or more computing entities of the plurality of computing entities for processing the new computational task based, at least in part, upon: the processing result from the first parameter processing entity, the processing result from the second parameter entity, the received feedback information, and the created contextual model; and processing the computational task on the selected one or more computing entities. 7. The method according to claim 1 , wherein the scheduling entity includes a contextual self-learning mechanism capability taking into account feedback information that was derived from processing computational tasks on one or more computing entities with computing entity parameters that are similar to computing entity parameters of a currently selected computing entity.
| 0.677029 |
10,043,521 | 1 | 9 |
1. A computer-implemented method for user dependent key phrase enrollment comprising: receiving, via a microphone, an audio input representing a user defined key phrase and converting the audio input to received audio data representative of the audio input; determining a sequence of most probable audio units corresponding to the received audio data, wherein each audio unit of most probable audio units corresponds to a frame of a plurality of frames of the audio data; processing the sequence of most probable audio units to eliminate at least one audio unit from the sequence of most probable audio units to generate a final sequence of audio units by determining a first silence audio unit of the sequence and a number of silence audio units immediately temporally following the first silence audio unit, wherein the first silence audio unit and the number of silence audio units are between non-silence audio units of the sequence, and eliminating the first silence audio unit and the immediately temporally following silence audio units in response to the total number of consecutive silence audio units not exceeding a threshold; generating a key phrase recognition model representing the user defined key phrase based on the final sequence of audio units, the key phrase recognition model comprising a single start state based rejection model, a key phrase model, and a transition from the single start state based rejection model to the key phrase model, wherein the single start state based rejection model includes a single rejection state having a plurality of rejection model self loops, wherein the key phrase model comprises a plurality of states having transitions therebetween, the plurality of states including a final state of the key phrase model, and wherein the plurality of states of the key phrase model correspond to the final sequence of audio units; receiving a further audio input for evaluation by the key phrase recognition model; generating a time series of scores of audio units based on a time series of feature vectors representative of the further audio input; scoring the key phrase recognition model based on the time series of scores of audio units to generate a rejection likelihood score and a key phrase likelihood score; and recognizing that the further audio input corresponds to the user defined key phrase based on the rejection likelihood score and the key phrase likelihood score.
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1. A computer-implemented method for user dependent key phrase enrollment comprising: receiving, via a microphone, an audio input representing a user defined key phrase and converting the audio input to received audio data representative of the audio input; determining a sequence of most probable audio units corresponding to the received audio data, wherein each audio unit of most probable audio units corresponds to a frame of a plurality of frames of the audio data; processing the sequence of most probable audio units to eliminate at least one audio unit from the sequence of most probable audio units to generate a final sequence of audio units by determining a first silence audio unit of the sequence and a number of silence audio units immediately temporally following the first silence audio unit, wherein the first silence audio unit and the number of silence audio units are between non-silence audio units of the sequence, and eliminating the first silence audio unit and the immediately temporally following silence audio units in response to the total number of consecutive silence audio units not exceeding a threshold; generating a key phrase recognition model representing the user defined key phrase based on the final sequence of audio units, the key phrase recognition model comprising a single start state based rejection model, a key phrase model, and a transition from the single start state based rejection model to the key phrase model, wherein the single start state based rejection model includes a single rejection state having a plurality of rejection model self loops, wherein the key phrase model comprises a plurality of states having transitions therebetween, the plurality of states including a final state of the key phrase model, and wherein the plurality of states of the key phrase model correspond to the final sequence of audio units; receiving a further audio input for evaluation by the key phrase recognition model; generating a time series of scores of audio units based on a time series of feature vectors representative of the further audio input; scoring the key phrase recognition model based on the time series of scores of audio units to generate a rejection likelihood score and a key phrase likelihood score; and recognizing that the further audio input corresponds to the user defined key phrase based on the rejection likelihood score and the key phrase likelihood score. 9. The method of claim 1 , wherein the rejection likelihood score corresponds to the single start state based rejection model, the key phrase likelihood score corresponds to the final state of the key phrase model, and determining whether the further audio input corresponds to the user defined key phrase comprises determining a log likelihood score based on the rejection likelihood score and the key phrase likelihood score and comparing the log likelihood score to a threshold.
| 0.638346 |
10,102,453 | 1 | 14 |
1. A method of machine learning of written natural languages comprising: receiving a string of natural language texts in a first computing system having at least one application module installed thereon; forming, with the at least one application module in the first computing system, a multi-layer two-dimensional (2-D) symbol from the received string of natural language texts based on a set of rules, the 2-D symbol being a matrix of N×N pixels of data that contains a super-character, the matrix being divided into M×M sub-matrices with each of the sub-matrices containing (N/M)×(N/M) pixels, said each of the sub-matrices representing one ideogram defined in an ideogram collection set, and the super-character representing a meaning formed from a specific combination of a plurality of ideograms, where N and M are positive integers, and N is a multiple of M; and learning the meaning of the super-character in a second computing system by using an image processing technique to classify the 2-D symbol, which is formed with the at least one application module in the first computing system and transmitted to the second computing system.
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1. A method of machine learning of written natural languages comprising: receiving a string of natural language texts in a first computing system having at least one application module installed thereon; forming, with the at least one application module in the first computing system, a multi-layer two-dimensional (2-D) symbol from the received string of natural language texts based on a set of rules, the 2-D symbol being a matrix of N×N pixels of data that contains a super-character, the matrix being divided into M×M sub-matrices with each of the sub-matrices containing (N/M)×(N/M) pixels, said each of the sub-matrices representing one ideogram defined in an ideogram collection set, and the super-character representing a meaning formed from a specific combination of a plurality of ideograms, where N and M are positive integers, and N is a multiple of M; and learning the meaning of the super-character in a second computing system by using an image processing technique to classify the 2-D symbol, which is formed with the at least one application module in the first computing system and transmitted to the second computing system. 14. The method of claim 1 , wherein the image processing technique comprises a convolutional neural networks algorithm.
| 0.935326 |
9,743,243 | 1 | 2 |
1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category therefor from publically available information responsive to uncertain mobile device location data; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix.
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1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category therefor from publically available information responsive to uncertain mobile device location data; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. 2. The method of claim 1 , wherein the uncertain mobile device location data comprises cellular telephone location data generated by a cellular telephone locator.
| 0.843931 |
8,417,651 | 9 | 17 |
9. A computer based method of matching a text description to a structured record of a product, the method comprising: obtaining a set of text descriptions and a set of structured records individually containing a plurality of attributes of a product, each of the text descriptions matching one of the structured records; parsing the set of text descriptions to form one or more text segments; associating the text segments of each text description with one or more attributes of the structured records; and deriving a weight factor for at least some of the associated attributes based on matches of the individual text descriptions to one of the structured records, the weight factor representing a relative importance of the corresponding attributes for matching.
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9. A computer based method of matching a text description to a structured record of a product, the method comprising: obtaining a set of text descriptions and a set of structured records individually containing a plurality of attributes of a product, each of the text descriptions matching one of the structured records; parsing the set of text descriptions to form one or more text segments; associating the text segments of each text description with one or more attributes of the structured records; and deriving a weight factor for at least some of the associated attributes based on matches of the individual text descriptions to one of the structured records, the weight factor representing a relative importance of the corresponding attributes for matching. 17. The method of claim 9 wherein each of the attributes is associated with a corresponding value, and wherein deriving a weight factor includes: generating a similarity vector having one or more elements individually representing a similarity of the values of attributes in the text descriptions and those in the corresponding structured records, wherein the one or more elements have binary values or numeric values; and deriving the weight factors of the attributes based at least in part on a binary logistic regression of the similarity vector.
| 0.610638 |
9,384,262 | 3 | 6 |
3. The method of claim 1 , wherein determining the similarity among the corresponding field values of the database records comprises: assigning a hyperspace attribute to each database record, wherein the hyperspace attribute corresponding to two database records is correlated with a similarity of the corresponding field values of the two database records; determining membership of each database record in a plurality of hyperspace clusters based at least in part on the hyperspace attributes; assigning, to each record, a cluster ID and a match value reflecting a likelihood that the record is a member of a particular hyperspace cluster; and linking related records based at least in part on the cluster ID and the match value.
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3. The method of claim 1 , wherein determining the similarity among the corresponding field values of the database records comprises: assigning a hyperspace attribute to each database record, wherein the hyperspace attribute corresponding to two database records is correlated with a similarity of the corresponding field values of the two database records; determining membership of each database record in a plurality of hyperspace clusters based at least in part on the hyperspace attributes; assigning, to each record, a cluster ID and a match value reflecting a likelihood that the record is a member of a particular hyperspace cluster; and linking related records based at least in part on the cluster ID and the match value. 6. The method of claim 3 , wherein the determining membership of each database record in the plurality of hyperspace clusters further comprises creating a plurality of nodes at random locations in hyperspace, each node maintaining records in hyperspace based on the hyperspace attribute for which it is the closest node.
| 0.5 |
8,949,256 | 11 | 12 |
11. The system of claim 10 , wherein utilizing the first potential name and the second potential name to identify the name associated with the web page comprises comparing the first potential name and the second potential name to determine if the first potential name matches the second potential name.
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11. The system of claim 10 , wherein utilizing the first potential name and the second potential name to identify the name associated with the web page comprises comparing the first potential name and the second potential name to determine if the first potential name matches the second potential name. 12. The system of claim 11 , wherein if the first potential name and the second potential name match, the name associated with the web page is determined to be the first potential name.
| 0.5 |
8,812,505 | 1 | 3 |
1. An information recommending method with a computer using a database storing multiple classification words displayed as a tag or a category in a web site, one or more words related to each of the multiple classification words, and a numerical value of the relationship of one or more words with the classification word in association with each other, wherein the tag is text information displayed on the web page as which is representing the gist of a word group included in sentences of the web site, the method comprises a step of establishing the database, wherein the step for establishing the database comprises: a web site selecting step in which the computer selects multiple web sites having a certain classification word from web sites connected to the computer via an electronic communication circuit; a word group extracting step in which the computer extracts the word group included in the sentences in the web sites selected in the web site selecting step; a numeric conversion step in which the computer measures, in the web sites selected in the web site selecting step, a frequency of each word included in the word group extracted in the word group extracting step, and performs numerical conversion on a relationship between the certain classification word and each word to determine the numerical value; and a storage step in which the computer stores, to the database, the numerical value obtained in the numeric conversion step for each word included in the word group and each word of the word group included in the sentences of the web sites selected in the web site selecting step in relation to the certain classification word, a first word extracting step of extracting words included in each of multiple web pages; a first classification word extracting step of accessing the database using the words extracted in the first word extracting step, and extracting a classification word from the database, and thereby extracting the classification word related to each of the web pages; a related classification word storing step of storing access information to each of the web pages and the classification word related to each of the web pages extracted in the first classification word extracting step in association with each other; a second word extracting step of extracting words used for a search of the Internet by a certain client or words included in web pages viewed by the certain client; a second classification word extracting step of accessing the database using the words extracted in the second word extracting step, and extracting a classification word from the database, and thereby extracting the classification word related to each client; a web page selecting step of obtaining a web page having a classification word related to the classification word extracted in the second classification word extracting step using the classification word extracted in the second classification word extracting step and the classification word extracted in the first classification word extracting step; and an access information displaying step of reading out the access information to the web page obtained in the web page selecting step from the access information stored in the related classification word storing step, and displaying the access information read out on the client; therefore, the preference of a user of the client that can be read from the certain client and the web page suitable for the preference can be matched.
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1. An information recommending method with a computer using a database storing multiple classification words displayed as a tag or a category in a web site, one or more words related to each of the multiple classification words, and a numerical value of the relationship of one or more words with the classification word in association with each other, wherein the tag is text information displayed on the web page as which is representing the gist of a word group included in sentences of the web site, the method comprises a step of establishing the database, wherein the step for establishing the database comprises: a web site selecting step in which the computer selects multiple web sites having a certain classification word from web sites connected to the computer via an electronic communication circuit; a word group extracting step in which the computer extracts the word group included in the sentences in the web sites selected in the web site selecting step; a numeric conversion step in which the computer measures, in the web sites selected in the web site selecting step, a frequency of each word included in the word group extracted in the word group extracting step, and performs numerical conversion on a relationship between the certain classification word and each word to determine the numerical value; and a storage step in which the computer stores, to the database, the numerical value obtained in the numeric conversion step for each word included in the word group and each word of the word group included in the sentences of the web sites selected in the web site selecting step in relation to the certain classification word, a first word extracting step of extracting words included in each of multiple web pages; a first classification word extracting step of accessing the database using the words extracted in the first word extracting step, and extracting a classification word from the database, and thereby extracting the classification word related to each of the web pages; a related classification word storing step of storing access information to each of the web pages and the classification word related to each of the web pages extracted in the first classification word extracting step in association with each other; a second word extracting step of extracting words used for a search of the Internet by a certain client or words included in web pages viewed by the certain client; a second classification word extracting step of accessing the database using the words extracted in the second word extracting step, and extracting a classification word from the database, and thereby extracting the classification word related to each client; a web page selecting step of obtaining a web page having a classification word related to the classification word extracted in the second classification word extracting step using the classification word extracted in the second classification word extracting step and the classification word extracted in the first classification word extracting step; and an access information displaying step of reading out the access information to the web page obtained in the web page selecting step from the access information stored in the related classification word storing step, and displaying the access information read out on the client; therefore, the preference of a user of the client that can be read from the certain client and the web page suitable for the preference can be matched. 3. The method accordance with claim 1 , wherein the web site selecting step in which the computer extracts multiple web sites having the certain classification word on the basis of the identification tag allocated to the web site.
| 0.780534 |
5,519,867 | 3 | 4 |
3. The apparatus of claim 1, wherein said object-oriented class library comprises object-oriented task classes for enabling said application to access in an object-oriented manner said services to reference and control a task, said task representing an execution environment for at least one thread of execution associated with said task.
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3. The apparatus of claim 1, wherein said object-oriented class library comprises object-oriented task classes for enabling said application to access in an object-oriented manner said services to reference and control a task, said task representing an execution environment for at least one thread of execution associated with said task. 4. The apparatus of claim 3, wherein said task classes comprise a first task object-oriented class encapsulating attributes and operations of an existing task, said first task class including protected methods to enable run-time specific subclasses of said first task class to spawn new tasks.
| 0.5 |
7,945,904 | 3 | 6 |
3. The one or more computer-readable storage media of claim 2 , wherein the at least one XML literal is a static structure and further comprises at least one of an expression or a statement block that is non-static within the static structure of the at least one XML literal.
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3. The one or more computer-readable storage media of claim 2 , wherein the at least one XML literal is a static structure and further comprises at least one of an expression or a statement block that is non-static within the static structure of the at least one XML literal. 6. The one or more computer-readable storage media of claim 3 , wherein the compilation component comprises a reification component that reifies a compile-time XML declaration as a dynamic run-time value.
| 0.735065 |
8,805,839 | 6 | 12 |
6. The computer-implemented method of claim 1 , wherein each label received from the user identifies a type of access event item associated with the candidate problematic access event item.
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6. The computer-implemented method of claim 1 , wherein each label received from the user identifies a type of access event item associated with the candidate problematic access event item. 12. The computer-implemented method of claim 6 , wherein using feature-based analysis and graph-based analysis comprises using an integrated combination of the feature-based analysis and the graph-based analysis to identify said at least one candidate problematic access event item.
| 0.820153 |
7,954,049 | 15 | 16 |
15. The system of claim 11 wherein the second application is a spreadsheet program.
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15. The system of claim 11 wherein the second application is a spreadsheet program. 16. The system of claim 15 wherein the user action is to modify contents of a spreadsheet cell.
| 0.5 |
8,374,850 | 1 | 7 |
1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed.
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1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. 7. The apparatus according to claim 1 , wherein: said precursor is greater than one word in length, and the apparatus is further caused to, in response to the selection of a candidate word: cause the precursor to be updated by causing the selected candidate word to be appended to the end of the precursor and causing the leading word to be deleted, select a new list of candidate words whose index matches the updated precursor, and cause m-number or less of candidate words from the new list of candidate words to be displayed.
| 0.5 |
8,713,049 | 5 | 7 |
5. The method of providing parameterized queries in CEP as in claim 4 , wherein the providing of the sets of parameters corresponding to the one or more bind variables is performed statically by using a config file at deployment time of the query template.
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5. The method of providing parameterized queries in CEP as in claim 4 , wherein the providing of the sets of parameters corresponding to the one or more bind variables is performed statically by using a config file at deployment time of the query template. 7. The method of providing parameterized queries in CEP as in claim 5 , wherein the config file includes at least one or more of the following: application association, processor association, query rules, the query template, the sets of parameters, or the bindings.
| 0.5 |
9,740,750 | 11 | 18 |
11. A system comprising: a processor; and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the search query data for the search query, and adjusting the point value associated with one or more of the winning score improvement list or the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing.
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11. A system comprising: a processor; and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the search query data for the search query, and adjusting the point value associated with one or more of the winning score improvement list or the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing. 18. The system of claim 11 , wherein the search query data includes user selection data associated with search results for the search query.
| 0.908735 |
8,620,911 | 1 | 4 |
1. A document registry system ( 10 ), comprising: a registry database ( 20 ), including: a specific task sub-database ( 22 ), including: pre-existing fields configured to store specific task-related document data received from one or more of a plurality of sources (S 1 , S 2 , S 3 , S 4 or from a source other than the plurality of sources (NS 1 , NS 2 ); and de novo fields configured to be generated as a result of a general task query and configured to store specific task-related document data received from the source other than the plurality of sources (NS 1 , NS 2 ); an analytics-supporting general task sub-database ( 24 ), including: pre-existing fields configured to store general task-related document data received from one or more of the plurality of sources (S 1 , S 2 , S 3 , S 4 ) or at least a second source other than the plurality of sources (NS 1 , NS 2 ): and de novo fields configured to be generated as a result of a general task query and configured to store general task-related document data received from the source or the second source other than the plurality of sources (NS 1 NS 2 ); and a query mapping engine ( 26 ) configured to receive a request entry, map the request entry into a query, and actively collect data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the source or the it least a second source other than the plurality of sources (NS 1 , NS 2 ).
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1. A document registry system ( 10 ), comprising: a registry database ( 20 ), including: a specific task sub-database ( 22 ), including: pre-existing fields configured to store specific task-related document data received from one or more of a plurality of sources (S 1 , S 2 , S 3 , S 4 or from a source other than the plurality of sources (NS 1 , NS 2 ); and de novo fields configured to be generated as a result of a general task query and configured to store specific task-related document data received from the source other than the plurality of sources (NS 1 , NS 2 ); an analytics-supporting general task sub-database ( 24 ), including: pre-existing fields configured to store general task-related document data received from one or more of the plurality of sources (S 1 , S 2 , S 3 , S 4 ) or at least a second source other than the plurality of sources (NS 1 , NS 2 ): and de novo fields configured to be generated as a result of a general task query and configured to store general task-related document data received from the source or the second source other than the plurality of sources (NS 1 NS 2 ); and a query mapping engine ( 26 ) configured to receive a request entry, map the request entry into a query, and actively collect data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the source or the it least a second source other than the plurality of sources (NS 1 , NS 2 ). 4. The document registry system ( 10 ) as defined in claim 1 , further comprising: a computing device ( 14 ) configured to transmit the request entry; and a cloud computing network ( 12 ) configured to be accessible by the computing device ( 14 ) and configured to provide an access point ( 34 ) into a workflow management system ( 18 ) include the query mapping engine ( 26 ).
| 0.555425 |
9,996,556 | 7 | 9 |
7. The computer-implemented method of claim 1 , further comprising performing a second image process on a second object included in said image based, at least in part, on a selection of said second object.
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7. The computer-implemented method of claim 1 , further comprising performing a second image process on a second object included in said image based, at least in part, on a selection of said second object. 9. The computer-implemented method of claim 7 , wherein performing said second image process is further based, at least in part, on historical selection data associated with said second object.
| 0.5 |
9,483,519 | 1 | 5 |
1. A method, in a data processing system comprising a processor and a memory, for processing a corpus of information in a natural language processing system, the method comprising: identifying, by the data processing system, a corpus of information to process; retrieving, by the data processing system, a set of author profiles associated with the corpus of information; presenting, by the data processing system, a user interface that comprises the set of author profiles, through which a user input is received specifying a user selection of at least one user selected author profile in the set of author profiles; generating, by the data processing system, a content profile for a portion of content of the corpus of information; comparing, by the data processing system, the content profile to the set of author profiles to generate an association of the content profile with at least one author profile in the set of author profiles; and controlling a processing operation of the natural language processing (NLP) system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, wherein the processing operation is an ingestion operation that ingests portions of content from the corpus of information, wherein controlling the processing operation of the NLP system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, comprises: ingesting first content, associated with a first user selected author profile having an associated first user specified priority value associated with the first user selected author profile, from the corpus into the NLP system and performing an NLP operation on the first content; and ingesting second content, associated with a second user selected author profile having an associated second user specified priority value associated with the second user selected author profile, after ingesting the first content and performing the NLP operation on the first content, and performing the NLP operation on the second content, wherein the first user specified priority value indicates a higher priority associated with the first user selected author profile than the second user specified priority value.
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1. A method, in a data processing system comprising a processor and a memory, for processing a corpus of information in a natural language processing system, the method comprising: identifying, by the data processing system, a corpus of information to process; retrieving, by the data processing system, a set of author profiles associated with the corpus of information; presenting, by the data processing system, a user interface that comprises the set of author profiles, through which a user input is received specifying a user selection of at least one user selected author profile in the set of author profiles; generating, by the data processing system, a content profile for a portion of content of the corpus of information; comparing, by the data processing system, the content profile to the set of author profiles to generate an association of the content profile with at least one author profile in the set of author profiles; and controlling a processing operation of the natural language processing (NLP) system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, wherein the processing operation is an ingestion operation that ingests portions of content from the corpus of information, wherein controlling the processing operation of the NLP system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, comprises: ingesting first content, associated with a first user selected author profile having an associated first user specified priority value associated with the first user selected author profile, from the corpus into the NLP system and performing an NLP operation on the first content; and ingesting second content, associated with a second user selected author profile having an associated second user specified priority value associated with the second user selected author profile, after ingesting the first content and performing the NLP operation on the first content, and performing the NLP operation on the second content, wherein the first user specified priority value indicates a higher priority associated with the first user selected author profile than the second user specified priority value. 5. The method of claim 1 , wherein each author profile in the set of author profiles specifies characteristics of either a particular individual author or a group of authors having at least one common characteristic.
| 0.862069 |
8,713,054 | 65 | 80 |
65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document.
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65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. 80. The system of claim 65 , wherein said electronic document security regimen further comprising at least one unique code that is associated with said at least one criterion, and wherein said at least one software engine further comprising embed said at least one unique code into said electronic document, where said at least one unique code is associated with said classification mark.
| 0.61811 |
9,047,267 | 1 | 2 |
1. A method comprising: receiving written input, the written input being representative of a mathematical expression; analyzing the written input to identify at least one operator and at least one operand; constructing, via a processor, an expression tree based at least in part on predefined symbol relationships, the at least one operator, and the at least one operand; wherein constructing the expression tree includes inserting, based at least in part on the predefined symbol relationships, a placeholder within the expression tree for a missing operator, a missing operand, or a missing parenthesis and wherein the placeholder separately identifies whether the placeholder is for a missing operator, a missing operand, or a missing parenthesis; analyzing the expression tree to identify an error based at least in part on one or more predefined rules; and providing for display of a feedback message corresponding to the error, wherein the feedback message may include a suggestion for correcting the error.
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1. A method comprising: receiving written input, the written input being representative of a mathematical expression; analyzing the written input to identify at least one operator and at least one operand; constructing, via a processor, an expression tree based at least in part on predefined symbol relationships, the at least one operator, and the at least one operand; wherein constructing the expression tree includes inserting, based at least in part on the predefined symbol relationships, a placeholder within the expression tree for a missing operator, a missing operand, or a missing parenthesis and wherein the placeholder separately identifies whether the placeholder is for a missing operator, a missing operand, or a missing parenthesis; analyzing the expression tree to identify an error based at least in part on one or more predefined rules; and providing for display of a feedback message corresponding to the error, wherein the feedback message may include a suggestion for correcting the error. 2. The method of claim 1 , wherein receiving the written input includes receiving the written input via a touch screen display.
| 0.809309 |
7,984,035 | 1 | 2 |
1. A system comprising: a computer readable storage medium having computer readable instructions stored thereon that are operable by one or more system components, the one or more system components comprising: a context analyzer component that establishes context of each of a plurality of documents, wherein the context analyzer component includes an image analyzer that employs facial recognition to establish the context; a search engine component that identifies a plurality of search results based upon the context of each of the plurality of documents in view of a search query; and a category association component that maps each context to a category and ranks each context within the category, the category being determined by mining a plurality of search queries submitted.
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1. A system comprising: a computer readable storage medium having computer readable instructions stored thereon that are operable by one or more system components, the one or more system components comprising: a context analyzer component that establishes context of each of a plurality of documents, wherein the context analyzer component includes an image analyzer that employs facial recognition to establish the context; a search engine component that identifies a plurality of search results based upon the context of each of the plurality of documents in view of a search query; and a category association component that maps each context to a category and ranks each context within the category, the category being determined by mining a plurality of search queries submitted. 2. The system of claim 1 , wherein the context analyzer component employs word patterns within a document to establish the context.
| 0.763538 |
9,811,728 | 1 | 12 |
1. A computer implemented method of identifying a document, the method comprising: obtaining document context data for one or more documents, wherein the document context data includes supplemental information used to identify the document and includes temporal information for one or more previous scans of portions of the one or more documents, the temporal information specifying a time at which each previous scan occurred; receiving data specifying a portion of the document captured using a handheld capture device; identifying a digital document associated with the document using the document context data including the temporal information and the captured portion of the document; identifying, using the captured portion of the document, a location of the captured portion within the digital document; identifying a location-based action to be performed based on the identified location of the captured portion and data specifying one or more location-based actions associated with one or more locations within the digital document; and performing the identified location-based action.
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1. A computer implemented method of identifying a document, the method comprising: obtaining document context data for one or more documents, wherein the document context data includes supplemental information used to identify the document and includes temporal information for one or more previous scans of portions of the one or more documents, the temporal information specifying a time at which each previous scan occurred; receiving data specifying a portion of the document captured using a handheld capture device; identifying a digital document associated with the document using the document context data including the temporal information and the captured portion of the document; identifying, using the captured portion of the document, a location of the captured portion within the digital document; identifying a location-based action to be performed based on the identified location of the captured portion and data specifying one or more location-based actions associated with one or more locations within the digital document; and performing the identified location-based action. 12. The method of claim 1 , wherein identifying a digital document comprises: identifying a plurality of digital documents; and identifying the digital document from among the plurality of identified digital documents.
| 0.609319 |
9,552,807 | 1 | 8 |
1. A system for automatically dubbing a video in a first language into a second language, comprising: an audio/video pre-processor constructed and arranged to provide separate original audio and video files of the same media; a text analysis unit constructed and arranged to receive a first text file of the video's subtitles in the first language and a second text file of the video's subtitles in the second language, said text analysis unit further constructed and arranged to re-divide said first and second text files into text sentences; a text-to-speech unit constructed and arranged to receive said text sentences in said first and second languages from said text analysis unit and produce therefrom first and second standard TTS spoken sentences; a prosody unit constructed and arranged to receive said first and second spoken sentences, said separated audio file and timing parameters and produce therefrom dubbing recommendations; and a dubbing unit constructed and arranged to receive said second spoken sentence and said recommendations and produce therefrom an automatically dubbed sentence in said second language.
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1. A system for automatically dubbing a video in a first language into a second language, comprising: an audio/video pre-processor constructed and arranged to provide separate original audio and video files of the same media; a text analysis unit constructed and arranged to receive a first text file of the video's subtitles in the first language and a second text file of the video's subtitles in the second language, said text analysis unit further constructed and arranged to re-divide said first and second text files into text sentences; a text-to-speech unit constructed and arranged to receive said text sentences in said first and second languages from said text analysis unit and produce therefrom first and second standard TTS spoken sentences; a prosody unit constructed and arranged to receive said first and second spoken sentences, said separated audio file and timing parameters and produce therefrom dubbing recommendations; and a dubbing unit constructed and arranged to receive said second spoken sentence and said recommendations and produce therefrom an automatically dubbed sentence in said second language. 8. The system of claim 1 , further comprising a translation unit constructed and arranged to provide said second language text sentences.
| 0.698238 |
9,990,432 | 12 | 16 |
12. A system, comprising a server computer communicatively coupled to a network and comprising at least one processor executing computer-executable instructions within a memory that, when executed, cause the system to: receive, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenize the domain name search string; identify a search string token within the domain name search string as a concept seed; execute a first database command to create a data record storing the search string token in association with a concept id; execute a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenize at least one domain name text string within the domain name search log or the at least one DNS zone file; identify, within the at least one domain name text string, at least one synonym or translation of the search string token; execute a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identify, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generate a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmit the second GUI to the client computer for display.
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12. A system, comprising a server computer communicatively coupled to a network and comprising at least one processor executing computer-executable instructions within a memory that, when executed, cause the system to: receive, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenize the domain name search string; identify a search string token within the domain name search string as a concept seed; execute a first database command to create a data record storing the search string token in association with a concept id; execute a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenize at least one domain name text string within the domain name search log or the at least one DNS zone file; identify, within the at least one domain name text string, at least one synonym or translation of the search string token; execute a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identify, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generate a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmit the second GUI to the client computer for display. 16. The system of claim 12 , wherein the server computer is further configured to: run a relatedness calculation; generate a relatedness dictionary from the relatedness calculation; and rank the at least one available domain name according to the relatedness dictionary.
| 0.632153 |
7,774,699 | 1 | 3 |
1. A method of transforming data from a first hierarchical data structure into a second hierarchical data structure, comprising: determining which segments within the first hierarchal data structure are separable by determining segments which are not referenced by another segment; separating the determined separable segments from the first hierarchical data structure into individual segments; transforming each individual segment, wherein the transforming of a set of one or more segments that comprise a portion of the first hierarchical data structure is done independently from transforming another set, and wherein the transforming is defined by a transformation file; analyzing the transformation file to determine one or more sets of repeated transformations that are separable; analyzing the first hierarchical data structure to estimate which set of the separable transformations will utilize the most computing resources, wherein the analyzing comprises counting the data elements and their descendants accessed within a set of transformations, and wherein the number of segments is based upon the number of data elements and their descendants; in response to the number of data elements and their descendants in a set of the separable transformations providing a beneficial reduction in the use of the computing resources, segmenting the set of the separable transformations; and combining the separable transformed segments to form the second hierarchical data structure, by parsing each segment separately until all segments have been parsed.
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1. A method of transforming data from a first hierarchical data structure into a second hierarchical data structure, comprising: determining which segments within the first hierarchal data structure are separable by determining segments which are not referenced by another segment; separating the determined separable segments from the first hierarchical data structure into individual segments; transforming each individual segment, wherein the transforming of a set of one or more segments that comprise a portion of the first hierarchical data structure is done independently from transforming another set, and wherein the transforming is defined by a transformation file; analyzing the transformation file to determine one or more sets of repeated transformations that are separable; analyzing the first hierarchical data structure to estimate which set of the separable transformations will utilize the most computing resources, wherein the analyzing comprises counting the data elements and their descendants accessed within a set of transformations, and wherein the number of segments is based upon the number of data elements and their descendants; in response to the number of data elements and their descendants in a set of the separable transformations providing a beneficial reduction in the use of the computing resources, segmenting the set of the separable transformations; and combining the separable transformed segments to form the second hierarchical data structure, by parsing each segment separately until all segments have been parsed. 3. The method of claim 1 , wherein each segment uniquely contains a first data element that is a sibling of a second data element uniquely contained within another segment.
| 0.627706 |
4,427,848 | 3 | 4 |
3. The system of claim 1, wherein said system further includes means, responsive to said memory means output signals, for generating audible feedback signals to said telephone set, indicative of said symbol code transmitted to said computer.
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3. The system of claim 1, wherein said system further includes means, responsive to said memory means output signals, for generating audible feedback signals to said telephone set, indicative of said symbol code transmitted to said computer. 4. The system of claim 3 wherein said audible feedback signals constitute a synthesized speech signal corresponding to said symbol.
| 0.5 |
8,516,458 | 34 | 35 |
34. A code-portion-handling tool as claimed in claim 32 , wherein: said candidate code portion is a code portion expressed in said computer-programming language; and the at least one processor is operable to output the candidate code portion before or after such manipulation as object code.
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34. A code-portion-handling tool as claimed in claim 32 , wherein: said candidate code portion is a code portion expressed in said computer-programming language; and the at least one processor is operable to output the candidate code portion before or after such manipulation as object code. 35. A code-portion-handling tool as claimed in claim 34 , the at least one processor being configured as one of a parser and a compiler.
| 0.5 |
8,499,283 | 14 | 15 |
14. A non-transitory, tangible computer readable storage medium, encoded with processor readable instructions to perform a method for protecting client computers, the method comprising: receiving webpage data at a proxy from a webpage before the data reaches an intended recipient, wherein the proxy is disposed as an intermediary between a server serving up the webpage and the intended recipient; gathering scripting-language-data from the webpage data; generating a parse tree from the gathered scripting-language-data; identifying characteristics of the scripting-language-data; scoring the characteristics of the scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language-data; normalizing string-splitting constructs to reduce a level of string splitting in the parse tree; replacing variable names of the parse tree with standard names; generating a representation of at least a portion of the standard names; comparing the representation with signatures of known scripting language exploits; and determining whether to prevent the scripting-language-data from reaching the intended recipient based upon one or more of: (i) a score of characteristics of a normalized scripting-language-data; (ii) a score of characteristics of inspection data based on the scripting-language-data; and (iii) when the representation matches a signature of the one of the known scripting language exploits.
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14. A non-transitory, tangible computer readable storage medium, encoded with processor readable instructions to perform a method for protecting client computers, the method comprising: receiving webpage data at a proxy from a webpage before the data reaches an intended recipient, wherein the proxy is disposed as an intermediary between a server serving up the webpage and the intended recipient; gathering scripting-language-data from the webpage data; generating a parse tree from the gathered scripting-language-data; identifying characteristics of the scripting-language-data; scoring the characteristics of the scripting-language-data based upon a likelihood that the characteristics of the scripting-language-data are associated with malicious scripting-language-data; normalizing string-splitting constructs to reduce a level of string splitting in the parse tree; replacing variable names of the parse tree with standard names; generating a representation of at least a portion of the standard names; comparing the representation with signatures of known scripting language exploits; and determining whether to prevent the scripting-language-data from reaching the intended recipient based upon one or more of: (i) a score of characteristics of a normalized scripting-language-data; (ii) a score of characteristics of inspection data based on the scripting-language-data; and (iii) when the representation matches a signature of the one of the known scripting language exploits. 15. The non-transitory, tangible computer readable storage medium of claim 14 , wherein the representation is a hash of at least a portion of the standard names.
| 0.861684 |
8,250,465 | 1 | 9 |
1. An information processing apparatus for encoding a structured document into an encoded document, comprising: at least one processor operable to function as: a storage unit that stores, into an encoding table, a portion of a schema describing an object included in the structured document as a vocabulary together with a first code, the portion of the schema defining at least a plurality of data types for a plurality of variables; a verification unit that compares a grammar of a part of the structured document to a grammar of the portion of the schema in the encoding table and verifies that the grammar of the part of the structured document matches the grammar of the portion of the schema in the encoding table; and an encoding unit that encodes the structured document by assigning the first code for the part of the structured document and by assigning a second code for a plurality of variables associated with the part of the structured document according to the plurality of data types.
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1. An information processing apparatus for encoding a structured document into an encoded document, comprising: at least one processor operable to function as: a storage unit that stores, into an encoding table, a portion of a schema describing an object included in the structured document as a vocabulary together with a first code, the portion of the schema defining at least a plurality of data types for a plurality of variables; a verification unit that compares a grammar of a part of the structured document to a grammar of the portion of the schema in the encoding table and verifies that the grammar of the part of the structured document matches the grammar of the portion of the schema in the encoding table; and an encoding unit that encodes the structured document by assigning the first code for the part of the structured document and by assigning a second code for a plurality of variables associated with the part of the structured document according to the plurality of data types. 9. The information processing apparatus according to claim 1 , wherein the encoding unit encodes the structured document (i) by assigning the first code for the part of the structured document, (ii) by assigning the second code for the variables associated with the part of the structured document, (iii) by assigning a third code for a start of the part of the structured document, and (iv) by assigning a forth code for an end of the part of the structured document.
| 0.721097 |
9,043,367 | 1 | 7 |
1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form.
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1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form. 7. The method as set forth in claim 1 , wherein said step of first identifying comprises applying logic to parse said input string into cognizable units and selecting one or more of said units as said source term.
| 0.595057 |
7,571,386 | 1 | 10 |
1. A recording medium storing a data structure for managing reproduction of data by a reproducing device, the data structure comprising: at least one audio/video (AV) stream file and at least one text subtitle stream file, each text subtitle stream file including a style segment and at least one presentation segment associated with the style segment and the AV stream file including at least one of audio data and video data, the style segment including at least one set of style information, each set of style information providing region positioning information for positioning a region in an image, text box positioning information for positioning a text box in the region, and text flow information indicating a character progression of text string data, and the presentation segment including at least one region subtitle information, the region subtitle information including text subtitle data and a region style identifier; and at least one clip information file containing attribute information and timing information of a corresponding stream file, wherein the at least one clip information file is separate from the AV stream file and the text subtitle stream file, one of the at least one clip information file has one to one correspondence with the AV stream file, and another clip information file has one to one correspondence with the text subtitle stream file, the text subtitle stream file exists as a separate file from the AV stream file, and the text subtitle data includes at least one of text string data and style data, and the region style identifier identifies one of the sets of style information in the style segment to apply to the text string data such that the text string data appears in the text box in which the identified set of style information is applied.
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1. A recording medium storing a data structure for managing reproduction of data by a reproducing device, the data structure comprising: at least one audio/video (AV) stream file and at least one text subtitle stream file, each text subtitle stream file including a style segment and at least one presentation segment associated with the style segment and the AV stream file including at least one of audio data and video data, the style segment including at least one set of style information, each set of style information providing region positioning information for positioning a region in an image, text box positioning information for positioning a text box in the region, and text flow information indicating a character progression of text string data, and the presentation segment including at least one region subtitle information, the region subtitle information including text subtitle data and a region style identifier; and at least one clip information file containing attribute information and timing information of a corresponding stream file, wherein the at least one clip information file is separate from the AV stream file and the text subtitle stream file, one of the at least one clip information file has one to one correspondence with the AV stream file, and another clip information file has one to one correspondence with the text subtitle stream file, the text subtitle stream file exists as a separate file from the AV stream file, and the text subtitle data includes at least one of text string data and style data, and the region style identifier identifies one of the sets of style information in the style segment to apply to the text string data such that the text string data appears in the text box in which the identified set of style information is applied. 10. The recording medium of claim 1 , wherein each set of style information further includes text box size information indicating a size of the text box, the text box size information including height information indicating a height of the text box and width information indicating a width of the text box.
| 0.853589 |
7,823,117 | 13 | 14 |
13. The article of manufacture of claim 12 , wherein the selecting the subset of functional elements comprises: adding to the subset a functional element having a largest execution count and responsive to the execution count being greater than a threshold value; for each functional element not in the subset, adding the functional element to the subset in response to determining that the functional element provides input data to a functional element already in the subset and the functional element not in the subset having an execution count that is greater than the threshold value; and for each functional element not in the subset, adding the functional element to the subset in response to determining that the functional element receives output from a functional element already in the subset and the functional element not in the subset having an execution count that is greater than the threshold value.
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13. The article of manufacture of claim 12 , wherein the selecting the subset of functional elements comprises: adding to the subset a functional element having a largest execution count and responsive to the execution count being greater than a threshold value; for each functional element not in the subset, adding the functional element to the subset in response to determining that the functional element provides input data to a functional element already in the subset and the functional element not in the subset having an execution count that is greater than the threshold value; and for each functional element not in the subset, adding the functional element to the subset in response to determining that the functional element receives output from a functional element already in the subset and the functional element not in the subset having an execution count that is greater than the threshold value. 14. The article of manufacture of claim 13 , wherein the selecting the subset of functional elements comprises: determining a first quantity of the programmable resources required to implement the functions of the subset of functional elements; comparing the first quantity to a second quantity of the programmable resources available to implement the functions of the subset of functional elements; and wherein the generating, removing, and configuring are responsive to the second quantity being greater than the first quantity.
| 0.587869 |
9,122,667 | 11 | 13 |
11. The system according to claim 5 , wherein the one or more computers generate a request to receive information enabling at least the second determination to be made, the received information being validly received in response to the request.
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11. The system according to claim 5 , wherein the one or more computers generate a request to receive information enabling at least the second determination to be made, the received information being validly received in response to the request. 13. The system according to claim 11 , wherein the generated request is a database query.
| 0.679856 |
9,922,033 | 1 | 11 |
1. A computer-implemented method for efficiently extracting contents of container files, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving, at a first stage of a file-archiving system, an unnested container file containing a first constituent file and a second constituent file, wherein: the first constituent file is a nested container file that contains the second constituent file; and the file-archiving system is configured to perform a time-consuming file-indexing operation; enabling high file throughput at the first stage of the file-archiving system by refraining, at the first stage of the file-archiving system, from performing the time-consuming file-indexing operation; enabling a second stage of the file-archiving system to perform the time-consuming file-indexing operation on the second constituent file by creating, at the first stage of the file-archiving system, a content hierarchy for the unnested container file that comprises: metadata of the second constituent file; first hierarchical metadata that indicates that the unnested container file contains the nested container file; and second hierarchical metadata that indicates that the nested container file contains the second constituent file; using, at the second stage of the file-archiving system, the content hierarchy to locate the second constituent file within the nested container file; extracting, at the second stage of the file-archiving system, the second constituent file from the nested container file; performing, at the second stage of the file-archiving system, the time-consuming file-indexing operation on the second constituent file.
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1. A computer-implemented method for efficiently extracting contents of container files, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving, at a first stage of a file-archiving system, an unnested container file containing a first constituent file and a second constituent file, wherein: the first constituent file is a nested container file that contains the second constituent file; and the file-archiving system is configured to perform a time-consuming file-indexing operation; enabling high file throughput at the first stage of the file-archiving system by refraining, at the first stage of the file-archiving system, from performing the time-consuming file-indexing operation; enabling a second stage of the file-archiving system to perform the time-consuming file-indexing operation on the second constituent file by creating, at the first stage of the file-archiving system, a content hierarchy for the unnested container file that comprises: metadata of the second constituent file; first hierarchical metadata that indicates that the unnested container file contains the nested container file; and second hierarchical metadata that indicates that the nested container file contains the second constituent file; using, at the second stage of the file-archiving system, the content hierarchy to locate the second constituent file within the nested container file; extracting, at the second stage of the file-archiving system, the second constituent file from the nested container file; performing, at the second stage of the file-archiving system, the time-consuming file-indexing operation on the second constituent file. 11. The computer-implemented method of claim 1 , wherein: the unnested container file comprises a third constituent file; the step of extracting the second constituent file from the nested container file is performed without extracting the third constituent file from the unnested container file.
| 0.738516 |
8,745,725 | 1 | 21 |
1. A system comprising: a transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the transfer determining module including at least: a visual cue detecting module configured to determine that the computing device has been transferred from the first user to the second user when the visual cue detecting module at least detects presence or absence of one or more visual cues in proximate vicinity of the computing device that when detected as occurring at least suggested transfer of the computing device between the first and second users, the visual cue detecting module including at least: a gesture detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the gesture detecting module at least detects visually one or more gestures exhibited by the first user that when detected as occurring at least suggested transfer of the computing device from the first user to the second user at least in part by the first user moving the computing device at least in part with the one or more gestures; and a highlighted portion presenting module configured to present, via the computing device, one or more highlighted portions of the item, the highlighted portion presenting module being responsive at least in part to the transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the highlighted portion presenting module being configured to present the one or more highlighted portions of the item responsive at least in part to the transfer determining module and to a highlighting selection detecting module, the highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions to select the one or more portions for highlighting.
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1. A system comprising: a transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the transfer determining module including at least: a visual cue detecting module configured to determine that the computing device has been transferred from the first user to the second user when the visual cue detecting module at least detects presence or absence of one or more visual cues in proximate vicinity of the computing device that when detected as occurring at least suggested transfer of the computing device between the first and second users, the visual cue detecting module including at least: a gesture detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the gesture detecting module at least detects visually one or more gestures exhibited by the first user that when detected as occurring at least suggested transfer of the computing device from the first user to the second user at least in part by the first user moving the computing device at least in part with the one or more gestures; and a highlighted portion presenting module configured to present, via the computing device, one or more highlighted portions of the item, the highlighted portion presenting module being responsive at least in part to the transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the highlighted portion presenting module being configured to present the one or more highlighted portions of the item responsive at least in part to the transfer determining module and to a highlighting selection detecting module, the highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions to select the one or more portions for highlighting. 21. The system of claim 1 , wherein said visual cue detecting module including at least a gesture detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the gesture detecting module at least detects visually one or more gestures exhibited by the first user that when detected as occurring at least suggested transfer of the computing device from the first user to the second user at least in part by the first user moving the computing device at least in part with the one or more gestures comprises: a face detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the face detecting module at least detects presence of a first face associated with the first user and a second face associated with the second user in the proximate vicinity of the computing device, the second face being detected as being closer to the computing device than the first face.
| 0.689552 |
8,626,588 | 30 | 31 |
30. A computer-implemented method comprising: a) accepting, with an advertising system including at least one computer, relevance information for an audio document; b) determining, with the advertising system, a plurality of advertisements relevant to the audio document using the relevance information and serving constraints of the advertisements; c) selecting, with the advertising system, at least one of the determined relevant advertisements to be served with the audio document; d) transmitting, with the advertising system, the audio document for delivery to an end user client device; and e) transmitting, with the advertising system, the selected at least one of the determined relevant advertisements for delivery to the end user client device, wherein the act of selecting occurs after the act of transmitting the audio document has been completed and a play operation has been initiated on the audio document.
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30. A computer-implemented method comprising: a) accepting, with an advertising system including at least one computer, relevance information for an audio document; b) determining, with the advertising system, a plurality of advertisements relevant to the audio document using the relevance information and serving constraints of the advertisements; c) selecting, with the advertising system, at least one of the determined relevant advertisements to be served with the audio document; d) transmitting, with the advertising system, the audio document for delivery to an end user client device; and e) transmitting, with the advertising system, the selected at least one of the determined relevant advertisements for delivery to the end user client device, wherein the act of selecting occurs after the act of transmitting the audio document has been completed and a play operation has been initiated on the audio document. 31. The computer-implemented method of claim 30 , wherein the act of selecting includes: i) accepting offers to have advertisements served in the at least one ad spot, and ii) arbitrating among competing advertisements, using at least the offers, to select at least one advertisement to be served in that at least one ad spot.
| 0.51632 |
7,765,477 | 19 | 29 |
19. A computer program product, embodied on a machine-readable storage device, for searching an electronic document that includes a non-coded representation of characters of text, the computer program product including instructions operable to cause data processing apparatus to: receive text coding information identifying each of a plurality of characters of text represented by the non-coded representation; based on the text coding information, generate a coded representation that: specifies, for each of the plurality of characters of text represented by the non-coded representation, a respective code value based on a character encoding, the code value selected to represent the respective character of text, and associates a particular glyph from a collection of glyphs with each of the code values specified for the plurality of characters of text, the particular glyph selected independently of any relation to the respective character of text, the collection of glyphs being insufficient to semantically represent the plurality of characters of text; associate the coded representation with the non-coded representation, wherein a code value of one of the plurality of characters of text is associated with one or more positions in a visual representation of the non-coded representation; displaying the visual representation of the non-coded representation; searching the coded representation to find a coded character sequence that includes one or more characters at a location in the coded representation; and highlighting, in the displayed visual representation of the non-coded representation, the portion of the non-coded visual representation associated with the coded character sequence at the location in the coded representation.
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19. A computer program product, embodied on a machine-readable storage device, for searching an electronic document that includes a non-coded representation of characters of text, the computer program product including instructions operable to cause data processing apparatus to: receive text coding information identifying each of a plurality of characters of text represented by the non-coded representation; based on the text coding information, generate a coded representation that: specifies, for each of the plurality of characters of text represented by the non-coded representation, a respective code value based on a character encoding, the code value selected to represent the respective character of text, and associates a particular glyph from a collection of glyphs with each of the code values specified for the plurality of characters of text, the particular glyph selected independently of any relation to the respective character of text, the collection of glyphs being insufficient to semantically represent the plurality of characters of text; associate the coded representation with the non-coded representation, wherein a code value of one of the plurality of characters of text is associated with one or more positions in a visual representation of the non-coded representation; displaying the visual representation of the non-coded representation; searching the coded representation to find a coded character sequence that includes one or more characters at a location in the coded representation; and highlighting, in the displayed visual representation of the non-coded representation, the portion of the non-coded visual representation associated with the coded character sequence at the location in the coded representation. 29. The computer program product of claim 19 , further comprising instructions operable to cause data processing apparatus to: store the coded representation and the non-coded representation in a single document.
| 0.746411 |
6,131,091 | 11 | 13 |
11. A method for evaluation of data relevance, comprising: (a) evaluating a document for relevance with regard to a list of specified topics; (b) using the relevance determination to create a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; and (c) transmitting the topic-evaluation vector.
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11. A method for evaluation of data relevance, comprising: (a) evaluating a document for relevance with regard to a list of specified topics; (b) using the relevance determination to create a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; and (c) transmitting the topic-evaluation vector. 13. The method of claim 11, further comprising: (e) receiving a topic dictionary, wherein the topic dictionary comprises information regarding where in the topic-evaluation vector certain topics are located; and (f) transmitting the topic dictionary.
| 0.5 |
8,412,566 | 10 | 11 |
10. The method of claim 9 , wherein said marketing strategy includes at least one targeting product grouping and a promoted product grouping linked to said at least one targeting product grouping; and said promotional offers are distributed only to customers having a high probability of acceptance from said at least one targeting product grouping.
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10. The method of claim 9 , wherein said marketing strategy includes at least one targeting product grouping and a promoted product grouping linked to said at least one targeting product grouping; and said promotional offers are distributed only to customers having a high probability of acceptance from said at least one targeting product grouping. 11. The method of claim 10 , further comprising: providing a taxonomy of said product groupings; wherein said at least one targeting product grouping is defined in reference to said taxonomy.
| 0.5 |
7,840,586 | 1 | 13 |
1. A method, comprising: selecting an item from a plurality of items each having associated metadata attributes; displaying a first value of a first metadata attribute of the selected item; defining a first modifier that modifies the first value of the first metadata attribute; searching the plurality of items in accordance with the first value and the first modifier; and displaying a result of the searching.
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1. A method, comprising: selecting an item from a plurality of items each having associated metadata attributes; displaying a first value of a first metadata attribute of the selected item; defining a first modifier that modifies the first value of the first metadata attribute; searching the plurality of items in accordance with the first value and the first modifier; and displaying a result of the searching. 13. The method of claim 1 , wherein the first metadata attribute is at least one of location, time, date, or user identification.
| 0.837121 |
9,697,184 | 1 | 11 |
1. A method of adjusting layout size of a hyperlink, comprising: displaying at least one hyperlink in a user interface; detecting a touch operation for the at least one hyperlink, and extracting position coordinates of a touch point formed by the touch operation on the user interface; determining a target hyperlink from the at least one hyperlink, and determining a precision of the touch operation with respect to the target hyperlink based on the position coordinates of the touch point; adjusting the layout size of the target hyperlink based on the determined precision; determining an average precision P of multiple touch operations with respect to the target hyperlink based on position coordinates of multiple touch points formed by the multiple touch operations during a latest time period; comparing the average precision P with a reference value N, and when P<N, generating an adjustment parameter for adjusting the layout size of the target hyperlink, and, based on the adjustment parameter, increasing the layout size of the target hyperlink by an amount commensurate with an adjustment value in a predetermined step; calculating an average distance Yt from multiple touch points to a center position of the target hyperlink based on position coordinates of multiple touch points formed by multiple continuous touch operations during a latest time period; configuring a monotone decreasing function of an average distance Yt as an average precision of the multiple touch operations with respect to the target hyperlink; comparing the average distance Yt with a threshold value Yal, and when Ya 1 <Yt, generating adjustment parameter for adjusting the layout size of the target hyperlink; increasing the layout size of the target hyperlink by an adjustment value in a predetermined step, where Ya 1 ≦Yb, wherein Yb represents a distance between an edge line of the target hyperlink and its center position; and when Yb<Yt, increasing the layout size of the hyperlink by an adjustment value ΔA 1 in a first predetermined step, and when Ya 1 <Yt ≦Yb, increasing the layout size of the hyperlink by an adjustment value ΔA 2 in a second predetermined step, where ΔA 2 <ΔA 1 .
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1. A method of adjusting layout size of a hyperlink, comprising: displaying at least one hyperlink in a user interface; detecting a touch operation for the at least one hyperlink, and extracting position coordinates of a touch point formed by the touch operation on the user interface; determining a target hyperlink from the at least one hyperlink, and determining a precision of the touch operation with respect to the target hyperlink based on the position coordinates of the touch point; adjusting the layout size of the target hyperlink based on the determined precision; determining an average precision P of multiple touch operations with respect to the target hyperlink based on position coordinates of multiple touch points formed by the multiple touch operations during a latest time period; comparing the average precision P with a reference value N, and when P<N, generating an adjustment parameter for adjusting the layout size of the target hyperlink, and, based on the adjustment parameter, increasing the layout size of the target hyperlink by an amount commensurate with an adjustment value in a predetermined step; calculating an average distance Yt from multiple touch points to a center position of the target hyperlink based on position coordinates of multiple touch points formed by multiple continuous touch operations during a latest time period; configuring a monotone decreasing function of an average distance Yt as an average precision of the multiple touch operations with respect to the target hyperlink; comparing the average distance Yt with a threshold value Yal, and when Ya 1 <Yt, generating adjustment parameter for adjusting the layout size of the target hyperlink; increasing the layout size of the target hyperlink by an adjustment value in a predetermined step, where Ya 1 ≦Yb, wherein Yb represents a distance between an edge line of the target hyperlink and its center position; and when Yb<Yt, increasing the layout size of the hyperlink by an adjustment value ΔA 1 in a first predetermined step, and when Ya 1 <Yt ≦Yb, increasing the layout size of the hyperlink by an adjustment value ΔA 2 in a second predetermined step, where ΔA 2 <ΔA 1 . 11. The method of claim 1 , wherein extracting position coordinates of a touch point formed by the touch operation on the user interface includes determining a central-point position of a contact area formed by the touch operation.
| 0.882503 |
6,070,160 | 4 | 5 |
4. The apparatus of claim 3, wherein the processor is further programmed to operate a security process effective to transfer the digital image data to the remote computer in a format effective to be displayed by the remote computer and effective to prohibit retention of a copy of the digital image data within the remote computer.
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4. The apparatus of claim 3, wherein the processor is further programmed to operate a security process effective to transfer the digital image data to the remote computer in a format effective to be displayed by the remote computer and effective to prohibit retention of a copy of the digital image data within the remote computer. 5. The apparatus of claim 4, wherein the digital image data is transferable as an ASCII text file directly executable by the remote computer as assembled source code.
| 0.5 |
10,101,822 | 1 | 6 |
1. A method for inputting language, the method comprising: at a device having one or more processors, memory, and a touch-sensitive display: detecting a sequence of contact inputs via a keyboard interface on the touch-sensitive display, wherein detecting a contact input of the sequence of contact inputs comprises detecting an initiation of contact with the touch-sensitive display at a first position of the keyboard interface, a continuous contact motion from the first position to a second position of the keyboard interface, and a release of contact from the touch-sensitive display at the second position, and wherein the contact input represents a user selection of at most one character key of the keyboard interface; determining a plurality of candidate words corresponding to the sequence of contact inputs; ranking the plurality of candidate words based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface; and displaying a portion of the plurality of candidate words for user selection.
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1. A method for inputting language, the method comprising: at a device having one or more processors, memory, and a touch-sensitive display: detecting a sequence of contact inputs via a keyboard interface on the touch-sensitive display, wherein detecting a contact input of the sequence of contact inputs comprises detecting an initiation of contact with the touch-sensitive display at a first position of the keyboard interface, a continuous contact motion from the first position to a second position of the keyboard interface, and a release of contact from the touch-sensitive display at the second position, and wherein the contact input represents a user selection of at most one character key of the keyboard interface; determining a plurality of candidate words corresponding to the sequence of contact inputs; ranking the plurality of candidate words based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface; and displaying a portion of the plurality of candidate words for user selection. 6. The method of claim 1 , wherein: the probability that the contact input is an intended input to select the first key of the keyboard interface is determined based on a distance between the first position and a center position of the first key; and the probability that the contact input is an intended input to select the second key of the keyboard interface is determined based on a distance between the first position and a center position of the second key.
| 0.56403 |
7,827,503 | 2 | 4 |
2. The method of claim 1 , further comprising: performing the search of content based on the determined symbol; and displaying a result of the search in a result window in the display area.
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2. The method of claim 1 , further comprising: performing the search of content based on the determined symbol; and displaying a result of the search in a result window in the display area. 4. The method of claim 2 , wherein the result comprises at least one of the following: a definition of the symbol, a translation of the symbol, an encyclopedia entry associated with the symbol, audio data of a sound of the symbol, and an image associated with the symbol.
| 0.5 |
8,335,680 | 1 | 3 |
1. An electronic apparatus comprising: a display device; an input unit; a storage which includes: dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language, reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language, and kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a processor which accepts the input of a reading in the second language via the input unit, reads a kanji character in the second language corresponding to the input reading in the second language from the reading-kanji correspondence information stored in the storage, reads a kanji character in the first language corresponding to the read kanji character in the second language from the kanji correspondence information stored in the storage and performs display control of the read kanji character on the display device, and reads explanatory information that uses a character string including the kanji character in the first language subjected to display control as an entry word from dictionary information stored in the storage and performs display control of the explanatory information on the display device; wherein the storage further includes multiple kanji correspondence information that causes a plurality of kanji kanji characters in the first language to correspond to a plurality of kanji characters in the second language, and the processor reads a kanji character in the second language corresponding to the reading in the second language input via the input unit from the reading-kanji correspondence information stored in the storage and determines whether the kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information and performs display control of the read kanji characters on the display device, if it has been determined that the kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language is not in the plurality of kanji characters included in the multiple kanji correspondence information.
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1. An electronic apparatus comprising: a display device; an input unit; a storage which includes: dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language, reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language, and kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a processor which accepts the input of a reading in the second language via the input unit, reads a kanji character in the second language corresponding to the input reading in the second language from the reading-kanji correspondence information stored in the storage, reads a kanji character in the first language corresponding to the read kanji character in the second language from the kanji correspondence information stored in the storage and performs display control of the read kanji character on the display device, and reads explanatory information that uses a character string including the kanji character in the first language subjected to display control as an entry word from dictionary information stored in the storage and performs display control of the explanatory information on the display device; wherein the storage further includes multiple kanji correspondence information that causes a plurality of kanji kanji characters in the first language to correspond to a plurality of kanji characters in the second language, and the processor reads a kanji character in the second language corresponding to the reading in the second language input via the input unit from the reading-kanji correspondence information stored in the storage and determines whether the kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information and performs display control of the read kanji characters on the display device, if it has been determined that the kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language is not in the plurality of kanji characters included in the multiple kanji correspondence information. 3. The electronic apparatus according to claim 1 , wherein each of the first language and the second language is any one of Japanese, Korean, and Chinese.
| 0.5 |
9,304,980 | 16 | 17 |
16. A system for identifying software component versions on a file system, the system comprising: a processor; and a non-transitory computer-readable medium having executable code, the executable code executed by the processor to perform steps of: scanning a plurality of target files to obtain content-based file identifiers; comparing each content-based file identifier to identifiers in a reference library to determine a plurality of candidate versions of software components, each candidate version corresponding to at least one of the content-based file identifiers; identifying a subset of candidate versions from the plurality of candidate versions as present on the file system by, for each candidate version in the plurality of candidate versions: determining whether the content-based file identifiers uniquely identify the candidate version using the reference library, a content-based file identifier uniquely identifying the candidate version responsive to the content-based file identifier matching an identifier in the reference library that is associated with the candidate version but is not associated with other candidate versions; and responsive to the content-based file identifiers uniquely identifying the candidate version, determining that the candidate version is present on the file system; and producing a report including the subset of candidate versions identified as present on the file system.
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16. A system for identifying software component versions on a file system, the system comprising: a processor; and a non-transitory computer-readable medium having executable code, the executable code executed by the processor to perform steps of: scanning a plurality of target files to obtain content-based file identifiers; comparing each content-based file identifier to identifiers in a reference library to determine a plurality of candidate versions of software components, each candidate version corresponding to at least one of the content-based file identifiers; identifying a subset of candidate versions from the plurality of candidate versions as present on the file system by, for each candidate version in the plurality of candidate versions: determining whether the content-based file identifiers uniquely identify the candidate version using the reference library, a content-based file identifier uniquely identifying the candidate version responsive to the content-based file identifier matching an identifier in the reference library that is associated with the candidate version but is not associated with other candidate versions; and responsive to the content-based file identifiers uniquely identifying the candidate version, determining that the candidate version is present on the file system; and producing a report including the subset of candidate versions identified as present on the file system. 17. The system of claim 16 , wherein determining that the candidate version is present on the file system comprises: determining whether a directory structure of the scanned target files matches a directory structure of at least one release of the candidate version; and responsive to the content-based file identifiers uniquely identifying the candidate version and the directory structure matching the at least one release of the candidate version, determining that the candidate version is present on the file system.
| 0.5 |
7,761,856 | 11 | 15 |
11. A computer program product for defining expressions in a meta-object model of an application, the computer program product comprising a computer readable medium having computer readable program code tangibly embedded therein, the computer readable program code comprising: computer readable program code configured to locate a string representation of an expression including an identification of a programming language associated with the expression, the string representation of the expression being in a syntax different from a syntax associated with the programming language, and the string representation of the expression to be converted into the expression based on the programming language, wherein the string representation of the expression is defined in the meta-object model of the application; computer readable program code configured to access a data type definition corresponding to the string representation of the expression, the data type definition including a converter for converting one or more of the string representation of the expression into the expression and a string representation of a data value into a data value instance, wherein the data type definition and the converter are part of the meta-object model; and computer readable program code configured to generate an executable runtime representation of the expression based on the expression.
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11. A computer program product for defining expressions in a meta-object model of an application, the computer program product comprising a computer readable medium having computer readable program code tangibly embedded therein, the computer readable program code comprising: computer readable program code configured to locate a string representation of an expression including an identification of a programming language associated with the expression, the string representation of the expression being in a syntax different from a syntax associated with the programming language, and the string representation of the expression to be converted into the expression based on the programming language, wherein the string representation of the expression is defined in the meta-object model of the application; computer readable program code configured to access a data type definition corresponding to the string representation of the expression, the data type definition including a converter for converting one or more of the string representation of the expression into the expression and a string representation of a data value into a data value instance, wherein the data type definition and the converter are part of the meta-object model; and computer readable program code configured to generate an executable runtime representation of the expression based on the expression. 15. The computer program product of claim 11 , wherein the converter includes a compiler.
| 0.840502 |
10,102,245 | 1 | 2 |
1. A method comprising, by one or more computing devices: receiving, from a client system of a first user, a search query input comprising a character string having a first number of characters; searching, by the one or more computing devices, one or more indexes of one or more verticals, respectively, to identify terms corresponding to the search query input, each index comprising terms associated with objects of a particular object-type of a plurality of object-types indexed by the one or more verticals, wherein: if the first number is less than or equal to a first threshold number, then searching one or more first indexes, wherein each first index is related to objects of a first object-type; and if the first number is greater than the first threshold number, then searching the one or more first indexes and one or more second indexes, wherein each second index is related to objects of a second object-type different than the first object-type; and sending, to the client system of the first user, instructions for presenting one or more suggested queries, each suggested query comprising the character string of the search query input and one or more of the identified terms.
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1. A method comprising, by one or more computing devices: receiving, from a client system of a first user, a search query input comprising a character string having a first number of characters; searching, by the one or more computing devices, one or more indexes of one or more verticals, respectively, to identify terms corresponding to the search query input, each index comprising terms associated with objects of a particular object-type of a plurality of object-types indexed by the one or more verticals, wherein: if the first number is less than or equal to a first threshold number, then searching one or more first indexes, wherein each first index is related to objects of a first object-type; and if the first number is greater than the first threshold number, then searching the one or more first indexes and one or more second indexes, wherein each second index is related to objects of a second object-type different than the first object-type; and sending, to the client system of the first user, instructions for presenting one or more suggested queries, each suggested query comprising the character string of the search query input and one or more of the identified terms. 2. The method of claim 1 , wherein searching the one or more indexes of the one or more verticals further comprises: if the first number is greater than a second threshold number, then searching the one or more first indexes, the one or more second indexes, and one or more third indexes, wherein each third index is related to objects of a third object-type different than the first object-type and the second object-type, and wherein the second threshold number is greater than the first threshold number.
| 0.610599 |
8,266,162 | 10 | 12 |
10. An apparatus comprising: one or more processing devices; and one or more machine-readable storage devices for storing instructions that are executable by the one or more processing devices to perform operations comprising: collecting data indicative of search terms associated with one or more search queries; identifying, in the search terms, a particular keyword; identifying remaining search terms as candidate keywords related to the particular keyword; and generating a confidence score for a candidate keyword, the confidence score comprising a ratio of (i) a number of times the candidate keyword and the particular keyword appeared in a same search query of the one or more search queries, to (ii) a number of times the candidate keyword appeared in the one or more search queries.
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10. An apparatus comprising: one or more processing devices; and one or more machine-readable storage devices for storing instructions that are executable by the one or more processing devices to perform operations comprising: collecting data indicative of search terms associated with one or more search queries; identifying, in the search terms, a particular keyword; identifying remaining search terms as candidate keywords related to the particular keyword; and generating a confidence score for a candidate keyword, the confidence score comprising a ratio of (i) a number of times the candidate keyword and the particular keyword appeared in a same search query of the one or more search queries, to (ii) a number of times the candidate keyword appeared in the one or more search queries. 12. The apparatus of claim 10 , wherein the operations further comprise: assigning a weighting to the candidate keyword based on a ratio of a cost for using the candidate keyword in a pay-per-click advertising arrangement to a frequency-of-use metric.
| 0.640401 |
8,683,321 | 1 | 2 |
1. A computer-assisted method of transforming a document with semantic encoding destined for a target service, including: electronically requesting by target service identifier and receiving from an interface registry at least one target document version used by a target service from among a plurality of document versions in a document family; and electronically requesting by source and target document versions and receiving from a document family registry one or more transforms or references to transforms to be applied sequentially to convert a document from the source document version to the target document version.
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1. A computer-assisted method of transforming a document with semantic encoding destined for a target service, including: electronically requesting by target service identifier and receiving from an interface registry at least one target document version used by a target service from among a plurality of document versions in a document family; and electronically requesting by source and target document versions and receiving from a document family registry one or more transforms or references to transforms to be applied sequentially to convert a document from the source document version to the target document version. 2. The method of claim 1 , further including applying the transforms to convert the document from the source document version to the target document version.
| 0.603535 |
10,027,688 | 1 | 2 |
1. A method of detecting at least one malicious and/or botnet-related domain name, comprising: performing processing associated with collecting at least one domain name by monitoring Domain Name System (DNS) traffic in at least one network; performing processing associated with obtaining, during a time period, information about the at least one domain name, comprising determining if the at least one domain name is in at least one domain name white list; wherein the obtained information further comprises statistics related to the at least one domain name comprising a total number of queries to the at least one domain name during the time period and a total number of distinct source IP addresses that queried the at least one domain name during the time period; responsive to determining that the at least one domain name is not in the at least one domain name white list, performing processing associated with automatically obtaining, using at least one Internet search engine, search results for the at least one domain name; performing processing associated with analyzing the search results to determine whether at least one search result associated with the at least one domain name comprises a known malware site; and performing processing associated with classifying the at least one domain name as at least one of malicious, suspicious, and legitimate based on the analyzed search results.
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1. A method of detecting at least one malicious and/or botnet-related domain name, comprising: performing processing associated with collecting at least one domain name by monitoring Domain Name System (DNS) traffic in at least one network; performing processing associated with obtaining, during a time period, information about the at least one domain name, comprising determining if the at least one domain name is in at least one domain name white list; wherein the obtained information further comprises statistics related to the at least one domain name comprising a total number of queries to the at least one domain name during the time period and a total number of distinct source IP addresses that queried the at least one domain name during the time period; responsive to determining that the at least one domain name is not in the at least one domain name white list, performing processing associated with automatically obtaining, using at least one Internet search engine, search results for the at least one domain name; performing processing associated with analyzing the search results to determine whether at least one search result associated with the at least one domain name comprises a known malware site; and performing processing associated with classifying the at least one domain name as at least one of malicious, suspicious, and legitimate based on the analyzed search results. 2. The method of claim 1 , further comprising, calculating a suspiciousness score based on the total number of queries to the at least one domain name during the time period and the total number of distinct source IP addresses that queried the at least one domain name during the time period, wherein the classifying the at least one domain name as at least one of malicious, suspicious, and legitimate is further based on the suspiciousness score.
| 0.5 |
10,114,874 | 3 | 4 |
3. The method of claim 1 , wherein for each source query of the second set of source queries, the method further includes: identifying a source table included in the respective source query; determining a cache table name based on a name of the identified source table, wherein the storing includes storing the result in a table identified by the cache table name.
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3. The method of claim 1 , wherein for each source query of the second set of source queries, the method further includes: identifying a source table included in the respective source query; determining a cache table name based on a name of the identified source table, wherein the storing includes storing the result in a table identified by the cache table name. 4. The method of claim 3 , wherein the determining a cache table name includes identifying a source table name of the identified source table and adding a suffix to the source table name.
| 0.793142 |
9,164,973 | 1 | 2 |
1. A computer-implemented method for synthesizing a reusable graphic in a document, the method comprising: extracting an identified graphic from the document to provide an extracted graphic, wherein the extracting comprises: identifying individual candidate reusable graphic components contained within the document; extracting feature information and environmental information about each of the individual candidate reusable graphic components; evaluating the extracted information associated with each individual candidate reusable graphic component to determine whether the individual candidate reusable graphic components are to be consolidated into a single reusable graphic, wherein the evaluating includes a plurality of: performing a first determining of whether a first of the individual candidate reusable graphic components is placed over a second of the individual candidate reusable graphic components in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; performing a second determining of whether the first individual candidate reusable graphic component is within a predetermined distance from the second individual candidate reusable graphic component in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and performing a third determining of whether a third of the individual candidate reusable graphic components is between the first and the second individual candidate reusable graphic components to determine whether the first, second and third individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and synthesizing a single reusable graphic from the plurality of the first, second, and third individual candidate reusable graphic components based on at least one of the first, second, and third determinations.
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1. A computer-implemented method for synthesizing a reusable graphic in a document, the method comprising: extracting an identified graphic from the document to provide an extracted graphic, wherein the extracting comprises: identifying individual candidate reusable graphic components contained within the document; extracting feature information and environmental information about each of the individual candidate reusable graphic components; evaluating the extracted information associated with each individual candidate reusable graphic component to determine whether the individual candidate reusable graphic components are to be consolidated into a single reusable graphic, wherein the evaluating includes a plurality of: performing a first determining of whether a first of the individual candidate reusable graphic components is placed over a second of the individual candidate reusable graphic components in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; performing a second determining of whether the first individual candidate reusable graphic component is within a predetermined distance from the second individual candidate reusable graphic component in the document to determine whether the first and second individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and performing a third determining of whether a third of the individual candidate reusable graphic components is between the first and the second individual candidate reusable graphic components to determine whether the first, second and third individual candidate reusable graphic components are to be consolidated into a single reusable graphic; and synthesizing a single reusable graphic from the plurality of the first, second, and third individual candidate reusable graphic components based on at least one of the first, second, and third determinations. 2. The method of claim 1 , further comprising extracting at least one textual feature from the document or the extracted graphic, extracting at least one visual feature from the extracted graphic, and classifying the extracted graphic based on the at least one extracted textual or visual feature.
| 0.800671 |
10,056,077 | 19 | 23 |
19. A system for entering text into a music system comprising: a resident capture facility for recording speech presented by a user; a speech recognition facility for receiving the speech as a recording, for determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording, for conducting the additional recognition pass of the recording, for selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording, and for generating results by selecting at least one statistical language model from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one selected statistical language model includes a general language model for artists, a general language model for song titles, and a general language model for music types; and the music system for using the results, wherein the music system provides information relating to a music application to the speech recognition facility and wherein the results are generated based at least in part on the information, and wherein the contextual information includes usage history of the music application and information from at least one of a favorites list and playlists of the user.
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19. A system for entering text into a music system comprising: a resident capture facility for recording speech presented by a user; a speech recognition facility for receiving the speech as a recording, for determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording, for conducting the additional recognition pass of the recording, for selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording, and for generating results by selecting at least one statistical language model from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one selected statistical language model includes a general language model for artists, a general language model for song titles, and a general language model for music types; and the music system for using the results, wherein the music system provides information relating to a music application to the speech recognition facility and wherein the results are generated based at least in part on the information, and wherein the contextual information includes usage history of the music application and information from at least one of a favorites list and playlists of the user. 23. The system of claim 19 , wherein the speech recognition facility allows the user an opportunity to alter the speech from the recording recognized by the speech recognition facility.
| 0.631474 |
9,548,987 | 10 | 17 |
10. The apparatus of claim 7 wherein the ordered list comprises, for each of the one or more new events, a first classification indicator specifying the riskiness of the new event utilizing the learning set and a second classification indicator specifying the riskiness of the new event without utilizing the learning set.
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10. The apparatus of claim 7 wherein the ordered list comprises, for each of the one or more new events, a first classification indicator specifying the riskiness of the new event utilizing the learning set and a second classification indicator specifying the riskiness of the new event without utilizing the learning set. 17. The apparatus of claim 10 wherein the ordered list further comprises, for each of the one or more new events, at least a subset of the metadata associated with new event including a policy associated with the product causing generation of the new event at its corresponding event generator in the information technology infrastructure.
| 0.5 |
5,414,847 | 3 | 4 |
3. A distributed computer device in a distributed processing system for a data processing operation comprising a plurality of processes, said distributed computer device comprising: means for receiving data items, input by an operator, said data including names of the processes, names of respective data items to be input to said processes and corresponding attributes to said data items and for producing definitions for the processes forming said data processing operation and a corresponding data flowchart; system flow generation tool means for producing a system flowchart on the basis of the data flowchart corresponding to the processes; programs specification generation tool means for producing program specifications, designating program names, a program pattern name, input file name and output file name, on the basis of said system flowchart and interactive operation by an operator; data analysis tool means for extracting a data item from the data processing operation on the basis of said data flowchart; storage means for storing the extracted data item; and source program generation tool means for producing a source program for the data processing operation on the basis of the extracted data item obtained from said storage means and the programs specifications.
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3. A distributed computer device in a distributed processing system for a data processing operation comprising a plurality of processes, said distributed computer device comprising: means for receiving data items, input by an operator, said data including names of the processes, names of respective data items to be input to said processes and corresponding attributes to said data items and for producing definitions for the processes forming said data processing operation and a corresponding data flowchart; system flow generation tool means for producing a system flowchart on the basis of the data flowchart corresponding to the processes; programs specification generation tool means for producing program specifications, designating program names, a program pattern name, input file name and output file name, on the basis of said system flowchart and interactive operation by an operator; data analysis tool means for extracting a data item from the data processing operation on the basis of said data flowchart; storage means for storing the extracted data item; and source program generation tool means for producing a source program for the data processing operation on the basis of the extracted data item obtained from said storage means and the programs specifications. 4. A distributed computer device according to claim 3, further comprising means for advancing one step of the data processing operation to a next step of said process, by advancing data generated in the one step to the next step in accordance with a predetermined order input to said computer.
| 0.5 |
9,509,847 | 20 | 38 |
20. The method of claim 1 , wherein the first endpoint and a subsequent endpoint are part of the plurality of endpoints in the contact center operation system, and further comprising the step of: a. performing by the first endpoint, the language assignment of the inbound interaction based at least in part on at least one of the interaction's location of origin and the interaction's destination location, wherein the language assignment comprises the reference means.
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20. The method of claim 1 , wherein the first endpoint and a subsequent endpoint are part of the plurality of endpoints in the contact center operation system, and further comprising the step of: a. performing by the first endpoint, the language assignment of the inbound interaction based at least in part on at least one of the interaction's location of origin and the interaction's destination location, wherein the language assignment comprises the reference means. 38. The method of claim 20 , wherein the interaction comprises video.
| 0.780255 |
8,156,508 | 11 | 19 |
11. A non-transitory computer-accessible memory medium comprising program instructions for runtime execution of one or more tasks defined in a workflow process language, wherein the program instructions are executable by a processor to: at runtime: obtain a description of the one or more tasks from a process ontology (PO), the process ontology (PO) defining a hierarchical taxonomy of executable tasks, each task referring to at least one frame of a hierarchical frame taxonomy of the process ontology (PO); identify at least one task parameter as described in the frame description to which the task refers; resolve the value of the at least one task parameter, comprising determining the value of the at least one task parameter; select a most specific applicable version of the task from a plurality of versions of the task contained in the task taxonomy of the process ontology (PO) based on the resolved value of the at least one task parameter; execute the most specific applicable version of the task.
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11. A non-transitory computer-accessible memory medium comprising program instructions for runtime execution of one or more tasks defined in a workflow process language, wherein the program instructions are executable by a processor to: at runtime: obtain a description of the one or more tasks from a process ontology (PO), the process ontology (PO) defining a hierarchical taxonomy of executable tasks, each task referring to at least one frame of a hierarchical frame taxonomy of the process ontology (PO); identify at least one task parameter as described in the frame description to which the task refers; resolve the value of the at least one task parameter, comprising determining the value of the at least one task parameter; select a most specific applicable version of the task from a plurality of versions of the task contained in the task taxonomy of the process ontology (PO) based on the resolved value of the at least one task parameter; execute the most specific applicable version of the task. 19. The non-transitory computer-accessible memory medium of claim 11 , wherein the description of each task comprises attributes defining the frame it refers to, one or more input parameters, one or more output parameters and a reference to an implementation of the task.
| 0.564309 |
9,519,636 | 14 | 18 |
14. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer to perform a process comprising: receiving text; extracting a plurality of linguistic entities and associated linguistic entity categories based on the text; determining one or more semantic objects of a semantic layer based on the linguistic entity categories, wherein each of the one or more semantic objects of the semantic layer associates one or more physical entities stored in a data source with user-friendly names; determining an analysis context based on the text, the linguistic entities, and the associated linguistic entity categories; after determination of the analysis context and the one or more semantic objects, generating a query of the semantic layer based on the analysis context and the one or more semantic objects, wherein the generating the query of the semantic layer comprises: determining, based on the linguistic entity categories that were extracted, whether the one or more semantic objects are to be filtered, and in response to determining to filter the one or more semantic objects, determining how to filter the semantic objects, wherein when a value from a first linguistic entity category matches a value for one of the one or more semantic objects, using the value from the first linguistic entity category as a query filter, and when only a single entity is mentioned for the first linguistic entity category, including the entity in the query filter and removing the first linguistic entity category from a result of the query of the semantic layer; and receiving a structured data result in response to the query of the semantic layer.
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14. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer to perform a process comprising: receiving text; extracting a plurality of linguistic entities and associated linguistic entity categories based on the text; determining one or more semantic objects of a semantic layer based on the linguistic entity categories, wherein each of the one or more semantic objects of the semantic layer associates one or more physical entities stored in a data source with user-friendly names; determining an analysis context based on the text, the linguistic entities, and the associated linguistic entity categories; after determination of the analysis context and the one or more semantic objects, generating a query of the semantic layer based on the analysis context and the one or more semantic objects, wherein the generating the query of the semantic layer comprises: determining, based on the linguistic entity categories that were extracted, whether the one or more semantic objects are to be filtered, and in response to determining to filter the one or more semantic objects, determining how to filter the semantic objects, wherein when a value from a first linguistic entity category matches a value for one of the one or more semantic objects, using the value from the first linguistic entity category as a query filter, and when only a single entity is mentioned for the first linguistic entity category, including the entity in the query filter and removing the first linguistic entity category from a result of the query of the semantic layer; and receiving a structured data result in response to the query of the semantic layer. 18. The medium according to claim 14 , wherein the generating the query of the semantic layer comprises: generating a second query based on the analysis context.
| 0.903823 |
7,818,171 | 1 | 4 |
1. A speech recognition apparatus comprising: a storage medium for storing tree structured dictionary data that contains a plurality of words as nodes in a tree structure; a backward speech comparison unit for comparing a backward speech resulting from reproducing an input speech in chronologically backward order with a backward acoustic model corresponding to a speech of reversely reproducing a word string sequence toward a root of the tree structure, wherein a comparison is performed in reverse order of the sequence; a forward speech comparison unit for comparing the input speech with a forward acoustic model corresponding to a speech resulting from reproducing a leaf node word of the tree structure in chronologically forward order; a detection unit for detecting a beginning and an end of receiving the input speech, wherein the forward speech comparison unit starts comparing received part of the input speech with the forward acoustic model immediately when the detection unit detects a beginning of receiving the input speech before detecting an end of receiving the input speech; and an output unit for outputting a word or a word string highly likely matching the input speech based on a comparison result each from the backward speech comparison unit and the forward speech comparison unit.
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1. A speech recognition apparatus comprising: a storage medium for storing tree structured dictionary data that contains a plurality of words as nodes in a tree structure; a backward speech comparison unit for comparing a backward speech resulting from reproducing an input speech in chronologically backward order with a backward acoustic model corresponding to a speech of reversely reproducing a word string sequence toward a root of the tree structure, wherein a comparison is performed in reverse order of the sequence; a forward speech comparison unit for comparing the input speech with a forward acoustic model corresponding to a speech resulting from reproducing a leaf node word of the tree structure in chronologically forward order; a detection unit for detecting a beginning and an end of receiving the input speech, wherein the forward speech comparison unit starts comparing received part of the input speech with the forward acoustic model immediately when the detection unit detects a beginning of receiving the input speech before detecting an end of receiving the input speech; and an output unit for outputting a word or a word string highly likely matching the input speech based on a comparison result each from the backward speech comparison unit and the forward speech comparison unit. 4. The speech recognition apparatus of claim 1 , comprising: a selection unit for selecting a plurality of words from a group of leaf node words according to the tree structure, wherein the forward speech comparison unit compares the input speech with a forward acoustic model corresponding to a speech resulting from chronologically reproducing the plurality of words selected by the selection unit.
| 0.552573 |
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