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8,625,154 | 3 | 5 |
3. The apparatus of claim 2 , wherein the color information correction module comprises: a preference color input module which inputs a preference color to be corrected among preference colors constituting the input image; and a color component correction module which corrects a color component of the input preference color.
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3. The apparatus of claim 2 , wherein the color information correction module comprises: a preference color input module which inputs a preference color to be corrected among preference colors constituting the input image; and a color component correction module which corrects a color component of the input preference color. 5. The apparatus of claim 3 , wherein the color component is one of lightness, chroma, and hue.
| 0.704969 |
8,555,248 | 15 | 16 |
15. The computer-implemented method according to claim 1 , wherein the determining that a cardinality of a business object node action has changed while the business object node action is associated with the RELEASED release status code or that a cardinality of a business object node association has changed while the business object node association is associated with the RELEASED release status code comprises: determining that a technical name of a query has changed while the query is associated with the RELEASED release status code; and wherein the raising a flag in a business application development environment to indicate that a constraint has been violated comprises: raising a flag in a business application development environment to indicate that a constraint has been violated in response to the determining that a technical name of a query has changed while the query is associated with the RELEASED release status code.
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15. The computer-implemented method according to claim 1 , wherein the determining that a cardinality of a business object node action has changed while the business object node action is associated with the RELEASED release status code or that a cardinality of a business object node association has changed while the business object node association is associated with the RELEASED release status code comprises: determining that a technical name of a query has changed while the query is associated with the RELEASED release status code; and wherein the raising a flag in a business application development environment to indicate that a constraint has been violated comprises: raising a flag in a business application development environment to indicate that a constraint has been violated in response to the determining that a technical name of a query has changed while the query is associated with the RELEASED release status code. 16. The computer-implemented method according to claim 15 , wherein the first metadata associated with the first release associates the query with the RELEASED release status code; wherein metadata associated with a next release after the first release associates the query with the RELEASED release status code; wherein the determining that a technical name of a query has changed while the query is associated with the RELEASED release status code comprises: determining that the technical name of the query in the next release is changed from the technical name of the query in the first release; and wherein the raising a flag in a business application development environment to indicate that a constraint has been violated comprises: raising a flag in a business application development environment to indicate that a constraint has been violated in response to the determining that the technical name of the query in the next release is changed from the technical name of the query in the first release.
| 0.5 |
9,183,830 | 21 | 24 |
21. A non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: implementing a source hidden Markov model (HMM) based speech features generator by one or more processors of a system, wherein the source HMM based speech features generator comprises a configuration of source HMM state models, each of the source HMM state models having a set of generator-model functions, and wherein the implemented source HMM based speech features generator is trained using speech signals of a source speaker; providing a set of target-speaker vectors, the set of target-speaker vectors having been generated from speech features extracted from speech signals of a target speaker; implementing a converted HMM based speech features generator that is the same as the source HMM based speech features generator, but wherein (i) parameters of the set of generator-model functions of each given source HMM state model of the converted HMM based speech features generator are replaced with a particular target-speaker vector from among the target set that most closely matches the parameters of the set of generator-model functions of the given source HMM, and (ii) fundamental frequency (F0) statistics of the converted HMM based speech features generator are speech-adapted using an F0 transform that speech-adapts F0 statistics of the source HMM based speech features generator to match F0 statistics of the speech of the target speaker.
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21. A non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: implementing a source hidden Markov model (HMM) based speech features generator by one or more processors of a system, wherein the source HMM based speech features generator comprises a configuration of source HMM state models, each of the source HMM state models having a set of generator-model functions, and wherein the implemented source HMM based speech features generator is trained using speech signals of a source speaker; providing a set of target-speaker vectors, the set of target-speaker vectors having been generated from speech features extracted from speech signals of a target speaker; implementing a converted HMM based speech features generator that is the same as the source HMM based speech features generator, but wherein (i) parameters of the set of generator-model functions of each given source HMM state model of the converted HMM based speech features generator are replaced with a particular target-speaker vector from among the target set that most closely matches the parameters of the set of generator-model functions of the given source HMM, and (ii) fundamental frequency (F0) statistics of the converted HMM based speech features generator are speech-adapted using an F0 transform that speech-adapts F0 statistics of the source HMM based speech features generator to match F0 statistics of the speech of the target speaker. 24. The non-transitory computer-readable storage medium of claim 21 , wherein the set of generator-model functions for each given source HMM state model comprises a multivariate spectral probability density function (PDF) for jointly modeling spectral envelope parameters of a phonetic unit modeled by a given source HMM state model, and a multivariate excitation PDF for jointly modeling excitation parameters of the phonetic unit, and wherein determining for each given source HMM state model the particular target-speaker vector from among the target set that most closely matches parameters of the set of generator-model functions of the given source HMM comprises: determining a target-speaker vector from among the target set that is computationally nearest to parameters of the multivariate spectral PDF of the given source HMM state model in terms of a distance criterion based on one of mean-squared-error (mse) or Kullback-Leibler distance; and determining a target-speaker vector from among the target set that is computationally nearest to the multivariate excitation PDF of the given source HMM state model in terms of a distance criterion based on one of mse or Kullback-Leibler distance.
| 0.5 |
8,892,421 | 1 | 19 |
1. A computer-implemented method of determining a difficulty level of a text, comprising: determining with a processing system a number of cohesive devices present in a text; determining with the processing system a number of cohesive devices expected in the text, wherein determining the expected number of cohesive devices includes: for each sentence in the text having a preceding sentence in the text, determining a total number of words in that sentence and a sentence preceding that sentence to generate a sentence pair total; determining a sum of the sentence pair totals; and determining the expected number of cohesive devices based on the sum of the sentence pair totals; calculating with the processing system a cohesiveness metric based on the number of cohesive devices present in the text and the number of cohesive devices expected in the text; and identifying a difficulty level of the text based upon the cohesiveness metric.
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1. A computer-implemented method of determining a difficulty level of a text, comprising: determining with a processing system a number of cohesive devices present in a text; determining with the processing system a number of cohesive devices expected in the text, wherein determining the expected number of cohesive devices includes: for each sentence in the text having a preceding sentence in the text, determining a total number of words in that sentence and a sentence preceding that sentence to generate a sentence pair total; determining a sum of the sentence pair totals; and determining the expected number of cohesive devices based on the sum of the sentence pair totals; calculating with the processing system a cohesiveness metric based on the number of cohesive devices present in the text and the number of cohesive devices expected in the text; and identifying a difficulty level of the text based upon the cohesiveness metric. 19. The method of claim 1 , comprising selecting the text for inclusion on an examination based on the identified level of difficulty.
| 0.860125 |
8,407,217 | 14 | 17 |
14. A computer-assisted method for indexing documents for search and ranking search results, comprising: obtaining a first group of text units in one of the documents in a document collection by a computer system, each of the text units comprises one or more words; tokenizing the first group of text units by the computer system to produce a plurality of tokens that include a jth token; assigning token types to the tokens in the first group of text units according to the grammatical roles of the tokens; assigning weighting coefficients to the tokens in the first group of text units according to the token types of the tokens; for each text unit in the first group that includes the jth token, adding a weighting coefficient to a parameter token_j_count; dividing a cumulative value of the parameter token_j_count obtained from the first group of text units by the total number of text units in the first group to produce an internal term prominence (ITP) value for the jth token; obtaining a data set comprising a plurality of external term prominence (ETP) values each associated with one of the plurality of tokens including the jth token, wherein the ETP value is calculated using a second group of text units from external or random documents outside of the document collection; calculating a term prominence value for the jth token using the ITP and the ETP values of the jth token; receiving a query comprising a keyword for search in the document collection containing text; matching the keyword to one of the plurality of tokens to obtain a matched token; and ranking, by the computer system, the documents in the collection by the term prominence values for the matched token associated with their respective documents.
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14. A computer-assisted method for indexing documents for search and ranking search results, comprising: obtaining a first group of text units in one of the documents in a document collection by a computer system, each of the text units comprises one or more words; tokenizing the first group of text units by the computer system to produce a plurality of tokens that include a jth token; assigning token types to the tokens in the first group of text units according to the grammatical roles of the tokens; assigning weighting coefficients to the tokens in the first group of text units according to the token types of the tokens; for each text unit in the first group that includes the jth token, adding a weighting coefficient to a parameter token_j_count; dividing a cumulative value of the parameter token_j_count obtained from the first group of text units by the total number of text units in the first group to produce an internal term prominence (ITP) value for the jth token; obtaining a data set comprising a plurality of external term prominence (ETP) values each associated with one of the plurality of tokens including the jth token, wherein the ETP value is calculated using a second group of text units from external or random documents outside of the document collection; calculating a term prominence value for the jth token using the ITP and the ETP values of the jth token; receiving a query comprising a keyword for search in the document collection containing text; matching the keyword to one of the plurality of tokens to obtain a matched token; and ranking, by the computer system, the documents in the collection by the term prominence values for the matched token associated with their respective documents. 17. The computer-assisted method of claim 14 , wherein each of the text units is a sentence or a paragraph.
| 0.755708 |
9,218,334 | 18 | 20 |
18. A device comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that cause the at least one processor to perform a method comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability model to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings.
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18. A device comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that cause the at least one processor to perform a method comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability model to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings. 20. The device of claim 18 , wherein the method further comprising building the character order model representing character order characteristics of pronounceable words.
| 0.5 |
5,583,543 | 17 | 18 |
17. The pen input processing apparatus as set forth in claim 16, further comprising: second memory means for temporarily storing interrupting data from said inputting means, and for temporarily storing interrupting key data from said keyboard means.
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17. The pen input processing apparatus as set forth in claim 16, further comprising: second memory means for temporarily storing interrupting data from said inputting means, and for temporarily storing interrupting key data from said keyboard means. 18. The pen input processing apparatus as set forth in claim 17, wherein said key input nullifying means includes: means for reading the data out of said second memory means, and for judging whether the data is the interrupting data or the interrupting key data; and informing means for informing an error when the data is the interrupting key data and the editing processing is carried out in accordance with the handwritten input.
| 0.524229 |
8,020,111 | 6 | 17 |
6. A computer-readable medium having computer-executable instructions stored thereon to execute a data access model, comprising: a log that collects a plurality of past web data access patterns for a computer user, wherein each past web data access pattern comprises a web page accessed by the user on a computer and a context associated with each web page; a classifier component to perform automatic topic classification of the web page accessed by the user a context component to record the context associated with each web site; and a predictive component to determine web future data access patterns based at least in part on the past web data access patterns, the topic classification of the web page accessed by the user, and the recorded context, and based at least in part on interest of the user in a page from among the past web data access patterns, the interest in the page being computed as I(p)=L(p)*Constant 1 +D(p)*Constant 2 , where I(p) is interest in a page p, L(p) is links followed from page p, D(p) is an average number of seconds spent in sessions starting with page p, and constants Constant 1 and Constant 2 are selected to equate an average of links followed from page p with an average session time length of approximately 30 seconds.
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6. A computer-readable medium having computer-executable instructions stored thereon to execute a data access model, comprising: a log that collects a plurality of past web data access patterns for a computer user, wherein each past web data access pattern comprises a web page accessed by the user on a computer and a context associated with each web page; a classifier component to perform automatic topic classification of the web page accessed by the user a context component to record the context associated with each web site; and a predictive component to determine web future data access patterns based at least in part on the past web data access patterns, the topic classification of the web page accessed by the user, and the recorded context, and based at least in part on interest of the user in a page from among the past web data access patterns, the interest in the page being computed as I(p)=L(p)*Constant 1 +D(p)*Constant 2 , where I(p) is interest in a page p, L(p) is links followed from page p, D(p) is an average number of seconds spent in sessions starting with page p, and constants Constant 1 and Constant 2 are selected to equate an average of links followed from page p with an average session time length of approximately 30 seconds. 17. The model of claim 6 , further comprising the classifier employing a vector-based learning algorithm.
| 0.725131 |
6,155,834 | 3 | 18 |
3. The computer implemented, data driven method of teaching a student to read according to claim 2, wherein the whole word recognition test; the partial word recognition test; and the word sequence recognition test represent three interactive process types respectively corresponding to choosing a target word from a list of displayed words by first communicating the target then choosing the target word from a list of subsequently displayed words; filling in letter blanks by first communicating a target word and then filling in letter blanks of a displayed, partial target word having blanked letters; and determining a correct sequence of words by individually communicating a plurality of words that includes the target word in a first sequence one word at a time, then simultaneously displaying the plurality of words including the target word in a second sequence, and then selecting words from the displayed plurality of words in the first sequence, said presenting step presenting the student with at least one of nine interactive processes wherein each interactive process type includes three interactive processes, the three interactive processes including a show only process which communicates the target word by displaying the target word for a show interval, a say only process which communicates the target word by audibly announcing the target word, and a show and say process that communicates the target word by displaying the target word for a show interval and by audibly announcing the target word.
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3. The computer implemented, data driven method of teaching a student to read according to claim 2, wherein the whole word recognition test; the partial word recognition test; and the word sequence recognition test represent three interactive process types respectively corresponding to choosing a target word from a list of displayed words by first communicating the target then choosing the target word from a list of subsequently displayed words; filling in letter blanks by first communicating a target word and then filling in letter blanks of a displayed, partial target word having blanked letters; and determining a correct sequence of words by individually communicating a plurality of words that includes the target word in a first sequence one word at a time, then simultaneously displaying the plurality of words including the target word in a second sequence, and then selecting words from the displayed plurality of words in the first sequence, said presenting step presenting the student with at least one of nine interactive processes wherein each interactive process type includes three interactive processes, the three interactive processes including a show only process which communicates the target word by displaying the target word for a show interval, a say only process which communicates the target word by audibly announcing the target word, and a show and say process that communicates the target word by displaying the target word for a show interval and by audibly announcing the target word. 18. The computer implemented, data driven method of teaching a student to read according to claim 3, said adjusting step adjusting the difficulty level of the filling in letter blanks interactive process presented in said presenting step by gradually and proportionally adjusting how many blanks are to be filled in by the student based on student age, student performance and number of iterations performed by said first iterating step; said calculating step calculating student performance based on the number of blanks to be filled in by the student.
| 0.605563 |
8,402,005 | 3 | 8 |
3. A method for creating, in response to a single action, a self-extracting file from an associated input file, wherein the associated input file is automatically launched upon execution of the self-extracting file, and wherein a user is not required to separately choose a data compression method, create a compressed archive using the chosen compression method, select an input file to be launched upon decompression of the compressed archive, and create a self-extracting file from the compressed archive, the method comprising: receiving an input file to be used in creating a self-extracting file, wherein the file is one of a plurality of file types; and in response to only a single action, creating a self-extracting file from the input file, wherein the input file is configured to be automatically launched upon execution of the self-extracting file.
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3. A method for creating, in response to a single action, a self-extracting file from an associated input file, wherein the associated input file is automatically launched upon execution of the self-extracting file, and wherein a user is not required to separately choose a data compression method, create a compressed archive using the chosen compression method, select an input file to be launched upon decompression of the compressed archive, and create a self-extracting file from the compressed archive, the method comprising: receiving an input file to be used in creating a self-extracting file, wherein the file is one of a plurality of file types; and in response to only a single action, creating a self-extracting file from the input file, wherein the input file is configured to be automatically launched upon execution of the self-extracting file. 8. The method of claim 3 , wherein the single action is a call from a software routine.
| 0.762295 |
9,142,213 | 7 | 10 |
7. A computer program product comprising: a plurality of computer-executable instructions recorded on a non-transitory computer-readable media, wherein said computer-executable instructions, when executed by at least one computer system, cause the at least one computer system to: receive in the at least one computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyze the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model.
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7. A computer program product comprising: a plurality of computer-executable instructions recorded on a non-transitory computer-readable media, wherein said computer-executable instructions, when executed by at least one computer system, cause the at least one computer system to: receive in the at least one computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyze the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model. 10. The computer program product of claim 7 , further comprising the software application user executing a voice-enabled wizard program based on the created voice-enabled wizard code starting by filling attribute values for an entry wizard dialog unit code and the internal wizard dialog unit code if any, until all the wizard dialog unit code attributes have been filled.
| 0.761844 |
7,716,170 | 1 | 3 |
1. A computer implemented method for dynamically and contextually managing information in an electronic computational environment, the method comprising: with respect to a project, the project providing a corresponding context and/or one or more other contexts for management of a plurality of information elements, each information element being in at least one of a plurality of information categories, each information category being a member of a category set, the category set including data category, function category, and result category, wherein the corresponding context and/or one or more other contexts corresponds to at least one contextual model, where the contextual model is defined by the information elements and a set of rules governing permissible relationships among the information elements; (a) receiving an input and/or user interaction to the electronic computational environment specifying a relationship among at least two information elements; (b) using an integrity engine, operating globally to enforce the set of rules, to verify dynamically correctness of the relationship specified among all information categories within the corresponding context and/or one or more other contexts; wherein the integrity engine's role varies by the information category and operates on at least one of a plurality of levels within each information category to cause enforcement of the set of rules within the corresponding context and/or one or more other contexts; the plurality of levels within each information category including syntactic, semantic, and operational levels; where the corresponding context and/or one or more other contexts and the integrity engine establish the contextual model; and (c) upon acceptance of the relationship by the integrity engine, storing automatically the relationship specified in a storage medium, permitting dynamic interaction, wherein the dynamic interaction includes storing, retrieving, manipulation of information elements, and modifications of relations with respect to the corresponding context and/or one or more other contexts.
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1. A computer implemented method for dynamically and contextually managing information in an electronic computational environment, the method comprising: with respect to a project, the project providing a corresponding context and/or one or more other contexts for management of a plurality of information elements, each information element being in at least one of a plurality of information categories, each information category being a member of a category set, the category set including data category, function category, and result category, wherein the corresponding context and/or one or more other contexts corresponds to at least one contextual model, where the contextual model is defined by the information elements and a set of rules governing permissible relationships among the information elements; (a) receiving an input and/or user interaction to the electronic computational environment specifying a relationship among at least two information elements; (b) using an integrity engine, operating globally to enforce the set of rules, to verify dynamically correctness of the relationship specified among all information categories within the corresponding context and/or one or more other contexts; wherein the integrity engine's role varies by the information category and operates on at least one of a plurality of levels within each information category to cause enforcement of the set of rules within the corresponding context and/or one or more other contexts; the plurality of levels within each information category including syntactic, semantic, and operational levels; where the corresponding context and/or one or more other contexts and the integrity engine establish the contextual model; and (c) upon acceptance of the relationship by the integrity engine, storing automatically the relationship specified in a storage medium, permitting dynamic interaction, wherein the dynamic interaction includes storing, retrieving, manipulation of information elements, and modifications of relations with respect to the corresponding context and/or one or more other contexts. 3. The method according to claim 1 , further comprising: storing, in a function table, a list of functions in the function category, inputs to and outputs from each of the listed functions, and metadata for each of the listed functions, each function being an element permitting dynamic interaction with respect to function aspects of the context.
| 0.754944 |
7,606,428 | 1 | 12 |
1. A computer readable recording medium having encoded thereon an XMT (extensible MPEG-4 textual format) schema for DIBR data, the XMT schema comprising: a BitWrapper node schema used for graphics data compression; and a DepthImage node schema, which is used for depthimage-based model rendering, includes camera information and texture information having a depth information, defines diTexture as an element including SFDepthTextureNode as a model group, wherein the BitWrapper node schema comprises: a node element, which contains graphics data including data to be compressed and refers to SFWorldNode as a subelement; a BitWrapperEncodingParameter element; and three attributes having the names type, url, and buffer and the types SFInt32, MFUrl, and SFString, respectively, and the camera information of the depthimage node schema defines at least one of position, orientation, fieldOfView, nearPlane, farPlane, and orthographic as an attribute name, and attribute types defined in the camera information include SFVec3f, SFRotation, SFVec2f, SFFloat, SFFloat, and SFBool, respectively.
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1. A computer readable recording medium having encoded thereon an XMT (extensible MPEG-4 textual format) schema for DIBR data, the XMT schema comprising: a BitWrapper node schema used for graphics data compression; and a DepthImage node schema, which is used for depthimage-based model rendering, includes camera information and texture information having a depth information, defines diTexture as an element including SFDepthTextureNode as a model group, wherein the BitWrapper node schema comprises: a node element, which contains graphics data including data to be compressed and refers to SFWorldNode as a subelement; a BitWrapperEncodingParameter element; and three attributes having the names type, url, and buffer and the types SFInt32, MFUrl, and SFString, respectively, and the camera information of the depthimage node schema defines at least one of position, orientation, fieldOfView, nearPlane, farPlane, and orthographic as an attribute name, and attribute types defined in the camera information include SFVec3f, SFRotation, SFVec2f, SFFloat, SFFloat, and SFBool, respectively. 12. A computer readable recording medium having encoded thereon an XMT style sheet for parsing an input XMT (extensible MPEG-4 textual format) file including depth image-based representation (DIBR) data using a schema of claim 1 for the DIBR data, the XMT style sheet comprising: an XMT2BIFS style sheet used to generate a scene file for the DIBR data; and an XMT2MUX style sheet used to generate an mux file for the DIBR data.
| 0.68649 |
8,545,538 | 12 | 13 |
12. A method as in claim 1 , wherein the second portion of the bone fixation member comprises a spherical end segment.
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12. A method as in claim 1 , wherein the second portion of the bone fixation member comprises a spherical end segment. 13. A method as in claim 12 , further comprising articulating second portion of the bone fixation member within the second housing via a ball-in-socket articulation thereof.
| 0.5 |
10,109,297 | 10 | 11 |
10. A system comprising: one or more processors; and memory communicatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: causing a virtual assistant to carry out a conversation with a user; receiving user input during the conversation; determining one or more concepts for the user input by executing the instructions to: access features of a knowledge base stored in the memory, the features organized to trigger outputs according to units of vocabulary patterns arranged in the features, wherein the vocabulary patterns are stored in the memory with respective labels; substituting portions of the user input with sets of terms bearing corresponding labels that refer back to the respective labels of the knowledge base; matching the respective labels and the corresponding labels to identify a digital response to the speech input; causing the digital response to be presented to the user in real-time via the virtual assistant causing a task to be performed at least in part by the virtual assistant.
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10. A system comprising: one or more processors; and memory communicatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: causing a virtual assistant to carry out a conversation with a user; receiving user input during the conversation; determining one or more concepts for the user input by executing the instructions to: access features of a knowledge base stored in the memory, the features organized to trigger outputs according to units of vocabulary patterns arranged in the features, wherein the vocabulary patterns are stored in the memory with respective labels; substituting portions of the user input with sets of terms bearing corresponding labels that refer back to the respective labels of the knowledge base; matching the respective labels and the corresponding labels to identify a digital response to the speech input; causing the digital response to be presented to the user in real-time via the virtual assistant causing a task to be performed at least in part by the virtual assistant. 11. The system of claim 10 , wherein the task comprises providing content to the user.
| 0.818565 |
7,580,960 | 16 | 29 |
16. A machine readable medium having data stored thereon, the data, when read, causing the following: accessing from a web server, via a publicly available network path, content in a first language, including content retrieved by crawling a web site hosted on the web server via following links to additional pages; dividing the content into one or more translatable components; identifying translated components generated previously by translating previous content in the first language to previous content in a second language; determining whether each of the translatable components in the first language has corresponding one of the translated components associated with the previous content in the second language; translating at least a portion of at least one translatable component in the first language that does not have a corresponding translated component in the second language from the first language to a second language; and generating an updated content in the second language based on the translated at least a portion of the at least one translatable component, wherein the updated content in the second language is synchronized with the accessed content in the first language, and the steps of translating and generating are performed independent of the web server.
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16. A machine readable medium having data stored thereon, the data, when read, causing the following: accessing from a web server, via a publicly available network path, content in a first language, including content retrieved by crawling a web site hosted on the web server via following links to additional pages; dividing the content into one or more translatable components; identifying translated components generated previously by translating previous content in the first language to previous content in a second language; determining whether each of the translatable components in the first language has corresponding one of the translated components associated with the previous content in the second language; translating at least a portion of at least one translatable component in the first language that does not have a corresponding translated component in the second language from the first language to a second language; and generating an updated content in the second language based on the translated at least a portion of the at least one translatable component, wherein the updated content in the second language is synchronized with the accessed content in the first language, and the steps of translating and generating are performed independent of the web server. 29. The medium according to claim 16 , wherein the accessing content comprises a step of replicating a session state via at least one cookie and updated session parameters.
| 0.759777 |
4,553,205 | 4 | 7 |
4. A process of modification of source code developed for an origin system of known dialect, to produce source code for use in a destination system of differing from dialect, comprising the steps of: (a) providing a source file containing said source code, comprising a plurality of sequential source code statements incorporating parameters and macro names, each said macro name representing code to accomplish at least one basic function for data file manipulation including merge, update, extract, summarize and sort; and providing an empty output file; (b) providing said computer with a library file containing a plurality of sequential entries, each said entry comprising a macro name, one or more model statements, each said model statement comprising an expanded code statement which may incorporate one or more parameters, and a number of triplets each corresponding to one of the parameters in said expanded code statement, each said triplet specifying a condition of presence or absence of said corresponding parameter in a source code statement which inhibits passage of said expanded code to said output file; (c) sequentially fetching a source code statement from said source file, and initializing said library file; (d) sequentially fetching an entry from said library file, and comparing said macro name of said entry with said source code statement; (e) repetition of step (d) until said library file is exhausted and, if no macro name is found in said source code statement, passing said source code statement to said output file and reversion to step (c); (f) if said macro name of said entry is found in said source code statement, then sequentially fetching a model statement from said entry; (g) sequentially fetching a triplet in said model statement and a corresponding parameter in said expanded code statement of said model statement; (h) examining said source code statement for presence of said parameter; (i) repetition of steps (g) and (h) until said triplets of said model statement are exhausted and, if each said triplet does not inhibit passage of said expanded code statement to said output file, then passing said expanded code statement to said output file; (j) repetition of steps (f) through (i) until said model statements of said entry are exhausted; and (k) repetition of steps (c) through (j) until said source code statements are exhausted.
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4. A process of modification of source code developed for an origin system of known dialect, to produce source code for use in a destination system of differing from dialect, comprising the steps of: (a) providing a source file containing said source code, comprising a plurality of sequential source code statements incorporating parameters and macro names, each said macro name representing code to accomplish at least one basic function for data file manipulation including merge, update, extract, summarize and sort; and providing an empty output file; (b) providing said computer with a library file containing a plurality of sequential entries, each said entry comprising a macro name, one or more model statements, each said model statement comprising an expanded code statement which may incorporate one or more parameters, and a number of triplets each corresponding to one of the parameters in said expanded code statement, each said triplet specifying a condition of presence or absence of said corresponding parameter in a source code statement which inhibits passage of said expanded code to said output file; (c) sequentially fetching a source code statement from said source file, and initializing said library file; (d) sequentially fetching an entry from said library file, and comparing said macro name of said entry with said source code statement; (e) repetition of step (d) until said library file is exhausted and, if no macro name is found in said source code statement, passing said source code statement to said output file and reversion to step (c); (f) if said macro name of said entry is found in said source code statement, then sequentially fetching a model statement from said entry; (g) sequentially fetching a triplet in said model statement and a corresponding parameter in said expanded code statement of said model statement; (h) examining said source code statement for presence of said parameter; (i) repetition of steps (g) and (h) until said triplets of said model statement are exhausted and, if each said triplet does not inhibit passage of said expanded code statement to said output file, then passing said expanded code statement to said output file; (j) repetition of steps (f) through (i) until said model statements of said entry are exhausted; and (k) repetition of steps (c) through (j) until said source code statements are exhausted. 7. A process as claimed in claim 4 wherein said models include a mode in which passage of said expanded code statement to said output file is unconditionally conducted.
| 0.58209 |
9,229,992 | 1 | 4 |
1. A method of identifying digital content related to a portion of a block of text, the method comprising: receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; and the digital content comprises still or moving digital images; providing the block of text to a computer-implemented service that: separates the one or more words included in the block of text into one or more segments comprising phrases or individual words; searches a dataset of digital content based on the one or more segmented phrases or individual words; retrieves from the dataset one or more digital content items or identifiers associated with the one or more digital content items, wherein the digital content items are related to the one or more segmented phrases or individual words, the dataset of digital content containing licensing information regarding the one or more digital content items are licensed or unlicensed; determines from the licensing information, for each of the one or more retrieved digital content items or identifiers, whether a license has been indicated; receiving an indication from the computer-implemented service of retrieved digital content items or identifiers for which a license has been indicated; presenting the indication of retrieved digital content items or identifiers to a user; receiving a selection of one or more of the presented digital content items or identifiers from the user; and receiving for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text.
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1. A method of identifying digital content related to a portion of a block of text, the method comprising: receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; and the digital content comprises still or moving digital images; providing the block of text to a computer-implemented service that: separates the one or more words included in the block of text into one or more segments comprising phrases or individual words; searches a dataset of digital content based on the one or more segmented phrases or individual words; retrieves from the dataset one or more digital content items or identifiers associated with the one or more digital content items, wherein the digital content items are related to the one or more segmented phrases or individual words, the dataset of digital content containing licensing information regarding the one or more digital content items are licensed or unlicensed; determines from the licensing information, for each of the one or more retrieved digital content items or identifiers, whether a license has been indicated; receiving an indication from the computer-implemented service of retrieved digital content items or identifiers for which a license has been indicated; presenting the indication of retrieved digital content items or identifiers to a user; receiving a selection of one or more of the presented digital content items or identifiers from the user; and receiving for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text. 4. The method of claim 1 wherein receiving the block of text for which related digital content is to be identified comprises: providing to the user a visual indication of one or more words in the block of text for which related digital content is available; and receiving from the user a selection of one or more of the words for which the visual indication is provided.
| 0.608879 |
8,386,485 | 4 | 5 |
4. The non-transitory physical machine readable storage medium of claim 3 , wherein the method further comprises recommending at least one data item to the at least one user based on: a. feedback from at least one prior user; or b. feedback from the at least one user; or c. any combination thereof.
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4. The non-transitory physical machine readable storage medium of claim 3 , wherein the method further comprises recommending at least one data item to the at least one user based on: a. feedback from at least one prior user; or b. feedback from the at least one user; or c. any combination thereof. 5. The non-transitory physical machine readable storage medium of claim 4 , wherein the at least one recommended data item is based on: a. aggregated feedback from the at least one prior user; or b. aggregated feedback from the at least one user; or c. any combination thereof.
| 0.5 |
9,323,987 | 8 | 10 |
8. A method for detecting forgery/falsification of a homepage, comprising: generating homepage image shots of an entire screen of an accessed homepage; extracting character strings from each of the generated homepage image shots using an Optical Character Recognition (OCR) technique; comparing each of the extracted character strings with character strings required for determination of homepage forgery/falsification for determining whether the extracted character string is a normal character string or a falsified character string; determining whether the corresponding homepage has been forged/falsified, based on results of the comparison; and comparing the character string extracted using the homepage image shot, determining whether newly detected character strings are normal character strings using normality determination reference character strings based on the comparison, and classifying the character strings based on the normal character strings or the falsified character strings according to the determination, wherein classifying the character string comprises: in response to determination of the corresponding homepage is in a normal state, registering the character strings extracted from the corresponding homepage image shot using the OCR technique as a normal character string, and assigning a weight to a character string repeatedly appearing with respect to the character strings extracted from previous image shots.
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8. A method for detecting forgery/falsification of a homepage, comprising: generating homepage image shots of an entire screen of an accessed homepage; extracting character strings from each of the generated homepage image shots using an Optical Character Recognition (OCR) technique; comparing each of the extracted character strings with character strings required for determination of homepage forgery/falsification for determining whether the extracted character string is a normal character string or a falsified character string; determining whether the corresponding homepage has been forged/falsified, based on results of the comparison; and comparing the character string extracted using the homepage image shot, determining whether newly detected character strings are normal character strings using normality determination reference character strings based on the comparison, and classifying the character strings based on the normal character strings or the falsified character strings according to the determination, wherein classifying the character string comprises: in response to determination of the corresponding homepage is in a normal state, registering the character strings extracted from the corresponding homepage image shot using the OCR technique as a normal character string, and assigning a weight to a character string repeatedly appearing with respect to the character strings extracted from previous image shots. 10. The method of claim 8 , wherein determining whether the corresponding homepage has been forged/falsified comprises: determining whether the corresponding homepage having been forged/falsified, in response to determination whether the character string extracted from the homepage image shot is identical to any of falsification determination reference character strings, and determining whether the homepage is in a normal state in response to detection of a rate at which the character string extracted from the homepage image shot is identical to any of normality determination reference character strings is high.
| 0.5 |
4,464,716 | 11 | 12 |
11. The digital computer system of claim 10, wherein said output format means further comprises: output register means connected from said output register means and to said bus means for transferring said selected bits of said result into selected bit positions and providing the bits in said selected bit positions to said bus means.
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11. The digital computer system of claim 10, wherein said output format means further comprises: output register means connected from said output register means and to said bus means for transferring said selected bits of said result into selected bit positions and providing the bits in said selected bit positions to said bus means. 12. The digital computer system of claim 11, wherein said output format means further comprises: intermediate register means connected from said output multiplexer means and to said inputs of said hexidecimal ALU means for storing fourth certain of said operands expressed in an intermediate format of said third certain of said operands wherein said second certain information bits occupy said second certain information bit positions and third certain information bit positions are occupied by blank information bits, said constant memory means connected to said inputs of said gating means further providing third certain information bits to be written into said third certain information bit positions of said fourth certain of said operands, and said hexidecimal ALU means is responsive to said instructions for combining said fourth certain of said operands from said intermediate register means and said third certain information bits from said constant memory means and providing corresponding third certain of said operands.
| 0.5 |
9,002,887 | 1 | 11 |
1. A computer-implemented method for generating advertisement sets based on analysis of external referrals to a web site, the method comprising: under control of one or more computer systems configured with executable instructions, collecting information from one or more referring sources that are external to the one or more computer systems and that refer visitors of the referring sources to the website, the information corresponding to referrals to the web site by the referring sources, and each referral comprising referral information corresponding to a request for additional content that is sent responsive to user interaction with content of a corresponding referring source and that resulted in a visit to the website referred to by the corresponding referring source; for each of the referrals, identifying a referral type based at least in part upon a unique combination of a landing page type of the referral and one or more elements selected from a referring source identifier and a product identifier, the landing page type identifying a type of landing page that is displayed in response to user interaction with the referral; aggregating the referral information for each referral type, the aggregated referral information including a financial metric for the referrals; and for each referral type, determining whether the aggregated referral information satisfies an advertising criterion; when it is determined that the aggregated referral information satisfies an advertisement criterion, generating, based at least in part upon the aggregated referral information, an advertisement set for the referral type, the advertisement set having an associated link including a query string corresponding to the referral type, each referral type having at least one corresponding query string; and submitting the generated advertisement set to an order placement service.
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1. A computer-implemented method for generating advertisement sets based on analysis of external referrals to a web site, the method comprising: under control of one or more computer systems configured with executable instructions, collecting information from one or more referring sources that are external to the one or more computer systems and that refer visitors of the referring sources to the website, the information corresponding to referrals to the web site by the referring sources, and each referral comprising referral information corresponding to a request for additional content that is sent responsive to user interaction with content of a corresponding referring source and that resulted in a visit to the website referred to by the corresponding referring source; for each of the referrals, identifying a referral type based at least in part upon a unique combination of a landing page type of the referral and one or more elements selected from a referring source identifier and a product identifier, the landing page type identifying a type of landing page that is displayed in response to user interaction with the referral; aggregating the referral information for each referral type, the aggregated referral information including a financial metric for the referrals; and for each referral type, determining whether the aggregated referral information satisfies an advertising criterion; when it is determined that the aggregated referral information satisfies an advertisement criterion, generating, based at least in part upon the aggregated referral information, an advertisement set for the referral type, the advertisement set having an associated link including a query string corresponding to the referral type, each referral type having at least one corresponding query string; and submitting the generated advertisement set to an order placement service. 11. The computer-implemented method of claim 1 wherein a link associated with the generated advertisement set is a link to a page of the landing page type.
| 0.546784 |
9,633,463 | 8 | 9 |
8. The apparatus of claim 6 , wherein the gesture tracker is to accept movement or action definition for the avatar in defining the user gesture.
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8. The apparatus of claim 6 , wherein the gesture tracker is to accept movement or action definition for the avatar in defining the user gesture. 9. The apparatus of claim 8 , wherein the movement or action is a selected one of the avatar following a path defined by a trajectory; the avatar moving randomly; the avatar fading away; the avatar bouncing up and down in accordance with a pattern; or the avatar spinning relative to an axis.
| 0.5 |
5,546,507 | 4 | 11 |
4. A method for automatically generating a knowledge base in a computer from a graphical representation of a logical tree having at least one non-disjunctive branch, comprising the steps of: a) verifying the organization of said logical tree; b) verifying the content of said logical tree; c) generating a plurality of global attributes; d) creating a plurality of classes; and e) creating a plurality of rules as defined by said tree using said plurality of global attributes and said plurality of classes, wherein said rules are executable by an inference engine in a backward chaining mode; wherein said step of verifying the content of said tree comprises the steps of: b1) verifying that a valid formula is associated with each said leg; b2) verifying that a valid test is associated with each said test node; b3) verifying that a valid solution is associated with each solution node; and b4) verifying that each link node in said logical tree is linked to either a procedure or to a domain.
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4. A method for automatically generating a knowledge base in a computer from a graphical representation of a logical tree having at least one non-disjunctive branch, comprising the steps of: a) verifying the organization of said logical tree; b) verifying the content of said logical tree; c) generating a plurality of global attributes; d) creating a plurality of classes; and e) creating a plurality of rules as defined by said tree using said plurality of global attributes and said plurality of classes, wherein said rules are executable by an inference engine in a backward chaining mode; wherein said step of verifying the content of said tree comprises the steps of: b1) verifying that a valid formula is associated with each said leg; b2) verifying that a valid test is associated with each said test node; b3) verifying that a valid solution is associated with each solution node; and b4) verifying that each link node in said logical tree is linked to either a procedure or to a domain. 11. The method of claim 4 wherein said step of creating a plurality of rules comprises the steps of: e1) determining the identity of a path beginning with a root test node and ending at a solution node wherein said path comprises a plurality of path legs and a plurality of test nodes; e2) generating a first boolean evaluation statement for a given knowledge base language employing a formula associated with a first leg of said path; e3) determining if there is another leg in said path; e4) generating a second boolean evaluation statement for the given knowledge base language employing a formula associated with a next leg of said path if another leg was determined to exist in step e3; e5) concatenating said second boolean evaluation statement with said first boolean evaluation statement using a logical connector to form a new first boolean evaluation statement if another leg was determined to exist in step e3; e6) repeating steps e3, e4, and e5 until it is determine in step e3 that there is not another said test node and said leg in said path; e7) formatting a solution associated with said solution node as appropriate for the given knowledge base language; and e8) writing said first boolean evaluation statement and said formatted solution to said knowledge base.
| 0.62704 |
7,848,919 | 11 | 12 |
11. A computer readable object enabling a user to use a computer to edit a language communication sheet, wherein the computer readable object comprises a medium for recording program code, the medium comprising the following program code: a picture/text editing program for providing a picture/text editing interface, wherein the picture/text editing interface has a picture/text editing area and a function key area; a communication sheet dividing program for dividing the picture/text editing area into a plurality of language communication units; an expression database, the expression database comprising a plurality of expressions, wherein the expressions comprise expressions in the first language and expressions in the second language, and two expressions individually in the first language and the second language having substantially identical meanings are correlated, the expression database comprises a plurality of correlation indices, each correlation index correlating an expression having a substantially identical meaning in the first language and the second language with identical meaning have a same correlation index so that two vocalizations individually in the first language and the second language with substantially identical meanings are correlated; a picture database, the picture database comprising a plurality of pictures, wherein at least one of the pictures is correlated with one expression of the expression database, each picture comprises a picture file name, and picture file name corresponds to a correlation index so that a correlation is provided between the picture and an expression; a vocalization database, the vocalization database comprising a plurality of vocalizations corresponding to the plurality of expressions, wherein the vocalizations comprise vocalizations in the first language and vocalizations in the second language, and two vocalizations individually from the first language and the second language having substantially identical meanings are correlated, wherein at least one of the vocalizations is correlated with one expression of the expression database, each vocalization comprises a vocalization file name, and the vocalization file name corresponds to a correlation index so that a correlation is provided between the vocalization and an expression; a search program, wherein the search program performs at least one of the following functions: finding a corresponding picture for an expression according to the correlations between the expressions and the pictures; and finding a corresponding vocalization for an expression according to the correlations between the expressions and the vocalizations; an expression insertion program for inserting an expression into any one of the language communication units; a picture insertion program for inserting a picture into any one of the language communication units; and a language assigning program for assigning expressions in all language communication units as expressions in the first language or as expressions in the second language in one operation.
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11. A computer readable object enabling a user to use a computer to edit a language communication sheet, wherein the computer readable object comprises a medium for recording program code, the medium comprising the following program code: a picture/text editing program for providing a picture/text editing interface, wherein the picture/text editing interface has a picture/text editing area and a function key area; a communication sheet dividing program for dividing the picture/text editing area into a plurality of language communication units; an expression database, the expression database comprising a plurality of expressions, wherein the expressions comprise expressions in the first language and expressions in the second language, and two expressions individually in the first language and the second language having substantially identical meanings are correlated, the expression database comprises a plurality of correlation indices, each correlation index correlating an expression having a substantially identical meaning in the first language and the second language with identical meaning have a same correlation index so that two vocalizations individually in the first language and the second language with substantially identical meanings are correlated; a picture database, the picture database comprising a plurality of pictures, wherein at least one of the pictures is correlated with one expression of the expression database, each picture comprises a picture file name, and picture file name corresponds to a correlation index so that a correlation is provided between the picture and an expression; a vocalization database, the vocalization database comprising a plurality of vocalizations corresponding to the plurality of expressions, wherein the vocalizations comprise vocalizations in the first language and vocalizations in the second language, and two vocalizations individually from the first language and the second language having substantially identical meanings are correlated, wherein at least one of the vocalizations is correlated with one expression of the expression database, each vocalization comprises a vocalization file name, and the vocalization file name corresponds to a correlation index so that a correlation is provided between the vocalization and an expression; a search program, wherein the search program performs at least one of the following functions: finding a corresponding picture for an expression according to the correlations between the expressions and the pictures; and finding a corresponding vocalization for an expression according to the correlations between the expressions and the vocalizations; an expression insertion program for inserting an expression into any one of the language communication units; a picture insertion program for inserting a picture into any one of the language communication units; and a language assigning program for assigning expressions in all language communication units as expressions in the first language or as expressions in the second language in one operation. 12. The computer readable object as claimed in claim 11 , wherein the picture/text editing interface further comprises a picture searching area, and the picture search area inputs an expression and then finds a corresponding picture for the input expression according to the correlations between the expressions and the pictures.
| 0.626984 |
7,716,050 | 14 | 15 |
14. The computer-implemented method of claim 13 , wherein generating the acoustic word model, processing the utterance, and scoring matches is executed by a portable programmable device.
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14. The computer-implemented method of claim 13 , wherein generating the acoustic word model, processing the utterance, and scoring matches is executed by a portable programmable device. 15. The computer-implemented method of claim 14 , wherein the portable programmable device is a cellphone.
| 0.804428 |
8,914,758 | 26 | 28 |
26. The system of claim 25 wherein the one or more processors are further configured to generate a reference model based on the word-level data flow graph.
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26. The system of claim 25 wherein the one or more processors are further configured to generate a reference model based on the word-level data flow graph. 28. The system of claim 26 wherein the one or more processors are further configured to reduce the bit-level data flow graph by finding adders, to produce a reduced bit-level data flow graph.
| 0.5 |
10,095,688 | 19 | 20 |
19. A device for dynamically adapting and displaying at least one query, comprising; a processor including instructions on a non-transitory computer medium, the non-transitory computer medium constituted by one or more data storage mediums; the instructions, when executed by the processor configures the recipient device to: receive at least one query message with a plurality of query data and analyzing the query message to identify a plurality of attributes; compare at least one of the attributes from the plurality of attributes from the query message with a set of user profiles stored in the one or more storage mediums on the device; select a real-time user profile; determine a final user interface template based on the real-time user profile, the determining including analyzing a plurality of templates stored in the one or more data storage mediums using the selected real-time user profile and then selecting the final user interface template; and generating a user interface for display on the device comprised of the final user interface template, a final set of query data from the plurality of query data; and selecting the location of each element of the final set of query data within the final user interface template.
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19. A device for dynamically adapting and displaying at least one query, comprising; a processor including instructions on a non-transitory computer medium, the non-transitory computer medium constituted by one or more data storage mediums; the instructions, when executed by the processor configures the recipient device to: receive at least one query message with a plurality of query data and analyzing the query message to identify a plurality of attributes; compare at least one of the attributes from the plurality of attributes from the query message with a set of user profiles stored in the one or more storage mediums on the device; select a real-time user profile; determine a final user interface template based on the real-time user profile, the determining including analyzing a plurality of templates stored in the one or more data storage mediums using the selected real-time user profile and then selecting the final user interface template; and generating a user interface for display on the device comprised of the final user interface template, a final set of query data from the plurality of query data; and selecting the location of each element of the final set of query data within the final user interface template. 20. The device of claim 19 , the query message including a file with a filename, the filename including attributes for initial profile screening by the recipient device.
| 0.599526 |
7,962,555 | 9 | 10 |
9. The system of claim 8 , said program code further comprising: program code for, in the event said sub-thread is determined to be off-topic with respect to said discussion thread, moving said sub-thread to a new discussion thread.
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9. The system of claim 8 , said program code further comprising: program code for, in the event said sub-thread is determined to be off-topic with respect to said discussion thread, moving said sub-thread to a new discussion thread. 10. The system of claim 9 , said program code further comprising: program code for inserting a link to said new discussion thread at the former position of said sub-thread in said discussion thread.
| 0.5 |
10,156,455 | 18 | 25 |
18. A non-transitory machine readable medium storing a program for providing context aware audio prompts associated with a navigation presentation on an electronic device, the program executable by at least one processing unit, the program comprising sets of instructions for: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive first or second type of voice input, said set of instructions for determining an allowed type of audio prompt comprising sets of instructions for: based on detecting that a first audio service is currently receiving the first type of voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the second type of voice input different from the first type of audio input, determining that a non-verbal audio prompt is allowed; and based on detecting that no audio service is currently receiving the first or second type of voice input, determining that a verbal audio prompt is allowed; and providing the allowed type of audio prompt for the identified navigation instruction.
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18. A non-transitory machine readable medium storing a program for providing context aware audio prompts associated with a navigation presentation on an electronic device, the program executable by at least one processing unit, the program comprising sets of instructions for: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive first or second type of voice input, said set of instructions for determining an allowed type of audio prompt comprising sets of instructions for: based on detecting that a first audio service is currently receiving the first type of voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the second type of voice input different from the first type of audio input, determining that a non-verbal audio prompt is allowed; and based on detecting that no audio service is currently receiving the first or second type of voice input, determining that a verbal audio prompt is allowed; and providing the allowed type of audio prompt for the identified navigation instruction. 25. The non-transitory machine readable medium of claim 18 , wherein the set of instructions for providing the allowed type of audio prompt further comprises sets of instructions for: receiving a verbal prompt when verbal prompts are allowed and a service is currently playing audio on the device; pausing the audio currently played on the device; playing the verbal prompt; and resuming playing the audio by the service after the verbal prompt is played.
| 0.736385 |
8,019,713 | 24 | 27 |
24. A computer program product, comprising a memory device having computer program instructions embodied thereon to cause a computer processor to implement a method for enabling an autonomous machine to perform a task in an environment, the method comprising: receiving data collected by a distributed capture technique, said data comprising at least one class of knowledge associated with the task; automatically processing said at least one class of knowledge associated with the task to produce one or more categories of class rules , wherein said processing comprises filtering and extracting the at least one class of knowledge, and wherein the class rules comprise specific relationships within the at least one class of knowledge; and formulating a set of meta-rules that extract information from two or more categories of class rules to orchestrate an application of said class rules within the environment, each meta-rule identifying information from two or more categories of class rules; responsive to a first category of class rules missing information associated with the task, applying a meta-rule to retrieve the missing information associated with the task from a second category of class rules.
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24. A computer program product, comprising a memory device having computer program instructions embodied thereon to cause a computer processor to implement a method for enabling an autonomous machine to perform a task in an environment, the method comprising: receiving data collected by a distributed capture technique, said data comprising at least one class of knowledge associated with the task; automatically processing said at least one class of knowledge associated with the task to produce one or more categories of class rules , wherein said processing comprises filtering and extracting the at least one class of knowledge, and wherein the class rules comprise specific relationships within the at least one class of knowledge; and formulating a set of meta-rules that extract information from two or more categories of class rules to orchestrate an application of said class rules within the environment, each meta-rule identifying information from two or more categories of class rules; responsive to a first category of class rules missing information associated with the task, applying a meta-rule to retrieve the missing information associated with the task from a second category of class rules. 27. The computer program product of claim 24 , wherein said method further comprises the steps of: receiving at least one of a task command and a perceived situation within the environment; applying said meta-rules to orchestrate said application of said class rules in response to said task command or said perceived situation; applying said meta-rules to generate a set of task steps for performing the task; and sequencing said set of task steps to orchestrate an operation of the autonomous machine.
| 0.5 |
8,793,265 | 44 | 46 |
44. The client module of claim 37 , wherein the selector is further configured for causing execution of the query on the selected personalized search engine.
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44. The client module of claim 37 , wherein the selector is further configured for causing execution of the query on the selected personalized search engine. 46. The client module of claim 44 , wherein the selector further includes: an analyzer configured for analyzing quality of the search results based on one or more of the query and characteristic information for the selected personalized search engine; and a scoring module configured for scoring the selected personalized search engine based on the quality of the search results.
| 0.688834 |
9,858,928 | 1 | 4 |
1. A method comprising: transmitting, by a computing device and to a remote server, a verbal input; receiving, by the computing device and from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, by the computing device and using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, by the computing device and from the information provider as a response to the query, an information result; and presenting, through an application interface of the computing device, the information result.
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1. A method comprising: transmitting, by a computing device and to a remote server, a verbal input; receiving, by the computing device and from the remote server, a digital message that comprises a symbolic representation of the verbal input; determining, based on the symbolic representation of the verbal input, an application identifier for an application that is indicated by the symbolic representation of the verbal input; launching, by the computing device and using the application identifier, the application that is indicated by the symbolic representation of the verbal input; transmitting, using the application and to an information provider, a query that was generated based on the symbolic representation of the verbal input; obtaining, by the computing device and from the information provider as a response to the query, an information result; and presenting, through an application interface of the computing device, the information result. 4. The method of claim 1 , further comprising: after presenting the information result, receiving further input from a user, updating the information result to provide less detail; and presenting the updated information result.
| 0.5 |
7,885,426 | 9 | 11 |
9. The system of claim 5 wherein the amount of remuneration is based on a policy.
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9. The system of claim 5 wherein the amount of remuneration is based on a policy. 11. The system of claim 9 wherein the policy is specified by an owner or an operator of the system for assessing copyright fees.
| 0.5 |
8,788,886 | 5 | 6 |
5. The method as recited in claim 3 , further comprising verifying the accuracy of the memory dump operation.
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5. The method as recited in claim 3 , further comprising verifying the accuracy of the memory dump operation. 6. The method as recited in claim 5 , wherein prior to performing the memory dump operation, the method comprising writing a set of values to the one or more identified memories, and wherein verifying the accuracy of the memory dump operation comprises comparing an output bitstream of the memory dump operation to the set of values.
| 0.5 |
8,249,856 | 12 | 13 |
12. The method of claim 11 wherein the plurality of specified classes of tree-based structures include a class of fixed tree-based structures, each fixed tree-based structure including a determined head.
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12. The method of claim 11 wherein the plurality of specified classes of tree-based structures include a class of fixed tree-based structures, each fixed tree-based structure including a determined head. 13. The method of claim 12 wherein, for at least some fixed tree-based structures, the fixed tree-based structure further includes at least one child of the determined head, each child of the determined head being a complete tree-based structure without wildcards.
| 0.5 |
8,103,613 | 27 | 28 |
27. The system of claim 1 , wherein said objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user comprises: an objective occurrence data solicitation module configured to solicit data indicating incidence of at least one objective occurrence in response to a reception to a request to solicit the data indicating incidence of at least one objective occurrence, the request to solicit being remotely generated based, at least in part, on the hypothesis.
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27. The system of claim 1 , wherein said objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user comprises: an objective occurrence data solicitation module configured to solicit data indicating incidence of at least one objective occurrence in response to a reception to a request to solicit the data indicating incidence of at least one objective occurrence, the request to solicit being remotely generated based, at least in part, on the hypothesis. 28. The system of claim 27 , wherein said objective occurrence data solicitation module configured to solicit data indicating incidence of at least one objective occurrence in response to a reception to a request to solicit the data indicating incidence of at least one objective occurrence, the request to solicit being remotely generated based, at least in part, on the hypothesis comprises: an objective occurrence data solicitation module configured to solicit data indicating incidence of at least one objective occurrence in response to a request to solicit reception module receiving a request to solicit the data indicating incidence of at least one objective occurrence, the request to solicit being remotely generated based, at least in part, on the hypothesis and based and in response to the incidence of the at least one subjective user state associated with the user.
| 0.5 |
6,118,451 | 1 | 2 |
1. An operating system for use in a computer system comprising: a graphical user interface configured to generate at least one dialog box request in response to a user input provided on a display device; a plurality of dialogs each for controlling a display of and interactivity with an associated dialog box in response to a dialog box control request; and a dialog box control system, responsive to a selected one of a plurality of dialog launch modalities, said dialog box control system constructed and arranged to close open dialog boxes not having a predetermined relationship with said selected dialog box and to control generation of said one or more system calls within the operating system and to control providing said dialog box control requests generated by said graphical user interface to said plurality of dialogs to provide an associated degree of display clarity through the display of only those dialog boxes that have a predetermined relationship with an active dialog box, and an extent of system interactivity beyond said active dialog box through control of commands to the operating system, wherein said degree of display clarity and said extent of system interactivity are associated with said selected dialog box modality.
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1. An operating system for use in a computer system comprising: a graphical user interface configured to generate at least one dialog box request in response to a user input provided on a display device; a plurality of dialogs each for controlling a display of and interactivity with an associated dialog box in response to a dialog box control request; and a dialog box control system, responsive to a selected one of a plurality of dialog launch modalities, said dialog box control system constructed and arranged to close open dialog boxes not having a predetermined relationship with said selected dialog box and to control generation of said one or more system calls within the operating system and to control providing said dialog box control requests generated by said graphical user interface to said plurality of dialogs to provide an associated degree of display clarity through the display of only those dialog boxes that have a predetermined relationship with an active dialog box, and an extent of system interactivity beyond said active dialog box through control of commands to the operating system, wherein said degree of display clarity and said extent of system interactivity are associated with said selected dialog box modality. 2. The operating system of claim 1, wherein said dialog box control system logically associates the plurality of dialog boxes in a hierarchical relationship based on a location of a representative dialog launch display element used to launch each dialog box, and further wherein said dialog launch modalities comprise: a modal dialog launch modality for which said dialog box control system provides a first degree of display clarity and a first extent of system interactivity beyond said active dialog box; and a semi-modeless dialog launch modality for which said dialog box control system provides a second degree of display clarity approximately the same as said first degree of display clarity and a second extent of system interactivity beyond said active dialog box that is greater than said first extent of system interactivity.
| 0.659609 |
9,632,985 | 3 | 6 |
3. The system of claim 1 , further comprising: an interactive assessment analysis module to process the assessment data and to generate a report related to the assessment data.
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3. The system of claim 1 , further comprising: an interactive assessment analysis module to process the assessment data and to generate a report related to the assessment data. 6. The system of claim 3 , wherein subsequent to the interactive analysis module generating the report, sending the report to a third party.
| 0.675926 |
7,680,777 | 14 | 16 |
14. The method of claim 13 , wherein copying or cut-and-pasting a section of the spatial arrangement to a different location in the spatial arrangement creates a set of display elements whose corresponding queries correspond to query elements of the copied, or cut-and-pasted section, appended to a query corresponding to the location from which the section was moved.
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14. The method of claim 13 , wherein copying or cut-and-pasting a section of the spatial arrangement to a different location in the spatial arrangement creates a set of display elements whose corresponding queries correspond to query elements of the copied, or cut-and-pasted section, appended to a query corresponding to the location from which the section was moved. 16. The method of claim 14 , wherein the section of the spatial arrangement is a selected region of the display, the copying or pasting is to a different region, and the query corresponding to the Original location is the query corresponding to the different region.
| 0.521583 |
9,756,170 | 14 | 15 |
14. A method according to claim 11 further comprising: receiving input indicating a second keyword in the displayed message text; wherein the step of performing the operation generates a response message including information corresponding to said first keyword and said second keyword.
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14. A method according to claim 11 further comprising: receiving input indicating a second keyword in the displayed message text; wherein the step of performing the operation generates a response message including information corresponding to said first keyword and said second keyword. 15. A method according to claim 14 wherein the step of performing the operation associated with the indentified category comprises: opening an application associated with the first keyword and retrieving information from the application using the second keyword as data.
| 0.5 |
8,788,248 | 1 | 5 |
1. A computer implemented method for managing a flow model simulation, the computer implemented method comprising: responsive to receiving a source model created in a non-native modeler, associating annotated simulation settings with the source model to form an annotated source model, wherein the annotated simulation settings are derived from at least one of a set of user-defined simulation settings and default simulation settings; transforming the annotated source model into an internal domain model using a set of links, wherein the set of links are generated using a set of link rules that comprise instructions that govern the creation of the set of links, the set of link rules customizable for the source model, and wherein the set of links maps a set of source model elements to a set of internal domain model elements of the internal domain model; mapping results from a simulation of the internal domain model back to the source model to identify a context for the results, wherein the simulation is governed by the annotated simulation settings; and generating a target view model from the internal domain model, wherein the target view model comprises the results presented in the context of the source model.
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1. A computer implemented method for managing a flow model simulation, the computer implemented method comprising: responsive to receiving a source model created in a non-native modeler, associating annotated simulation settings with the source model to form an annotated source model, wherein the annotated simulation settings are derived from at least one of a set of user-defined simulation settings and default simulation settings; transforming the annotated source model into an internal domain model using a set of links, wherein the set of links are generated using a set of link rules that comprise instructions that govern the creation of the set of links, the set of link rules customizable for the source model, and wherein the set of links maps a set of source model elements to a set of internal domain model elements of the internal domain model; mapping results from a simulation of the internal domain model back to the source model to identify a context for the results, wherein the simulation is governed by the annotated simulation settings; and generating a target view model from the internal domain model, wherein the target view model comprises the results presented in the context of the source model. 5. The computer implemented method of claim 1 , wherein generating the target view model further comprises: conforming the target view model to the source view model.
| 0.774457 |
4,453,217 | 45 | 46 |
45. The invention set forth in claim 41 wherein each said directory name includes strings of characters and said accepted name includes strings of characters, and wherein said comparing means includes means for subdividing said directory of character strings into at least one subdirectory of character strings having bounds defined by a character of said provided character string, and means for examining said subdirectory for matches between a particular character of said provided character string and a particular character of said subdirectory character string.
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45. The invention set forth in claim 41 wherein each said directory name includes strings of characters and said accepted name includes strings of characters, and wherein said comparing means includes means for subdividing said directory of character strings into at least one subdirectory of character strings having bounds defined by a character of said provided character string, and means for examining said subdirectory for matches between a particular character of said provided character string and a particular character of said subdirectory character string. 46. The invention set forth in claim 45 wherein said subdividing and said examining means are recursively enabled by changing either the provided name character or the directory name character.
| 0.5 |
6,049,799 | 2 | 3 |
2. The apparatus of claim 1 wherein the installation utility is programmed to create a table for storing information identifying the plurality of documents, including the document, upon installation thereof.
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2. The apparatus of claim 1 wherein the installation utility is programmed to create a table for storing information identifying the plurality of documents, including the document, upon installation thereof. 3. The apparatus of claim 2, wherein the directory services database includes an object effective to identify the table.
| 0.5 |
9,922,286 | 8 | 9 |
8. A system for performing a machine-executed operation involving instructions, wherein said instructions are instructions which, when executed by one or more computing devices, cause performance of certain steps including: obtaining context data for a current context of a self-driving vehicle; determining a contextually-determined action for the self-driving vehicle based on the obtained context data and a reasoning model, wherein the reasoning model was determined based on multiple sets of training data, wherein the multiple sets of training data include multiple context data and action data pairings, and wherein determining the contextually-determined action for the self-driving vehicle comprises determining, using a premetric, closest context data in the multiple sets of training data that is closest to the current context based on the premetric and determining an action paired with the closest context data as the contextually-determined action for the self-driving vehicle, wherein the premetric is a Minkowski distance measure of order zero; determine whether performance of the contextually-determined action results in an indication of an anomaly for the self-driving vehicle; determining a portion of the reasoning model that caused the determining of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle based on the obtained context data; updating the portion of the reasoning model that caused the determining of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle based on the obtained context data in order to produce a corrected reasoning model; obtaining subsequent contextual data for a second context for the self-driving vehicle; determining a second contextually-determined action for the self-driving vehicle based on the obtained subsequent contextual data and the corrected reasoning model; and causing performance of the second contextually-determined action for the self-driving vehicle.
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8. A system for performing a machine-executed operation involving instructions, wherein said instructions are instructions which, when executed by one or more computing devices, cause performance of certain steps including: obtaining context data for a current context of a self-driving vehicle; determining a contextually-determined action for the self-driving vehicle based on the obtained context data and a reasoning model, wherein the reasoning model was determined based on multiple sets of training data, wherein the multiple sets of training data include multiple context data and action data pairings, and wherein determining the contextually-determined action for the self-driving vehicle comprises determining, using a premetric, closest context data in the multiple sets of training data that is closest to the current context based on the premetric and determining an action paired with the closest context data as the contextually-determined action for the self-driving vehicle, wherein the premetric is a Minkowski distance measure of order zero; determine whether performance of the contextually-determined action results in an indication of an anomaly for the self-driving vehicle; determining a portion of the reasoning model that caused the determining of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle based on the obtained context data; updating the portion of the reasoning model that caused the determining of the contextually-determined action that resulted in the indication of the anomaly for the self-driving vehicle based on the obtained context data in order to produce a corrected reasoning model; obtaining subsequent contextual data for a second context for the self-driving vehicle; determining a second contextually-determined action for the self-driving vehicle based on the obtained subsequent contextual data and the corrected reasoning model; and causing performance of the second contextually-determined action for the self-driving vehicle. 9. The system of claim 8 , wherein determining the portion of the reasoning model that caused the determining of the contextually-determined action that resulted in the indication of the anomaly comprises determining the previously-identified closest context data in the training data.
| 0.621011 |
8,806,440 | 1 | 4 |
1. A software validation system, comprising: a development computer, said development computer comprising an integrated software development system configured to develop a software program, said integrated software development system comprising: a set of validation rules, said set of validation rules including rules preventing the use of unsafe element definitions; interface descriptions comprising constraints on allowable input parameters; a program analyzer, as executed by a processor on said development computer, adapted to identify input parameters of an executable version of the software program in the development computer; and a validation enforcement system, said validation enforcement system being configured to: read the interface descriptions; map the interface descriptions to the identified input parameters from the program analyzer; and validate that constraints of the interface descriptions are complete with respect to the identified input parameters from the program analyzer and comply with the set of validation rules; and a server computer, said server computer being configured to receive the executable software program and the interface descriptions from the development computer once the validation enforcement system validates the constraints, said server computer comprising an execution environment in which the received software program is executed therewithin.
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1. A software validation system, comprising: a development computer, said development computer comprising an integrated software development system configured to develop a software program, said integrated software development system comprising: a set of validation rules, said set of validation rules including rules preventing the use of unsafe element definitions; interface descriptions comprising constraints on allowable input parameters; a program analyzer, as executed by a processor on said development computer, adapted to identify input parameters of an executable version of the software program in the development computer; and a validation enforcement system, said validation enforcement system being configured to: read the interface descriptions; map the interface descriptions to the identified input parameters from the program analyzer; and validate that constraints of the interface descriptions are complete with respect to the identified input parameters from the program analyzer and comply with the set of validation rules; and a server computer, said server computer being configured to receive the executable software program and the interface descriptions from the development computer once the validation enforcement system validates the constraints, said server computer comprising an execution environment in which the received software program is executed therewithin. 4. The software validation system according to claim 1 , wherein said program analyzer requests that input parameters be specified by a user and automatically generates corresponding source code for the software program.
| 0.701087 |
8,554,538 | 6 | 7 |
6. The computer program product of claim 1 , wherein the operations further comprise applying a rule to the definition to obtain at least one of the first and second nouns.
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6. The computer program product of claim 1 , wherein the operations further comprise applying a rule to the definition to obtain at least one of the first and second nouns. 7. The computer program product of claim 6 , wherein the rule defines how to truncate a word.
| 0.5 |
9,940,511 | 2 | 13 |
2. The method as recited in claim 1 , the identifying further comprising: determining a connectedness of the one or more connected components in the component map; determining whether each of the one or more connected components corresponds to a particular class of components based on the connectedness thereof, wherein the class of components to which each of the one or more connected components corresponds is selected from unknown, handwritten characters, signature, and machine-printed characters; and labeling each of the one or more connected components based on the particular class of components to which the connected component corresponds.
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2. The method as recited in claim 1 , the identifying further comprising: determining a connectedness of the one or more connected components in the component map; determining whether each of the one or more connected components corresponds to a particular class of components based on the connectedness thereof, wherein the class of components to which each of the one or more connected components corresponds is selected from unknown, handwritten characters, signature, and machine-printed characters; and labeling each of the one or more connected components based on the particular class of components to which the connected component corresponds. 13. The method as recited in claim 2 , further comprising performing a neighbor analysis to determine whether the particular class to which one or more adjacent components is identical to the particular class to which the connected component corresponds; and either confirming the particular class to which the connected component corresponds in response to determining the particular class to which the one or more adjacent components corresponds is identical to the particular class to which the connected component corresponds; or refuting a label associated with the connected component and identifying the particular class to which the connected component corresponds in response to determining the particular class to which the connected component corresponds is different than the particular class to which the one or more adjacent components correspond.
| 0.5 |
8,341,178 | 21 | 23 |
21. The computer-readable storage medium of claim 20 , wherein the workload set is captured from a production database system.
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21. The computer-readable storage medium of claim 20 , wherein the workload set is captured from a production database system. 23. The computer-readable storage medium of claim 21 , wherein the workload set is captured from at least one diagnostic trace of the production database system.
| 0.635747 |
9,122,540 | 17 | 18 |
17. The computer system of claim 16 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program.
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17. The computer system of claim 16 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program. 18. The computer system of claim 17 , wherein said parsing comprises: (i) identifying, in the first computer program, the first program statement that includes the first error and has thrown a parsing exception with respect to the first error prior to said parsing, and (ii) replacing the first program statement by a predefined program statement that is an executable equivalent program statement to the first program statement and can be parsed without throwing any parsing exception.
| 0.5 |
9,569,415 | 1 | 3 |
1. An information processing apparatus comprising: a memory; and at least one processor that executes a computer program in the memory to control the information processing apparatus to function as units comprising: an obtaining unit configured to obtain information corresponding to an editing portion which is a difference between an edited document and an original document; a specifying unit configured to specify a form of representation of objects included in the original document; a converting unit configured to convert the information corresponding to the editing portion so that a form of representation of the editing portion conforms with the specified form of representation of the objects included in the original document; and an integration unit configured to integrate the converted information corresponding to the editing portion with the original document.
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1. An information processing apparatus comprising: a memory; and at least one processor that executes a computer program in the memory to control the information processing apparatus to function as units comprising: an obtaining unit configured to obtain information corresponding to an editing portion which is a difference between an edited document and an original document; a specifying unit configured to specify a form of representation of objects included in the original document; a converting unit configured to convert the information corresponding to the editing portion so that a form of representation of the editing portion conforms with the specified form of representation of the objects included in the original document; and an integration unit configured to integrate the converted information corresponding to the editing portion with the original document. 3. The information processing apparatus according to claim 1 , further comprising a unit configured to acquire feature information indicating a form of representation of an object for each application used to create a document, wherein the specifying unit specifies the form of representation of objects included in the original document based on the acquired feature information.
| 0.5 |
8,200,695 | 5 | 6 |
5. The computing device according to claim 1 , wherein the output unit provides various kinds of user interface to a client connected through a network, and the user interface is an environment where a user inputs a query through various routes, and includes one of a first user interface where a query is input in sentence units, a second user interface where retrieved documents are used as a query, and a third user interface where a query is input by attaching or uploading a text file.
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5. The computing device according to claim 1 , wherein the output unit provides various kinds of user interface to a client connected through a network, and the user interface is an environment where a user inputs a query through various routes, and includes one of a first user interface where a query is input in sentence units, a second user interface where retrieved documents are used as a query, and a third user interface where a query is input by attaching or uploading a text file. 6. The computing device according to claim 5 , wherein, when a user attaches or uploads a predetermined file using the third user interface, the query input unit monitors a format of the attached or uploaded file to receive only a file of a specific formatthat is morphologically analyzable.
| 0.5 |
8,578,487 | 1 | 7 |
1. A computer implemented method performed by one or more processors for preventing SQL injection attacks, the method comprising the following operations: intercepting, at a first software hook, a web request associated with a web service, the first software hook associated with a first execution context of the web service; persisting at least a portion of the intercepted web request in a storage location associated with the first software hook, wherein the portion of the intercepted web request persisted in the storage location is made accessible to at least one additional execution context associated with the web service and the at least a portion of the intercepted web request is appended to one or more messages transmitted between one or more execution contexts, the intercepted web request comprising at least one string; intercepting a database query generated by at least one web service processing operation at a second software hook, the second software hook associated with execution of the generated database query, wherein the database query is generated in response to the intercepted web request, and wherein the second software hook retrieves the persisted portion of the intercepted web request; comparing at least a portion of the persisted portion of the intercepted web request with at least a portion of the intercepted database query by tokenizing the intercepted database query and comparing portions of the intercepted database query corresponding to each token to each string captured in the intercepted web request; and determining, prior to the intercepted database query being executed, whether the intercepted database query corresponds to a potential SQL injection attack if a string of the intercepted web request matches a portion of the intercepted database query and such string comprises a character that modifies a syntax of the intercepted database query.
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1. A computer implemented method performed by one or more processors for preventing SQL injection attacks, the method comprising the following operations: intercepting, at a first software hook, a web request associated with a web service, the first software hook associated with a first execution context of the web service; persisting at least a portion of the intercepted web request in a storage location associated with the first software hook, wherein the portion of the intercepted web request persisted in the storage location is made accessible to at least one additional execution context associated with the web service and the at least a portion of the intercepted web request is appended to one or more messages transmitted between one or more execution contexts, the intercepted web request comprising at least one string; intercepting a database query generated by at least one web service processing operation at a second software hook, the second software hook associated with execution of the generated database query, wherein the database query is generated in response to the intercepted web request, and wherein the second software hook retrieves the persisted portion of the intercepted web request; comparing at least a portion of the persisted portion of the intercepted web request with at least a portion of the intercepted database query by tokenizing the intercepted database query and comparing portions of the intercepted database query corresponding to each token to each string captured in the intercepted web request; and determining, prior to the intercepted database query being executed, whether the intercepted database query corresponds to a potential SQL injection attack if a string of the intercepted web request matches a portion of the intercepted database query and such string comprises a character that modifies a syntax of the intercepted database query. 7. The method of claim 1 , wherein the first software hook comprises a detour software hook.
| 0.868946 |
9,491,179 | 1 | 6 |
1. A method for detecting unauthorized user account communications, comprising: sampling messages associated with an authorized user of an account to provide a plurality of message samples; creating an authorized profile based on language patterns extracted from the plurality of message samples; comparing by a processor a language pattern extracted from a recent message with the authorized profile to determine a deviation between the language pattern extracted from the recent message and the authorized profile; determining that the recent message is an unauthorized user account communication when the deviation is not within an allowable amount of deviation, the allowable amount of deviation being based on an amount of samples in the plurality of message samples; and generating an alert indicating that the recent message is an unauthorized user account communication in response to the determining that the recent message is an unauthorized user account communication.
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1. A method for detecting unauthorized user account communications, comprising: sampling messages associated with an authorized user of an account to provide a plurality of message samples; creating an authorized profile based on language patterns extracted from the plurality of message samples; comparing by a processor a language pattern extracted from a recent message with the authorized profile to determine a deviation between the language pattern extracted from the recent message and the authorized profile; determining that the recent message is an unauthorized user account communication when the deviation is not within an allowable amount of deviation, the allowable amount of deviation being based on an amount of samples in the plurality of message samples; and generating an alert indicating that the recent message is an unauthorized user account communication in response to the determining that the recent message is an unauthorized user account communication. 6. The method as recited in claim 1 , wherein sampling the messages comprises: sampling the messages associated with the authorized user until a number of new words or phrases detected per transmission falls below a threshold.
| 0.607639 |
6,108,645 | 6 | 7 |
6. The method recited in claim 1, wherein evaluating the predicates further comprises: dynamically monitoring the evaluation of each predicate; assigning an evaluation cost to each predicate based upon the monitoring, wherein the cost of a cheap predicate requires less evaluation time and the cost of an expensive predicate requires more evaluation time; and evaluating the cheap predicates before the expensive predicates.
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6. The method recited in claim 1, wherein evaluating the predicates further comprises: dynamically monitoring the evaluation of each predicate; assigning an evaluation cost to each predicate based upon the monitoring, wherein the cost of a cheap predicate requires less evaluation time and the cost of an expensive predicate requires more evaluation time; and evaluating the cheap predicates before the expensive predicates. 7. The method recited in claim 6, wherein evaluating a predicate against a data item further comprises: accessing an index for the data items, the data items having contents and the index comprising a list of the contents; and evaluating a predicate against the list of the contents.
| 0.5 |
9,154,306 | 8 | 10 |
8. A non-transitory computer-readable storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving an indication of a first pseudonym registered by the user at the IdP in a previous session; upon verification of possession by the user of the first pseudonym, generating, by a processor, a first representation of an access token to the user for accessing the RP, wherein the first representation of the access token selectively encodes a partial disclosure based on one or more characteristics of the user known to the IdP, the partial disclosure being a confirmation of at least some characteristics required for user access at the RP, the first representation of the access token being modifiable by the user to a second representation of the access token that is unlinkable to the first representation of the access token, and the second representation of the access token remaining as a valid access token for accessing the RP; and providing the first representation of the access token to the user for accessing the RP.
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8. A non-transitory computer-readable storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving an indication of a first pseudonym registered by the user at the IdP in a previous session; upon verification of possession by the user of the first pseudonym, generating, by a processor, a first representation of an access token to the user for accessing the RP, wherein the first representation of the access token selectively encodes a partial disclosure based on one or more characteristics of the user known to the IdP, the partial disclosure being a confirmation of at least some characteristics required for user access at the RP, the first representation of the access token being modifiable by the user to a second representation of the access token that is unlinkable to the first representation of the access token, and the second representation of the access token remaining as a valid access token for accessing the RP; and providing the first representation of the access token to the user for accessing the RP. 10. The non-transitory computer-readable storage medium of claim 8 , wherein the operations further comprise: receiving the second representation of the access token, wherein the second representation of the access token is derived from the first representation of the access token by the user; and verifying the second representation of the access token without an ability to link the second representation of the access token to the first representation of the access token.
| 0.5 |
9,336,487 | 6 | 7 |
6. The method of claim 5 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes the requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, or a number of times that the object has been selected.
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6. The method of claim 5 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes the requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, or a number of times that the object has been selected. 7. The method of claim 6 , wherein the behavioral information is stored in a cookie.
| 0.5 |
4,750,044 | 1 | 3 |
1. An image editor for editing and processing image data according to attributes designated thereabout comprising: photo-electric transformation means for transforming an optical image into electric signals for individual pixels thereof; attribute memory means for storing attributes for indicating a processing method of an image signal for every unit of virtual area on an image area of a document, said virtual area being defined for each unit as one of the areas obtained by dividing the image area of a document regularly so as to have a larger area than that of one pixel; attribute designation means for indicating an attribute of each unit of virtual area to said attribute memory means; image signal processing means for processing an output signal from an individual pixel of said photo-electric transformation means according to attribute data stored in said attribute memory means of a corresponding unit of virtual area in which said pixel is included.
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1. An image editor for editing and processing image data according to attributes designated thereabout comprising: photo-electric transformation means for transforming an optical image into electric signals for individual pixels thereof; attribute memory means for storing attributes for indicating a processing method of an image signal for every unit of virtual area on an image area of a document, said virtual area being defined for each unit as one of the areas obtained by dividing the image area of a document regularly so as to have a larger area than that of one pixel; attribute designation means for indicating an attribute of each unit of virtual area to said attribute memory means; image signal processing means for processing an output signal from an individual pixel of said photo-electric transformation means according to attribute data stored in said attribute memory means of a corresponding unit of virtual area in which said pixel is included. 3. An image editor according to claim 1, wherein an attribute for indicating to make a designated area white is included among attributes and when said attribute is designated, said image processing means send signals of a constant level regardless of image data detected by the photo-electric transformation means.
| 0.697115 |
8,375,049 | 5 | 6 |
5. The method of claim 4 , further comprising: calculating the frequency of occurrence of the alternative query; calculating the user satisfaction score for the alternative query; and computing a rank for the alternative query as a function of the frequency of occurrence and the user satisfaction score, in which the alternative query is identified as the highly-ranked query based on the rank.
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5. The method of claim 4 , further comprising: calculating the frequency of occurrence of the alternative query; calculating the user satisfaction score for the alternative query; and computing a rank for the alternative query as a function of the frequency of occurrence and the user satisfaction score, in which the alternative query is identified as the highly-ranked query based on the rank. 6. The method of claim 5 , in which the user satisfaction score is based on an inverse revision frequency.
| 0.5 |
7,558,822 | 24 | 31 |
24. A computer readable storage medium storing one or more programs for execution by one or more processors of a client computer, the one or more programs including: a client assistant configured to monitor a user's browsing activities within a currently displayed document having links to one or more associated documents, including monitoring proximity of a user-controllable pointer to one or more of the links in the currently displayed document; the client assistant including instructions for identifying a link satisfying predefined criteria, the predefined criteria including proximity criteria with respect to the user-controllable pointer; and a communications interface coupled to the client assistant for transmitting to a server, prior to user selection of any respective link, a request for a document corresponding to the identified link.
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24. A computer readable storage medium storing one or more programs for execution by one or more processors of a client computer, the one or more programs including: a client assistant configured to monitor a user's browsing activities within a currently displayed document having links to one or more associated documents, including monitoring proximity of a user-controllable pointer to one or more of the links in the currently displayed document; the client assistant including instructions for identifying a link satisfying predefined criteria, the predefined criteria including proximity criteria with respect to the user-controllable pointer; and a communications interface coupled to the client assistant for transmitting to a server, prior to user selection of any respective link, a request for a document corresponding to the identified link. 31. The computer readable storage medium of claim 24 , wherein the client assistant includes instructions for determining whether a mouse-down action has been performed while a user-controllable pointer is positioned over a link in the currently displayed document.
| 0.746654 |
9,852,219 | 32 | 43 |
32. An apparatus comprising a processor and a memory storing program code, the memory and program code being configured to, with the processor, cause the apparatus to at least: cause streamed data to be stored in a file, wherein the file consists of media data and metadata enclosed separately, wherein causing the streamed data to be stored in a file includes storing in a reception hint track; identifying metadata applicable to two or more samples of the streamed data; cause at least one timed metadata track to be created based on the identified metadata, the at least one timed metadata track describing a referred media track and the reception hint track, wherein the hint track refers to samples comprising instructions for constructing packets for transmission over an indicated communication protocol, wherein the media track refers to samples formatted according to a media compression format; form at least one group from the two or more samples of the streamed data, each sample in a group having identical metadata content for a metadata type; select each sample to group box associated with the reception hint track and the media track; and find a sample group description index of a particular reception hint sample or media sample.
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32. An apparatus comprising a processor and a memory storing program code, the memory and program code being configured to, with the processor, cause the apparatus to at least: cause streamed data to be stored in a file, wherein the file consists of media data and metadata enclosed separately, wherein causing the streamed data to be stored in a file includes storing in a reception hint track; identifying metadata applicable to two or more samples of the streamed data; cause at least one timed metadata track to be created based on the identified metadata, the at least one timed metadata track describing a referred media track and the reception hint track, wherein the hint track refers to samples comprising instructions for constructing packets for transmission over an indicated communication protocol, wherein the media track refers to samples formatted according to a media compression format; form at least one group from the two or more samples of the streamed data, each sample in a group having identical metadata content for a metadata type; select each sample to group box associated with the reception hint track and the media track; and find a sample group description index of a particular reception hint sample or media sample. 43. The apparatus of claim 32 , wherein timed metadata track associates timing metadata with one or more timelines.
| 0.689189 |
7,526,073 | 11 | 12 |
11. The computer-readable medium of claim 1 , further comprising instructions that, when executed by the computer, cause the computer to connect the first telecommunications terminal to the IVR system in response to the user selecting the IVR option.
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11. The computer-readable medium of claim 1 , further comprising instructions that, when executed by the computer, cause the computer to connect the first telecommunications terminal to the IVR system in response to the user selecting the IVR option. 12. The computer-readable medium of claim 11 , wherein the prompts include a first prompt indicating a destination of the text message and a second prompt to speak the spoken message into the first telecommunications terminal.
| 0.5 |
8,635,180 | 1 | 6 |
1. A multi-hash apparatus for use with a pattern search engine, comprising: said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software, said pattern search engine having three rules comprising transition rules, default rules and initial rules, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule, wherein each said pattern search engine rule comprises a match portion, a next state portion and various flags, all of which rules may read for a given character; said pattern search engine is programmed having a rules structure in a memory that is accessed by said search engine which processes an input data stream by executing a given rules structure, wherein for each consecutive input character in said input stream, a highest-priority rule is searched in said rules structure having a test part containing conditions that match a current state and said given input character, so that the next state defined in the found rule then becomes the new state of said search engine and is used to process the next input character; said rules structure comprises a plurality of rule banks including at least one transition rule bank containing memory for storing transition rules which are read on the existing said current state and an input character; and at least one default rule bank containing memory for storing default rules which is used when no transition rule is found, each said rule bank operative to store pattern context rules; said default rules and said transition rules being indexed separately and held in separate physical data structures; said initial rule functioning when required to return said search engine to an initial state of said pattern search engine; a lookup circuit operative to perform a plurality of lookups for an input character on said plurality of rule banks, each lookup performed on either a said transition rule bank or a said default rule bank; and a multi-hash circuit operative to determine a highest priority rule from among said plurality of lookups, said highest priority rule determining the next state of said pattern search engine; multiple hashes being performed on the current character and current state, each being used respectively as a lookup to a corresponding transition rule bank , the hash results obtained therefrom being operative to output a transition rule; concurrently, only a single default hash, based on said current character is used as a lookup for a default rule bank which outputs default rules; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank.
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1. A multi-hash apparatus for use with a pattern search engine, comprising: said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software, said pattern search engine having three rules comprising transition rules, default rules and initial rules, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule, wherein each said pattern search engine rule comprises a match portion, a next state portion and various flags, all of which rules may read for a given character; said pattern search engine is programmed having a rules structure in a memory that is accessed by said search engine which processes an input data stream by executing a given rules structure, wherein for each consecutive input character in said input stream, a highest-priority rule is searched in said rules structure having a test part containing conditions that match a current state and said given input character, so that the next state defined in the found rule then becomes the new state of said search engine and is used to process the next input character; said rules structure comprises a plurality of rule banks including at least one transition rule bank containing memory for storing transition rules which are read on the existing said current state and an input character; and at least one default rule bank containing memory for storing default rules which is used when no transition rule is found, each said rule bank operative to store pattern context rules; said default rules and said transition rules being indexed separately and held in separate physical data structures; said initial rule functioning when required to return said search engine to an initial state of said pattern search engine; a lookup circuit operative to perform a plurality of lookups for an input character on said plurality of rule banks, each lookup performed on either a said transition rule bank or a said default rule bank; and a multi-hash circuit operative to determine a highest priority rule from among said plurality of lookups, said highest priority rule determining the next state of said pattern search engine; multiple hashes being performed on the current character and current state, each being used respectively as a lookup to a corresponding transition rule bank , the hash results obtained therefrom being operative to output a transition rule; concurrently, only a single default hash, based on said current character is used as a lookup for a default rule bank which outputs default rules; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank; said hash circuit being programed to store said default rules and said hash highest priority rules that apply to said pattern context search in said default rule bank; and said hash circuit being programed to store said transition rules that apply to a pattern context search in said transition rule bank; and determining a winning rule by prioritizing between a hash rule read from said default rule bank and a transition rule read from said transition rule bank. 6. The apparatus according to claim 1 , where support a plurality of transition rule lookups by transition rules referred to as multi-hash rules.
| 0.775542 |
9,479,911 | 22 | 28 |
22. A server for supporting a translation-based communication service, the system comprising: a communication unit configured to transmit and receive a signal; and one or more processors operably connected to the communication unit, the one or more processors configured to: establish, by controlling the communication unit, a communication service channel between transmitter-side terminal and a receiver-side terminal, receive, by controlling the communication unit, at least one of a text in a first language and a voice signal in the first language collected by the transmitter-side terminal with voice-related characteristic information, translate the at least one of the text in the first language and the voice signal in the first language into a second language, generate at least one of the translated text in the second language and the translated voice signal in the second language, wherein the voice-related characteristic information is used to generate the translation voice signal in the second language with a pitch and a tone similar to the voice signal in the first language, and transmit, by controlling the communication unit, the generated at least one of the translation text and the translation voice signal in the second language to the receiver-side terminal.
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22. A server for supporting a translation-based communication service, the system comprising: a communication unit configured to transmit and receive a signal; and one or more processors operably connected to the communication unit, the one or more processors configured to: establish, by controlling the communication unit, a communication service channel between transmitter-side terminal and a receiver-side terminal, receive, by controlling the communication unit, at least one of a text in a first language and a voice signal in the first language collected by the transmitter-side terminal with voice-related characteristic information, translate the at least one of the text in the first language and the voice signal in the first language into a second language, generate at least one of the translated text in the second language and the translated voice signal in the second language, wherein the voice-related characteristic information is used to generate the translation voice signal in the second language with a pitch and a tone similar to the voice signal in the first language, and transmit, by controlling the communication unit, the generated at least one of the translation text and the translation voice signal in the second language to the receiver-side terminal. 28. The server of claim 22 , wherein the one or more processors are further configured to: interrupt collection and transmission of the voice signal and operating a half-duplex mode by the receiver-side terminal in a voice signal outputting section; and support voice input standby and processing by the receiver-side terminal when it is not in voice signal outputting section.
| 0.793989 |
9,390,174 | 1 | 2 |
1. A computer implemented method for providing search results, the method comprising: parsing a search query to identify one or more words; determining, using one or more processors, an entity reference from the search query based on the one or more identified words; analyzing the entity reference to determine a type of entity reference; identifying, using one or more processors, a list of properties associated with the determined type of the entity reference from a knowledge graph; ranking, using one or more processors, the list of properties associated with the determined type of the entity reference; identifying, using one or more processors, a property for generating a presentation of search results from the ranked list of properties, based at least in part on the search query and on the type of the entity reference; determining, using one or more processors, a presentation technique associated with the property for generating a presentation; and causing to be presented, using one or more processors, search results based on the selected presentation technique.
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1. A computer implemented method for providing search results, the method comprising: parsing a search query to identify one or more words; determining, using one or more processors, an entity reference from the search query based on the one or more identified words; analyzing the entity reference to determine a type of entity reference; identifying, using one or more processors, a list of properties associated with the determined type of the entity reference from a knowledge graph; ranking, using one or more processors, the list of properties associated with the determined type of the entity reference; identifying, using one or more processors, a property for generating a presentation of search results from the ranked list of properties, based at least in part on the search query and on the type of the entity reference; determining, using one or more processors, a presentation technique associated with the property for generating a presentation; and causing to be presented, using one or more processors, search results based on the selected presentation technique. 2. The method of claim 1 , the method further comprising causing to be presented, using one or more processors, search results in an arrangement according to user input.
| 0.603286 |
7,617,078 | 41 | 49 |
41. A method for producing structured clinical information from patient records, comprising the steps of: providing a first computerized patient record comprising at least one data source containing patient information, at least some of the patient information being unstructured and at least some of the patient information being structured; providing a memory storing a domain knowledge base containing domain-specific criteria; extracting clinical information from the at least one data source by data mining using the domain-specific criteria; and creating, using a computer, structured clinical information as a function of the extracting, the structured clinical information being a summary of the unstructured and structured patient information.
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41. A method for producing structured clinical information from patient records, comprising the steps of: providing a first computerized patient record comprising at least one data source containing patient information, at least some of the patient information being unstructured and at least some of the patient information being structured; providing a memory storing a domain knowledge base containing domain-specific criteria; extracting clinical information from the at least one data source by data mining using the domain-specific criteria; and creating, using a computer, structured clinical information as a function of the extracting, the structured clinical information being a summary of the unstructured and structured patient information. 49. The method of claim 41 , wherein the created structured clinical information is stored in a database.
| 0.840909 |
8,478,186 | 1 | 2 |
1. An educational system for testing memorization, comprising: a processor; computer readable memory connected to the processor, the computer readable memory having a database recorded therein, the database including a set of digital data representing a text of a written work to be memorized by a user; a user interface coupled to the processor, the user interface including means for receiving audio input from the user; means for converting the audio input into textual data representing a sequence of spoken words, the means for converting the audio input into text being coupled to the processor; a display coupled to the processor; software stored in the memory and executable by the processor, the software having: means for selecting at least a portion of the text of the set of digital data stored in the database for testing, the portion being divided into individual words; means for comparing the textual data representing one word in the sequence of spoken words with a corresponding word of the portion stored in the database; means for instantly displaying a visual representation of the spoken word on the display if the spoken word matches the corresponding word of the portion stored in the database; and means for delaying a display of the visual representation of the spoken word on the display if the spoken word does not match the corresponding word of the portion stored in the database, and further recording an error indicator in the computer readable memory corresponding to the word.
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1. An educational system for testing memorization, comprising: a processor; computer readable memory connected to the processor, the computer readable memory having a database recorded therein, the database including a set of digital data representing a text of a written work to be memorized by a user; a user interface coupled to the processor, the user interface including means for receiving audio input from the user; means for converting the audio input into textual data representing a sequence of spoken words, the means for converting the audio input into text being coupled to the processor; a display coupled to the processor; software stored in the memory and executable by the processor, the software having: means for selecting at least a portion of the text of the set of digital data stored in the database for testing, the portion being divided into individual words; means for comparing the textual data representing one word in the sequence of spoken words with a corresponding word of the portion stored in the database; means for instantly displaying a visual representation of the spoken word on the display if the spoken word matches the corresponding word of the portion stored in the database; and means for delaying a display of the visual representation of the spoken word on the display if the spoken word does not match the corresponding word of the portion stored in the database, and further recording an error indicator in the computer readable memory corresponding to the word. 2. The educational system for testing memorization as recited in claim 1 , further comprising means for generating a report indicating the error.
| 0.5 |
7,849,030 | 12 | 15 |
12. A computer system for determining whether a claim has merit to warrant claim recovery comprising: a computer implemented means for describing a set of documents containing terms and phrases having contextual bases; a means for transforming the terms and phrases; a computer implemented means for iterating a classification process to determine rules that best classify the set of documents based upon context; a computer implemented means for incorporating the rules into an induction and knowledge representation; a thesauri taxonomy and a text summarization to classify claims; a computer implemented means for calculating a base score and one or more concept vectors to identify the selected claims that demonstrate a given probability of recovery.
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12. A computer system for determining whether a claim has merit to warrant claim recovery comprising: a computer implemented means for describing a set of documents containing terms and phrases having contextual bases; a means for transforming the terms and phrases; a computer implemented means for iterating a classification process to determine rules that best classify the set of documents based upon context; a computer implemented means for incorporating the rules into an induction and knowledge representation; a thesauri taxonomy and a text summarization to classify claims; a computer implemented means for calculating a base score and one or more concept vectors to identify the selected claims that demonstrate a given probability of recovery. 15. The computer system of claim 12 further wherein the claim is an insurance claim.
| 0.883978 |
8,401,837 | 6 | 7 |
6. A method for discriminating between linguistic and non-linguistic text, the method comprising: receiving, at a processor, input data; applying, by a processor, the input data to a word recognizer one byte at a time; identifying, by a processor, a total byte count of the input data; assigning, by a processor, the total byte count of the input data to a variable b; identifying, by a processor, a total of whitespace delimited character sequences in the input data; assigning, by a processor, the total of whitespace delimited character sequences in the input data to a variable c; identifying, by a processor, a total length of a longest whitespace delimited character sequence rejected as a non-word; assigning, by a processor, the total length of a longest whitespace delimited character sequence rejected as a non-word to a variable l; and calculating, by a processor, R=v(ceiling(b−(c−l)/c), wherein “R” is any real number.
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6. A method for discriminating between linguistic and non-linguistic text, the method comprising: receiving, at a processor, input data; applying, by a processor, the input data to a word recognizer one byte at a time; identifying, by a processor, a total byte count of the input data; assigning, by a processor, the total byte count of the input data to a variable b; identifying, by a processor, a total of whitespace delimited character sequences in the input data; assigning, by a processor, the total of whitespace delimited character sequences in the input data to a variable c; identifying, by a processor, a total length of a longest whitespace delimited character sequence rejected as a non-word; assigning, by a processor, the total length of a longest whitespace delimited character sequence rejected as a non-word to a variable l; and calculating, by a processor, R=v(ceiling(b−(c−l)/c), wherein “R” is any real number. 7. The method of claim 6 further comprising: determining whether l>R; and responsive to l>R, rejecting the input data as containing at least some non-linguistic text.
| 0.5 |
8,209,182 | 1 | 4 |
1. An emotion recognition system for automatically assessing human emotional behavior from physical phenomena indicative of the human emotional behavior, the system comprising: one or more a sensors configured to sense, the physical phenomena; and a computer processing system configured to: receive a time series of signals from the one or more sensors; identify features, in the time series of signals that are indicative of the human emotional behavior; and output a gradient, multiple-perspective assessment of the human, emotional behavior based on the identified features that includes a gradient representation of each of multiple emotional states indicated by the human emotional behavior.
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1. An emotion recognition system for automatically assessing human emotional behavior from physical phenomena indicative of the human emotional behavior, the system comprising: one or more a sensors configured to sense, the physical phenomena; and a computer processing system configured to: receive a time series of signals from the one or more sensors; identify features, in the time series of signals that are indicative of the human emotional behavior; and output a gradient, multiple-perspective assessment of the human, emotional behavior based on the identified features that includes a gradient representation of each of multiple emotional states indicated by the human emotional behavior. 4. The system of claim 1 , wherein the identification includes assessing probabilities.
| 0.954829 |
9,652,717 | 1 | 2 |
1. A method, comprising: receiving a case; generating a set of candidate answers for the case based on a corpus of information; excluding a first candidate answer from the set of candidate answers upon determining that a first attribute in the case precludes returning the first candidate answer as a valid response to the case based on a first rule, of a plurality of rules for processing supporting evidence; processing supporting evidence for the remaining candidate answers in the set of candidate answers by searching for items of evidence in the corpus of information that include passages supporting at least one candidate answer for each candidate answer in the set of candidate answers; and foregoing processing supporting evidence for the first candidate answer by refraining from searching for items of evidence in the corpus of information that include passages supporting the first candidate answer.
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1. A method, comprising: receiving a case; generating a set of candidate answers for the case based on a corpus of information; excluding a first candidate answer from the set of candidate answers upon determining that a first attribute in the case precludes returning the first candidate answer as a valid response to the case based on a first rule, of a plurality of rules for processing supporting evidence; processing supporting evidence for the remaining candidate answers in the set of candidate answers by searching for items of evidence in the corpus of information that include passages supporting at least one candidate answer for each candidate answer in the set of candidate answers; and foregoing processing supporting evidence for the first candidate answer by refraining from searching for items of evidence in the corpus of information that include passages supporting the first candidate answer. 2. The method of claim 1 , wherein the set of candidate answers specifies candidate answers for which supporting evidence will be processed, wherein supporting evidence is not processed for the first candidate answer, wherein the first rule comprises a minimum confidence threshold for a confidence score of each of the candidate answers, wherein the attribute of the first candidate answer comprises the confidence score for the first candidate answer, wherein the first candidate answer is excluded from the set of candidate answers upon determining that the confidence score for the first candidate answer is below the minimum confidence threshold, wherein foregoing processing supporting evidence for the first candidate answer is based upon the determination that the confidence score for the first candidate answer is below the minimum confidence threshold.
| 0.5 |
8,738,486 | 1 | 14 |
1. A computer-based method for discovering patterns in financial transaction card transaction data for determining group memberships of a merchant within the transaction data, said method comprising: storing transaction data within at least one database, wherein the transaction data includes data relating to merchants accepting transaction cards for payment; retrieving the transaction data by a first computer coupled to the at least one database; using at least one prediction algorithm and the retrieved transaction data to predict a plurality of group memberships of a merchant within one or more groupings of merchants wherein the algorithm is processed by the first computer; generating meta-data describing each prediction outputted by the at least one prediction algorithm, wherein the meta-data is generated by the at least one algorithm; inputting the plurality of predicted group memberships for the merchant and the meta-data describing each prediction into a data mining application executed on a second computer; assigning, by the second computer, a confidence score to each predicted group membership by the data mining application based at least in part on the predicted group memberships and the meta-data, wherein the confidence score represents a likelihood the merchant is actually associated with the corresponding predicted group membership; and outputting, by the second computer, the group membership prediction with the highest confidence score as a final membership prediction for the merchant.
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1. A computer-based method for discovering patterns in financial transaction card transaction data for determining group memberships of a merchant within the transaction data, said method comprising: storing transaction data within at least one database, wherein the transaction data includes data relating to merchants accepting transaction cards for payment; retrieving the transaction data by a first computer coupled to the at least one database; using at least one prediction algorithm and the retrieved transaction data to predict a plurality of group memberships of a merchant within one or more groupings of merchants wherein the algorithm is processed by the first computer; generating meta-data describing each prediction outputted by the at least one prediction algorithm, wherein the meta-data is generated by the at least one algorithm; inputting the plurality of predicted group memberships for the merchant and the meta-data describing each prediction into a data mining application executed on a second computer; assigning, by the second computer, a confidence score to each predicted group membership by the data mining application based at least in part on the predicted group memberships and the meta-data, wherein the confidence score represents a likelihood the merchant is actually associated with the corresponding predicted group membership; and outputting, by the second computer, the group membership prediction with the highest confidence score as a final membership prediction for the merchant. 14. A computer-based method according to claim 1 wherein using at least one prediction algorithm and the retrieved transaction data to predict a plurality of group memberships comprises: randomly sampling merchant data from a grouping of merchant data in the at least one database; computing a distribution of the numerals 1, 2, 3, 4, 5, 6, 7, 8, and 9 occurring in the first position of the transaction amount; and summarizing a transaction volume by merchant grouping.
| 0.646617 |
8,458,164 | 17 | 31 |
17. A computer-implemented method for assisting a user in creating and/or editing a query statement, wherein the computer performs the following functions comprising: visually displaying a search condition of a query statement in a first display area of the user interface; visually selecting two or more predicates of the displayed search condition for grouping; visually resolving column references and value expression datatypes in the query statement comprising: syntactic parsing of an input into an internal model form, semantic resolving of SQL expression tables and columns by associating the SQL expression tables and columns with table and column entities provided in an information catalog, and resolving remaining value expression datatypes; and visually indicating the grouping in the first display area in response to selection of the two or more predicates.
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17. A computer-implemented method for assisting a user in creating and/or editing a query statement, wherein the computer performs the following functions comprising: visually displaying a search condition of a query statement in a first display area of the user interface; visually selecting two or more predicates of the displayed search condition for grouping; visually resolving column references and value expression datatypes in the query statement comprising: syntactic parsing of an input into an internal model form, semantic resolving of SQL expression tables and columns by associating the SQL expression tables and columns with table and column entities provided in an information catalog, and resolving remaining value expression datatypes; and visually indicating the grouping in the first display area in response to selection of the two or more predicates. 31. The computer-implemented method of claim 17 , further comprising the step of receiving a query statement from an application for populating the interface.
| 0.82167 |
8,280,734 | 1 | 11 |
1. A method for titling a recording comprising: receiving a stimulus to commence a title acquisition mode; receiving an utterance representing a title during the title acquisition mode; converting the utterance into a series of textual characters using a speech to text converter, wherein the textual characters represent a lingual translation of the utterance; storing the series of textual characters representing the title in memory; automatically commencing a recording mode a predetermined time after the title acquisition mode is commenced; receiving a body of a recording during the recording mode; storing the body of the recording in memory; and automatically linking the series of textual characters representing the title with the body of the recording in memory to title the body of the recording.
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1. A method for titling a recording comprising: receiving a stimulus to commence a title acquisition mode; receiving an utterance representing a title during the title acquisition mode; converting the utterance into a series of textual characters using a speech to text converter, wherein the textual characters represent a lingual translation of the utterance; storing the series of textual characters representing the title in memory; automatically commencing a recording mode a predetermined time after the title acquisition mode is commenced; receiving a body of a recording during the recording mode; storing the body of the recording in memory; and automatically linking the series of textual characters representing the title with the body of the recording in memory to title the body of the recording. 11. The method of claim 1 , further comprising: displaying the series of textual characters representing the title to a user to confirm the series of textual characters are an accurate conversion of the utterance; and accepting a confirmation from the user that the series of textual characters representing the title is an acceptable conversion of the utterance to the user.
| 0.5 |
8,612,565 | 4 | 6 |
4. The apparatus according to claim 1 , wherein said network resource is configured to manage a virtual zero level domain (VZLD).
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4. The apparatus according to claim 1 , wherein said network resource is configured to manage a virtual zero level domain (VZLD). 6. The apparatus according to claim 4 , wherein the VZLD is a primary virtual zero level domain (PVZLD).
| 0.614815 |
7,899,812 | 1 | 4 |
1. A system for interactive browsing, wherein the system is coupled to a knowledge base and a document database, the knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents, the system comprises: term acquiring means, for acquiring one or more terms in which a user has interest; first extracting means, for extracting information relating to the one or more terms in which the user has interest from the knowledge base; second extracting means, for extracting documents containing the one or more terms in which the user has interest from the document database; a first display part in a user interface, for displaying information extracted by the first extracting means; and a second display part in the user interface, for displaying a list of the documents extracted by the second extracting means; wherein the information extracted by the first extracting means and the list of the documents extracted by the second extracting means are concurrently displayed in the same user interface such that: (i) selection by the user of a portion of the information displayed in the first display part effectuates a change in the list of documents displayed in the second display part; and (ii) selection by the user of a term in the list of documents displayed in the second display part effectuates a change in the information displayed in the first display part.
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1. A system for interactive browsing, wherein the system is coupled to a knowledge base and a document database, the knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents, the system comprises: term acquiring means, for acquiring one or more terms in which a user has interest; first extracting means, for extracting information relating to the one or more terms in which the user has interest from the knowledge base; second extracting means, for extracting documents containing the one or more terms in which the user has interest from the document database; a first display part in a user interface, for displaying information extracted by the first extracting means; and a second display part in the user interface, for displaying a list of the documents extracted by the second extracting means; wherein the information extracted by the first extracting means and the list of the documents extracted by the second extracting means are concurrently displayed in the same user interface such that: (i) selection by the user of a portion of the information displayed in the first display part effectuates a change in the list of documents displayed in the second display part; and (ii) selection by the user of a term in the list of documents displayed in the second display part effectuates a change in the information displayed in the first display part. 4. The system according to claim 1 , wherein the first display part displays the one or more terms in which the user has interest and at least one of their relations and properties by a term graph or a text description.
| 0.732927 |
8,484,142 | 14 | 15 |
14. The computer program product of claim 1 , wherein the collecting is from sources that reveal location behaviors of the user.
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14. The computer program product of claim 1 , wherein the collecting is from sources that reveal location behaviors of the user. 15. The computer program product of claim 14 , wherein the source is user location information from at least one of the web services foursquare, yelp, Google, Gowalla, and Facebook.
| 0.5 |
9,230,035 | 1 | 2 |
1. A computer-implemented method for pushing specific content for text content on a predetermined webpage, comprising: receiving, at a processing device of a computer, text content of a predetermined web page, said text content including a first text content input from a first user and reply text content input from other users in reply to the first user text content; classifying, using the processor device, both the first text content of the first user and each of the reply text content of the other users received via the predetermined webpage according to an emotional type from among a predetermined set of emotional types; and determining, by the processor device, for each said reply text content from said other users, a first matching degree between a classification result of the reply text content of a user and a classification result of the first text content, and determining a second matching degree between the classification result of the reply text content of the user and an emotion type expressed by the specific content to be pushed; and determining, by the processor device, whether the first matching degree and the second matching degree satisfy a predetermined condition; in response to that the first matching degree and the second matching degree determined satisfying a predetermined condition, combining, by the processor device, a part of the reply text content of the user with the specific content to be pushed to form pushing content specific for one or more said other users; and generating, using said processor device, an output for communication over a communications network to provide said pushing content to the web page displayed on a device associated with said one or more other users.
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1. A computer-implemented method for pushing specific content for text content on a predetermined webpage, comprising: receiving, at a processing device of a computer, text content of a predetermined web page, said text content including a first text content input from a first user and reply text content input from other users in reply to the first user text content; classifying, using the processor device, both the first text content of the first user and each of the reply text content of the other users received via the predetermined webpage according to an emotional type from among a predetermined set of emotional types; and determining, by the processor device, for each said reply text content from said other users, a first matching degree between a classification result of the reply text content of a user and a classification result of the first text content, and determining a second matching degree between the classification result of the reply text content of the user and an emotion type expressed by the specific content to be pushed; and determining, by the processor device, whether the first matching degree and the second matching degree satisfy a predetermined condition; in response to that the first matching degree and the second matching degree determined satisfying a predetermined condition, combining, by the processor device, a part of the reply text content of the user with the specific content to be pushed to form pushing content specific for one or more said other users; and generating, using said processor device, an output for communication over a communications network to provide said pushing content to the web page displayed on a device associated with said one or more other users. 2. The computer-implemented method of claim 1 , wherein the classifying the first text content and the reply text content of the user comprises at least one of: extracting, by the processor device, emotional symbols from the text content of the first user and the each said reply text content of the other users, wherein the emotional symbols belong to a predefined symbol set; and extracting, by the processor device, emotional words from the text content of the first user and from each reply text content of the other users.
| 0.5 |
10,127,316 | 1 | 7 |
1. A method comprising, by a computing device of a social-networking system: by the computing device, receiving, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; by the computing device, determining whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; by the computing device, parsing the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; by the computing device, generating a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; by the computing device, generating a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and by the computing device, sending, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user.
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1. A method comprising, by a computing device of a social-networking system: by the computing device, receiving, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; by the computing device, determining whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; by the computing device, parsing the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; by the computing device, generating a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; by the computing device, generating a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and by the computing device, sending, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user. 7. The method of claim 1 , wherein identifying the one or more first entities and the one or more first entity types referenced in the unstructured text comprises using a machine-learning topic tagger model to identify words or phrases in the unstructured text that correspond to entities and types of entities in the social graph.
| 0.690654 |
10,026,393 | 1 | 8 |
1. A system that converts text to speech, the system comprising: a response engine to generate a response text and a response intent based on user input; a non-lexical cue insertion engine to: receive the response text and the response intent representative of intended meaning to be conveyed by non-lexical cues; determine insertion points of non-lexical cues based on the received response intent; and insert a non-lexical cue at the insertion point within the response text to generate augmented text; and a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent.
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1. A system that converts text to speech, the system comprising: a response engine to generate a response text and a response intent based on user input; a non-lexical cue insertion engine to: receive the response text and the response intent representative of intended meaning to be conveyed by non-lexical cues; determine insertion points of non-lexical cues based on the received response intent; and insert a non-lexical cue at the insertion point within the response text to generate augmented text; and a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent. 8. The system of claim 1 , wherein the non-lexical cue insertion engine inserts the non-lexical cue at the insertion point by changing a portion of the response text.
| 0.734824 |
6,120,553 | 1 | 6 |
1. A system for modifying job control language (JCL) statements to optimize data storage allocations for datasets comprising: data collection means for collecting historical data concerning actual data storage space requirements of each dataset; parsing means for parsing JCL statements for references to datasets and requested data storage space allocations; and means for generating revised JCL statements containing revised requests for data storage space allocations for said datasets based on said historical data.
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1. A system for modifying job control language (JCL) statements to optimize data storage allocations for datasets comprising: data collection means for collecting historical data concerning actual data storage space requirements of each dataset; parsing means for parsing JCL statements for references to datasets and requested data storage space allocations; and means for generating revised JCL statements containing revised requests for data storage space allocations for said datasets based on said historical data. 6. The system of claim 1 wherein said historical data for each dataset includes maximum size.
| 0.821154 |
9,727,637 | 1 | 5 |
1. A method, in a question and answer (QA) system comprising a processor and a memory, for retrieving candidate answers from a corpus of documents, the method comprising: receiving, by the QA system, an input question for which an answer is sought; extracting, by the QA system, features of the input question based on a natural language processing of the input question; executing, by the QA system, a first search of the corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; executing, by the QA system, a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generating, by the QA system, query results from the subset of passages from which a set of candidate answers for the input question are identified.
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1. A method, in a question and answer (QA) system comprising a processor and a memory, for retrieving candidate answers from a corpus of documents, the method comprising: receiving, by the QA system, an input question for which an answer is sought; extracting, by the QA system, features of the input question based on a natural language processing of the input question; executing, by the QA system, a first search of the corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; executing, by the QA system, a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generating, by the QA system, query results from the subset of passages from which a set of candidate answers for the input question are identified. 5. The method of claim 1 , wherein the extracted features of the input question are identified by: identifying, by the QA system, a utility of each term in the input question; eliminating, by the QA system, zero or more terms within the input question that comprise a utility less than a predetermined value; and adding, by the QA system, the remaining terms in the input question to the extracted features.
| 0.718534 |
6,151,598 | 4 | 5 |
4. A digital dictionary in accordance with claim 1 further including a controller means for creation, updating, editing, storage, maintenance, referencing, and management of said digital dictionary.
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4. A digital dictionary in accordance with claim 1 further including a controller means for creation, updating, editing, storage, maintenance, referencing, and management of said digital dictionary. 5. A digital dictionary in accordance with claim 4, wherein the controller means comprises an operating system.
| 0.5 |
9,195,710 | 1 | 4 |
1. A computer implemented method for optimizing a query on a parallel computer system comprising the steps of: receiving a query to a database by a query optimizer; optimizing the query; determining the query utilizes multiple networks; determining whether any of the multiple networks are overloaded; and re-optimizing the query to reduce traffic on an overloaded network using an attribute table with attributes associated with the plurality of nodes and the plurality of networks to determine whether to use multiple networks to optimize the query, and using a query attribute file that holds attribute information for the query to make priority determinations when to re-optimize the query to reduce traffic on an overloaded network; the re-optimizing of the query to reduce network traffic creates a query that is sub-optimal in performance; and executing the re-optimized query.
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1. A computer implemented method for optimizing a query on a parallel computer system comprising the steps of: receiving a query to a database by a query optimizer; optimizing the query; determining the query utilizes multiple networks; determining whether any of the multiple networks are overloaded; and re-optimizing the query to reduce traffic on an overloaded network using an attribute table with attributes associated with the plurality of nodes and the plurality of networks to determine whether to use multiple networks to optimize the query, and using a query attribute file that holds attribute information for the query to make priority determinations when to re-optimize the query to reduce traffic on an overloaded network; the re-optimizing of the query to reduce network traffic creates a query that is sub-optimal in performance; and executing the re-optimized query. 4. The computer implemented method of claim 1 further comprising a query governor that is employed depending on the network loading to determine whether and how to execute the query where the query cannot be re-optimized to avoid an overloaded network.
| 0.5 |
8,117,203 | 15 | 18 |
15. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a computer processor to perform a method for automatically extracting and structuring data from a semi-structured web site, the method comprising: developing a set of experts; analyzing links and pages on the web site by the set of experts; identifying predetermined types of generic structures by the set of experts; clustering pages and textual segments within the pages based on the identified types of generic structures, the clustering being represented as a Bayesian belief network and including: adding a layer of nodes to the Bayesian belief network, the added layer of nodes including a node for every pair of samples being analyzed, at least one node in the added layer of nodes being an in-same-cluster node which represents whether or not a respective pair of samples being analyzed is in a same cluster, and the set of experts providing their output probabilistic suggestions represented as virtual-evidence nodes; collecting virtual-evidence from the set of experts; calculating a belief in a corresponding in-same-cluster node by propagating beliefs from all the virtual evidence nodes; and calculating a belief in a root clustering node by propagating beliefs from all corresponding in-same-cluster nodes; identifying, based on the clustering, semi-structured data that can be extracted; and extracting the identified semi-structured data from the web site.
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15. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a computer processor to perform a method for automatically extracting and structuring data from a semi-structured web site, the method comprising: developing a set of experts; analyzing links and pages on the web site by the set of experts; identifying predetermined types of generic structures by the set of experts; clustering pages and textual segments within the pages based on the identified types of generic structures, the clustering being represented as a Bayesian belief network and including: adding a layer of nodes to the Bayesian belief network, the added layer of nodes including a node for every pair of samples being analyzed, at least one node in the added layer of nodes being an in-same-cluster node which represents whether or not a respective pair of samples being analyzed is in a same cluster, and the set of experts providing their output probabilistic suggestions represented as virtual-evidence nodes; collecting virtual-evidence from the set of experts; calculating a belief in a corresponding in-same-cluster node by propagating beliefs from all the virtual evidence nodes; and calculating a belief in a root clustering node by propagating beliefs from all corresponding in-same-cluster nodes; identifying, based on the clustering, semi-structured data that can be extracted; and extracting the identified semi-structured data from the web site. 18. The non-transitory computer-readable storage medium of claim 15 , wherein the clustering further includes: finding a most likely value of a clustering variable after all virtual-evidence have been propagated through the Bayesian belief network by means of a greedy agglomerative search process including: consider all pairs of clusters; evaluating a set of edges connecting one sample in one cluster to another sample in another cluster to choose one pair of clusters; and merging repeatedly the chosen pair of clusters to create a larger cluster until only one cluster results.
| 0.5 |
4,592,086 | 1 | 11 |
1. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector consisting of a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern consisting of said feature vector in the same format as said input pattern for each of plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th words at a time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern v from the first word to end word V for each time point m of the input pattern, said each time point m changing from the start point to an end point M; an asymptotic calculating means to calculate a similarity measure D(v, n) given by the cumulative sum of said distances at said time points n and path information F(v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v and while changing the reference pattern v from the first word to end word for each time point m of the input pattern, said each time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of reference patterns of all the words obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(m) at said time point m, for each time point m of the input pattern, said time point m changing from the start point to end point M; an initializing means to give digit similarity measure DB(m-1) as an initial value of similarity measure and to give a time point (m-1) as an initial value of said path information at a time point m while changing the time point m of the input pattern from the start point to end point M; a decision means to obtain a recognized result at a final digit from said digit recognition category W(M) at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result on the digit previous to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern.
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1. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector consisting of a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern consisting of said feature vector in the same format as said input pattern for each of plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th words at a time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern v from the first word to end word V for each time point m of the input pattern, said each time point m changing from the start point to an end point M; an asymptotic calculating means to calculate a similarity measure D(v, n) given by the cumulative sum of said distances at said time points n and path information F(v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v and while changing the reference pattern v from the first word to end word for each time point m of the input pattern, said each time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of reference patterns of all the words obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(m) at said time point m, for each time point m of the input pattern, said time point m changing from the start point to end point M; an initializing means to give digit similarity measure DB(m-1) as an initial value of similarity measure and to give a time point (m-1) as an initial value of said path information at a time point m while changing the time point m of the input pattern from the start point to end point M; a decision means to obtain a recognized result at a final digit from said digit recognition category W(M) at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result on the digit previous to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern. 11. A continuous speech recognition system according to claim 1, wherein said asymptotic calculating means is provided with a plurality of similarity measure registers to store similarity measures at predetermined plural time points n, a plurality of path information registers to store path information at said predetermined plural time points n, a comparator to select and output a minimum value from among the values stored in said plurality of similarity measure registers and also to output a signal indicating a time point n corresponding to said selected similarity measure stored in the similarity measure register, an adder to output an added result as a similarity measure obtained newly with said minimum similarity measure as one input and the distance information obtained through said distance calculating means as another input, and means to output the contents stored in said path information register corresponding to said time point n as new path information.
| 0.5 |
8,364,664 | 1 | 2 |
1. A computing device comprising: a communication interface; memory; and processing circuitry coupled to the communication interface and to the memory, the processing circuitry, memory, and communication interface operable to: receive search criteria information from an external environment through the communication interface; process the search criteria information to obtain a first set of search results selected from at least one maxima category wherein the at least one maxima category-groups searchable data based on content similarity and a second category within each maxima category tags searchable data within that maxima category with a relative popularity indicator, wherein a first set of communication data is created to output information related to the first set of search results to the external environment through the communication interface, and wherein the at least one maxima category contains hierarchically ordered sub-maxima categories that further organize the searchable data within the at least maxima category based on content similarity; receive user interaction data from the external environment, the user interaction data indicating user interaction with a search result included in the at least one maxima category and at least one of the hierarchically ordered sub-maxima categories included in the first set of search results; process the user interaction data to identify interesting maxima categories and uninteresting maxima categories based on the user interaction data and obtain a second set of search results by favoring search results within interesting maxima categories that are identified as interesting to a user via processing of the user interaction data, wherein a second set of communication data is created to output information related to the second set of search results to the external environment through the communication interface; and iteratively repeat the process of analyzing user interaction data and selecting other sets of search results from interesting maxima and eliminating search results from uninteresting maxima so that the user interaction data allows increasingly more meaningful search results to be identified over the communication interface as time progresses.
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1. A computing device comprising: a communication interface; memory; and processing circuitry coupled to the communication interface and to the memory, the processing circuitry, memory, and communication interface operable to: receive search criteria information from an external environment through the communication interface; process the search criteria information to obtain a first set of search results selected from at least one maxima category wherein the at least one maxima category-groups searchable data based on content similarity and a second category within each maxima category tags searchable data within that maxima category with a relative popularity indicator, wherein a first set of communication data is created to output information related to the first set of search results to the external environment through the communication interface, and wherein the at least one maxima category contains hierarchically ordered sub-maxima categories that further organize the searchable data within the at least maxima category based on content similarity; receive user interaction data from the external environment, the user interaction data indicating user interaction with a search result included in the at least one maxima category and at least one of the hierarchically ordered sub-maxima categories included in the first set of search results; process the user interaction data to identify interesting maxima categories and uninteresting maxima categories based on the user interaction data and obtain a second set of search results by favoring search results within interesting maxima categories that are identified as interesting to a user via processing of the user interaction data, wherein a second set of communication data is created to output information related to the second set of search results to the external environment through the communication interface; and iteratively repeat the process of analyzing user interaction data and selecting other sets of search results from interesting maxima and eliminating search results from uninteresting maxima so that the user interaction data allows increasingly more meaningful search results to be identified over the communication interface as time progresses. 2. The computing device of claim 1 wherein additional information is processed between the computing device and the external environment after entry and processing of the search criteria information whereby this additional information is gathered interactively by the computing device from the external environment to better understand a meaning of the search criteria information.
| 0.806008 |
9,020,864 | 1 | 12 |
1. A method of creating a customized recommendation agent for a user, the method comprising: obtaining a plurality of labelled context slices derived from context data associated with a user, each labelled context slice including a time, a location and a user context label specifying at least a place inferred from the location; obtaining place features of places included in the obtained plurality of labelled context slices, the obtained place features relevant to personality traits of the user; identifying, using the plurality of labelled context slices, one or more home areas corresponding to one or more places at which the user has spent a majority of time spanned by the labelled context slices; identifying, from the places included in the plurality of labelled context slices, non-home areas comprising places that do not correspond to a home area; determining a home area statistic and non-home area statistics from the obtained place features, the home area statistic describing place features of the one or more home areas, the non-home area statistics describing place features of the non-home areas; determining, by a processor, a plurality of personality metrics based on the home area statistic and the non-home area statistics, each personality metric quantifying a position of the user on a corresponding one of a plurality of personality trait dimensions, wherein determining the plurality of personality metrics comprises applying a machine learning algorithm to the places to determine the plurality of personality metrics, the machine learning algorithm trained by: obtaining personality scores of each user of a baseline group for the plurality of metrics; obtaining baseline contextual slices for each user of the baseline group, the baseline contextual slices derived from context data associated with the user of the baseline group, the baseline contextual slices including locations and baseline contextual labels specifying places inferred from the locations; and training the machine learning algorithm to predict the personality scores using the baseline contextual labels from the baseline contextual slices obtained for each user; and creating the customized recommendation agent configured to provide a recommendation to the user responsive to the plurality of personality metrics indicating the user is likely to find value in the recommendation.
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1. A method of creating a customized recommendation agent for a user, the method comprising: obtaining a plurality of labelled context slices derived from context data associated with a user, each labelled context slice including a time, a location and a user context label specifying at least a place inferred from the location; obtaining place features of places included in the obtained plurality of labelled context slices, the obtained place features relevant to personality traits of the user; identifying, using the plurality of labelled context slices, one or more home areas corresponding to one or more places at which the user has spent a majority of time spanned by the labelled context slices; identifying, from the places included in the plurality of labelled context slices, non-home areas comprising places that do not correspond to a home area; determining a home area statistic and non-home area statistics from the obtained place features, the home area statistic describing place features of the one or more home areas, the non-home area statistics describing place features of the non-home areas; determining, by a processor, a plurality of personality metrics based on the home area statistic and the non-home area statistics, each personality metric quantifying a position of the user on a corresponding one of a plurality of personality trait dimensions, wherein determining the plurality of personality metrics comprises applying a machine learning algorithm to the places to determine the plurality of personality metrics, the machine learning algorithm trained by: obtaining personality scores of each user of a baseline group for the plurality of metrics; obtaining baseline contextual slices for each user of the baseline group, the baseline contextual slices derived from context data associated with the user of the baseline group, the baseline contextual slices including locations and baseline contextual labels specifying places inferred from the locations; and training the machine learning algorithm to predict the personality scores using the baseline contextual labels from the baseline contextual slices obtained for each user; and creating the customized recommendation agent configured to provide a recommendation to the user responsive to the plurality of personality metrics indicating the user is likely to find value in the recommendation. 12. The method of claim 1 , wherein determining the home area statistic comprises determining a proportion of visits to one of the home areas relative to total visits to the places from the plurality of labelled context slices.
| 0.698138 |
10,055,388 | 10 | 12 |
10. A computing device comprising: one or more processors; and one or more computer readable media embodying computer readable instructions which, when executed by the one or more processors, perform operations for implementing a computer-controlled method of improving response time for a webpage when determining a response to user gestures relative to content located on the webpage, the computer-controlled method comprising: at a manipulation thread, receiving an input message associated with a touch input for a user gesture relative to content on a webpage, wherein the webpage comprises: at least one dependent region in which content is processed in response to a user gesture by a user interface thread that performs full hit testing; at least one independent region in which content is processed in response to a user gesture by an independent hit test thread; wherein the content that is associated with the independent region is associated with hit testing of a display tree associated with the webpage; wherein one or more declared values are associated with one or more properties for an element of the independent region; and wherein the element is associated with the declared one or more values; in response to the touch input, the manipulation thread sending notification of the input message associated with the touch input to an independent hit test thread rather than sending the notification to the user interface thread, wherein full hit testing by the user interface thread is bypassed for any input message associated with a touch input for the independent region; and the independent hit thread performing hit testing for any independent regions associated with the touch input by traversing at least a portion of the display tree, and once the hit test is performed, the independent hit test thread then notifying the manipulation thread to initiate one or more default touch behaviors associated with the touch input.
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10. A computing device comprising: one or more processors; and one or more computer readable media embodying computer readable instructions which, when executed by the one or more processors, perform operations for implementing a computer-controlled method of improving response time for a webpage when determining a response to user gestures relative to content located on the webpage, the computer-controlled method comprising: at a manipulation thread, receiving an input message associated with a touch input for a user gesture relative to content on a webpage, wherein the webpage comprises: at least one dependent region in which content is processed in response to a user gesture by a user interface thread that performs full hit testing; at least one independent region in which content is processed in response to a user gesture by an independent hit test thread; wherein the content that is associated with the independent region is associated with hit testing of a display tree associated with the webpage; wherein one or more declared values are associated with one or more properties for an element of the independent region; and wherein the element is associated with the declared one or more values; in response to the touch input, the manipulation thread sending notification of the input message associated with the touch input to an independent hit test thread rather than sending the notification to the user interface thread, wherein full hit testing by the user interface thread is bypassed for any input message associated with a touch input for the independent region; and the independent hit thread performing hit testing for any independent regions associated with the touch input by traversing at least a portion of the display tree, and once the hit test is performed, the independent hit test thread then notifying the manipulation thread to initiate one or more default touch behaviors associated with the touch input. 12. The computing device of claim 10 , wherein the default touch behaviors comprise enabling or disabling a pinch zoom manipulation.
| 0.732794 |
10,083,227 | 1 | 11 |
1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user.
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1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user. 11. The computer system of claim 1 , wherein a single screen of the graphical user interface concurrently presents a display element for entering the search area string and a display element for entering the search string.
| 0.866426 |
9,444,793 | 3 | 4 |
3. The method of claim 1 , further comprising: receiving processed text at the intermediate module; and applying a reverse processing on said processed text to obtain original input text.
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3. The method of claim 1 , further comprising: receiving processed text at the intermediate module; and applying a reverse processing on said processed text to obtain original input text. 4. The method of claim 3 , further comprising sending said original input text to said client device.
| 0.5 |
9,672,824 | 15 | 16 |
15. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving a first voice query; generating a first recognition output; receiving a second voice query; determining from a recognition of the second voice query that the second voice query triggers a correction request; using the first recognition output and the second recognition to determine a plurality of candidate corrections including: determining a misrecognition portion of the first recognition output, and substituting the misrecognition portion with one or more candidate n-grams to form a candidate correction; scoring each candidate correction; and generating a corrected recognition output for a particular candidate correction having a score that satisfies a threshold value.
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15. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving a first voice query; generating a first recognition output; receiving a second voice query; determining from a recognition of the second voice query that the second voice query triggers a correction request; using the first recognition output and the second recognition to determine a plurality of candidate corrections including: determining a misrecognition portion of the first recognition output, and substituting the misrecognition portion with one or more candidate n-grams to form a candidate correction; scoring each candidate correction; and generating a corrected recognition output for a particular candidate correction having a score that satisfies a threshold value. 16. The one or more non-transitory computer-readable storage media of claim 15 , wherein each candidate corrected query is scored based at least in part on a query popularity of the candidate correction.
| 0.779826 |
7,697,760 | 7 | 8 |
7. The method of claim 6 , wherein the step of using the feature to select a best text word from the first and at least one additional lists further comprising the step of selecting the best text word according to at least one combination rule, the at least one combination rule using each of the at least one features.
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7. The method of claim 6 , wherein the step of using the feature to select a best text word from the first and at least one additional lists further comprising the step of selecting the best text word according to at least one combination rule, the at least one combination rule using each of the at least one features. 8. The method of claim 7 , wherein the at least one combination rule further comprises a decision tree of rules.
| 0.5 |
9,165,257 | 9 | 12 |
9. A system comprising: one or more processing units operable to execute computer-executable instructions for text entry and correction; one or more memory units coupled to the processing units; one or more touch screens having a display area, the one or more touch screens operable to receive touch input over at least a portion of the display area; storage for storing the computer-executable instructions for text entry and correction using: a text input module for receiving text input; a text entry module for associating the text input with a text entry, wherein at least a portion of the text entry is displayed using the display area of the one or more touch screens; a touch screen input module for processing: first touch screen input received from the touch screens to produce at least one selected word of the text entry, wherein the at least one selected word is identified using the first touch screen input, and second touch screen input received from the touch screens to select one of one or more suggestion candidates; a candidate generation module for producing the suggestion candidates for the at least one selected word, at least some of the suggestion candidates being produced from a candidate source, wherein the at least one selected word is automatically displayed as one of the suggestion candidates adjacent to an add-to-dictionary indicator, the at least one selected word and the indicator being displayed within a shape designating an area of the touch screens display as a button, and wherein a correction module is operable to add one or more words associated with the selected suggestion candidate to the candidate source if the selected word suggestion candidate is selected with the second touch screen input.
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9. A system comprising: one or more processing units operable to execute computer-executable instructions for text entry and correction; one or more memory units coupled to the processing units; one or more touch screens having a display area, the one or more touch screens operable to receive touch input over at least a portion of the display area; storage for storing the computer-executable instructions for text entry and correction using: a text input module for receiving text input; a text entry module for associating the text input with a text entry, wherein at least a portion of the text entry is displayed using the display area of the one or more touch screens; a touch screen input module for processing: first touch screen input received from the touch screens to produce at least one selected word of the text entry, wherein the at least one selected word is identified using the first touch screen input, and second touch screen input received from the touch screens to select one of one or more suggestion candidates; a candidate generation module for producing the suggestion candidates for the at least one selected word, at least some of the suggestion candidates being produced from a candidate source, wherein the at least one selected word is automatically displayed as one of the suggestion candidates adjacent to an add-to-dictionary indicator, the at least one selected word and the indicator being displayed within a shape designating an area of the touch screens display as a button, and wherein a correction module is operable to add one or more words associated with the selected suggestion candidate to the candidate source if the selected word suggestion candidate is selected with the second touch screen input. 12. The system of claim 9 , wherein the suggestion candidates are displayed adjacent to a touch keyboard area on the touch screen display area.
| 0.843202 |
8,065,655 | 2 | 10 |
2. The method of claim 1 wherein the representation of the ontology is a Web Ontology Language file.
|
2. The method of claim 1 wherein the representation of the ontology is a Web Ontology Language file. 10. The method of claim 2 wherein the Unified Modeling Language class diagram is created on a first server, and transformed on the first server into an Web Ontology Language file by means of an autogeneration tool; and the autogeneration tool is sent to a second server.
| 0.663342 |
8,073,818 | 9 | 13 |
9. In a computing environment, a system comprising: a query image processing subsystem that determines a query image word vector for the query image and a query pattern word vector for the query image, and a database image ranking subsystem that ranks database images with respect to similarity of each database image to the query image, including obtaining an image word vector and a pattern word vector for each database image, and, for each database image, using the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score for the similarity of each database image to the query image wherein the database image ranking subsystem uses the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score of the similarity of the database image to the query image by ranking database images according to a similarity score, for each image with the query image via visual word vector-based scoring, selecting a set of most similar images based on the ranking according to the visual word vector-based scoring, and re-ranking the set according to the similarity of each image pattern vector-based similarity score with respect to the query pattern word vector; and the system further comprising a computer processor being a functional component of the system and activated by the query image processing system and database image ranking system to facilitate determining the query image word vector and query pattern word vector and ranking the database images.
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9. In a computing environment, a system comprising: a query image processing subsystem that determines a query image word vector for the query image and a query pattern word vector for the query image, and a database image ranking subsystem that ranks database images with respect to similarity of each database image to the query image, including obtaining an image word vector and a pattern word vector for each database image, and, for each database image, using the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score for the similarity of each database image to the query image wherein the database image ranking subsystem uses the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score of the similarity of the database image to the query image by ranking database images according to a similarity score, for each image with the query image via visual word vector-based scoring, selecting a set of most similar images based on the ranking according to the visual word vector-based scoring, and re-ranking the set according to the similarity of each image pattern vector-based similarity score with respect to the query pattern word vector; and the system further comprising a computer processor being a functional component of the system and activated by the query image processing system and database image ranking system to facilitate determining the query image word vector and query pattern word vector and ranking the database images. 13. The system of claim 9 wherein the database image ranking subsystem uses the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for a given database image, and the pattern word vector for the given database image to determine a score for similarity of the given database image to the query image by merging the image word vector and pattern word vector of an image into a first merged vector, merging the query image word vector and with the query pattern word vector into a second merged vector, and determining a similarity score based on similarity between the first merged vector and the second merged vector.
| 0.538514 |
8,275,605 | 1 | 5 |
1. A hardware computer readable storage media having information and instructions thereon for a computer-implemented machine translation system to translate text from a first language to a second language, the information and instructions comprising: a plurality of mappings, each mapping indicative of associating a dependency structure of the first language with a dependency structure of the second language, wherein at least some of the mappings correspond to dependency structures of the first language having varying context with some common elements, wherein first and second dependency structures of the first language have at least one common word but the second dependency structure includes an additional word providing additional context and associated dependency structures of the second language to the dependency structures of the first language also having varying context with some common elements, wherein third and fourth dependency structure of the second language are associated with the first and second dependency structures of the first language, respectively, and have at least one common word but the fourth dependency structure includes a further word providing additional context; and a module that receives input text in a first language having the second dependency and outputs output text having the fourth dependency structure in a second language based on accessing the plurality of mappings.
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1. A hardware computer readable storage media having information and instructions thereon for a computer-implemented machine translation system to translate text from a first language to a second language, the information and instructions comprising: a plurality of mappings, each mapping indicative of associating a dependency structure of the first language with a dependency structure of the second language, wherein at least some of the mappings correspond to dependency structures of the first language having varying context with some common elements, wherein first and second dependency structures of the first language have at least one common word but the second dependency structure includes an additional word providing additional context and associated dependency structures of the second language to the dependency structures of the first language also having varying context with some common elements, wherein third and fourth dependency structure of the second language are associated with the first and second dependency structures of the first language, respectively, and have at least one common word but the fourth dependency structure includes a further word providing additional context; and a module that receives input text in a first language having the second dependency and outputs output text having the fourth dependency structure in a second language based on accessing the plurality of mappings. 5. The hardware computer readable storage media of claim 1 wherein the information includes information indicative of an extent of a complete alignment of the dependency structures of the first language originating from a larger dependency structure.
| 0.5 |
7,945,929 | 12 | 17 |
12. The system of claim 11 , wherein the processor is configured to combine at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category by: combining the identified simple categories into groups of two or more of the identified simple categories; and determining, for each of the groups of simple categories, whether the respective group is contained within a list of supported categories; wherein the at least one combination category comprises one of the groups of simple categories contained within the list of supported categories.
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12. The system of claim 11 , wherein the processor is configured to combine at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category by: combining the identified simple categories into groups of two or more of the identified simple categories; and determining, for each of the groups of simple categories, whether the respective group is contained within a list of supported categories; wherein the at least one combination category comprises one of the groups of simple categories contained within the list of supported categories. 17. The system of claim 12 , wherein the processor is further configured to assign the at least one combination category to the at least one program listing.
| 0.739203 |
5,555,367 | 11 | 13 |
11. A system according to claim 10, wherein the a series of transformation performed in the performing means includes operations such as retain, duplicate, merge, constrain, and restrict.
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11. A system according to claim 10, wherein the a series of transformation performed in the performing means includes operations such as retain, duplicate, merge, constrain, and restrict. 13. A system according to claim 11, wherein the duplicate operation includes duplicating classes and associations that specify the query.
| 0.599415 |
9,436,918 | 3 | 4 |
3. The process of claim 1 , further comprising the actions of: identifying the candidate text span in the ranked list of re-scored candidate text spans having the highest score; and displaying said identified candidate text span to the user as a prediction of the text span that they intended to select.
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3. The process of claim 1 , further comprising the actions of: identifying the candidate text span in the ranked list of re-scored candidate text spans having the highest score; and displaying said identified candidate text span to the user as a prediction of the text span that they intended to select. 4. The process of claim 3 , wherein said identified candidate text span comprises a phrase comprising two or more words.
| 0.5 |
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