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8,856,052 | 9 | 10 | 9. The method as claimed in claim 2 , wherein said source domain includes multi-labeled text document examples, and said abbreviated target domain text documents include one or more of: a web page of limited character length, a mobile text message of limited character length, an instant message of limited character length, an online blog of limited character length, a tweet, a weblink, a paper abstract, and, a newsfeed. | 9. The method as claimed in claim 2 , wherein said source domain includes multi-labeled text document examples, and said abbreviated target domain text documents include one or more of: a web page of limited character length, a mobile text message of limited character length, an instant message of limited character length, an online blog of limited character length, a tweet, a weblink, a paper abstract, and, a newsfeed. 10. The method as claimed in claim 9 , wherein a source domain dataset includes one or more webpages tagged using a social bookmarking tool; and, said abbreviated target domain text documents of limited character length ranges from between 20-140 characters. | 0.835038 |
8,694,324 | 1 | 7 | 1. A method comprising: training a spoken dialog system using task-independent call-types of a previous application; recognizing a user utterance using the spoken dialog system, to yield a recognized user utterance; determining an acceptance threshold and a rejection threshold based on an entity referenced in the recognized user utterance; classifying the recognized user utterance, to yield a classification, where the classification meets one of: the rejection threshold, the acceptance threshold, and both the rejection threshold and the acceptance threshold; when the classification meets the acceptance threshold acting according to a call-type associated with the classification; and when the classification meets the rejection threshold, and does not meet the acceptance threshold, transcribing the recognized user utterance and using the recognized user utterance for further training of the spoken dialog system. | 1. A method comprising: training a spoken dialog system using task-independent call-types of a previous application; recognizing a user utterance using the spoken dialog system, to yield a recognized user utterance; determining an acceptance threshold and a rejection threshold based on an entity referenced in the recognized user utterance; classifying the recognized user utterance, to yield a classification, where the classification meets one of: the rejection threshold, the acceptance threshold, and both the rejection threshold and the acceptance threshold; when the classification meets the acceptance threshold acting according to a call-type associated with the classification; and when the classification meets the rejection threshold, and does not meet the acceptance threshold, transcribing the recognized user utterance and using the recognized user utterance for further training of the spoken dialog system. 7. The method of claim 1 , wherein the method is performed by an automated hidden human. | 0.9 |
8,380,121 | 9 | 10 | 9. The method of claim 8 , further comprising tracking a first metric associated with said learning outcome, wherein said tracking said first metric comprises recording an amount of time spent by said student in association with said at least one of a learning content item and an assessment content item relative to said learning outcome. | 9. The method of claim 8 , further comprising tracking a first metric associated with said learning outcome, wherein said tracking said first metric comprises recording an amount of time spent by said student in association with said at least one of a learning content item and an assessment content item relative to said learning outcome. 10. The method of claim 9 , wherein said receiving a selection of a learning outcome comprises receiving a selection of at least one of comprehension of a standardized instructional content item, acquisition of a standardized skill, knowledge of a course content item, and mastery of a standardized learning outcome. | 0.952367 |
9,672,253 | 1 | 2 | 1. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document and a second document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining a second data measure for the second document, wherein the second data measure is indicative of an amount of data usage required to load the second document; determining that the first document is similar to the second document; in response to determining that the first document is similar to the second document, ranking the first document relative to the second document based on the first data measure and the second data measure; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing a second search result that is based on the second document, and providing the first search result and the second search result based on the ranking. | 1. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document and a second document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining a second data measure for the second document, wherein the second data measure is indicative of an amount of data usage required to load the second document; determining that the first document is similar to the second document; in response to determining that the first document is similar to the second document, ranking the first document relative to the second document based on the first data measure and the second data measure; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing a second search result that is based on the second document, and providing the first search result and the second search result based on the ranking. 2. The method of claim 1 , wherein ranking the first document relative to the second document based on the first data measure and the second data measure comprises: determining the first data measure is indicative of less data usage than the second data measure; and ranking the first document more prominently than the second document based on the first data measure being indicative of less data usage than the second data measure. | 0.676383 |
8,799,294 | 18 | 20 | 18. The method of claim 14 , wherein the step of using the created hierarchy further comprises using the created hierarchy to maximize the recall of a tag cloud comprising a plurality of tags. | 18. The method of claim 14 , wherein the step of using the created hierarchy further comprises using the created hierarchy to maximize the recall of a tag cloud comprising a plurality of tags. 20. The method of claim 18 , wherein the method of using the created hierarchy further comprises selecting root tags in the created hierarchy to be included in the tag cloud. | 0.951987 |
9,582,639 | 1 | 29 | 1. A computer-implemented method of collecting first and second DNA profile data using first and second different DNA typing technologies about an unidentified remain and first and second DNA profile data of the same first and second DNA typing technologies of each of a selected first and a selected second family member genetically related to a hypothesized identity of the unidentified remain and the first and the second family members being selected via application of a family member selection rule base considering available members of the family for DNA typing, the family member data including first and second DNA profile data obtained from a specimen associated with a selected typed family member and a genetic relationship existing among each of the first and the second selected family member and the hypothesized identity of the unidentified remain, the method for determining one of a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the selected first and second typed family member and that the unidentified remain can be excluded as not consistent with the first and the second selected typed family member, the method for implementation on telecommunications computer apparatus comprising a processor, an input device coupled to the processor comprising one of a touch screen of a display, a camera, a keyboard and a bar code reader for reading one and two dimension bar codes, an output device coupled to the processor comprising a display, a telecommunications interface coupled to the processor, and a memory for storing the first and the second DNA profile data obtained from said unidentified remain and said first and said second DNA profile data obtained from each specimen of said first selected and said second selected typed family member, the memory coupled to the processor, the computer-implemented method comprising: (a) storing the first and the second DNA profile data obtained from typing said unidentified remain using the first and the second DNA typing technologies in said memory via said bar code reader input device for reading a one dimension bar code uniquely identifying the unidentified remain and two different associated two dimension bar codes for transformation to the first and the second DNA profile data of the two different typing technologies for the unidentified remain; (b) storing a genetic relationship in said memory among said hypothesized identity of said unidentified remain of said missing person and each of said first and said second selected family member and family member and hypothesized identity identification data input via said input device; (c) storing said first and said second DNA profile data of each of the first and the second selected family member in said memory, each of the first and the second selected family members uniquely identified by a one dimension bar code and their associated first and second DNA profile data represented by two different two dimension bar codes being uniquely transformable into first and second DNA profile data of the first and the second DNA typing technologies, said first and said second DNA profile data obtained from the specimen associated with each of the first and the second selected typed family member and storing said first and said second DNA profile data from the unidentified remain, said first and said second family member DNA profile data for each of said first and said second selected typed family member being identified with a different two-dimensional bar code representing the same first and second typing technologies used for typing the unidentified remain; (d) displaying a family pedigree representing genetic relationships among the first and the second family members and the hypothesized identity of the unidentified remain, the family pedigree displayed on said display, said family pedigree being responsive to input received by said input device, said input causing information about a selected family member to be displayed including the stored DNA profile data associated with the selected family member, an identity being input by the input device and at least one of a first and a second type of collected DNA profile data each indicated by a predetermined color, each type comprising one of STR, Y-STR and mitochondrial DNA, at least one DNA typing technology comprising STR; (e) evaluating the genetic consistency of said stored genetic relationship by computing a pedigree likelihood ratio for each of said stored first and said second DNA typing technologies using said DNA profile data of each of said selected typed family member with said first and said second DNA profile data of said unidentified remain and a joint likelihood ratio computed as the product of the pedigree likelihood ratios; and (f) using the computed joint likelihood ratio to output a decision whether said stored genetic relationship and said stored first and said second DNA profile data obtained from the specimen associated with the first and second selected typed family member and said unidentified remain are consistent and outputting a decision of whether there exists one of said genetic relationship among the first and second family members and the hypothesized identity of the unidentified remain and exclusion of said genetic relationship among the first and second family members and the unidentified remain, including computing of the pedigree likelihood ratio according to evaluating the genetic consistency using a modified Elston Stewart algorithm for determining a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the typed first and second second family member or can be excluded as not consistent with the typed first and second selected available family member, the modification expressing a probability of mutation. | 1. A computer-implemented method of collecting first and second DNA profile data using first and second different DNA typing technologies about an unidentified remain and first and second DNA profile data of the same first and second DNA typing technologies of each of a selected first and a selected second family member genetically related to a hypothesized identity of the unidentified remain and the first and the second family members being selected via application of a family member selection rule base considering available members of the family for DNA typing, the family member data including first and second DNA profile data obtained from a specimen associated with a selected typed family member and a genetic relationship existing among each of the first and the second selected family member and the hypothesized identity of the unidentified remain, the method for determining one of a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the selected first and second typed family member and that the unidentified remain can be excluded as not consistent with the first and the second selected typed family member, the method for implementation on telecommunications computer apparatus comprising a processor, an input device coupled to the processor comprising one of a touch screen of a display, a camera, a keyboard and a bar code reader for reading one and two dimension bar codes, an output device coupled to the processor comprising a display, a telecommunications interface coupled to the processor, and a memory for storing the first and the second DNA profile data obtained from said unidentified remain and said first and said second DNA profile data obtained from each specimen of said first selected and said second selected typed family member, the memory coupled to the processor, the computer-implemented method comprising: (a) storing the first and the second DNA profile data obtained from typing said unidentified remain using the first and the second DNA typing technologies in said memory via said bar code reader input device for reading a one dimension bar code uniquely identifying the unidentified remain and two different associated two dimension bar codes for transformation to the first and the second DNA profile data of the two different typing technologies for the unidentified remain; (b) storing a genetic relationship in said memory among said hypothesized identity of said unidentified remain of said missing person and each of said first and said second selected family member and family member and hypothesized identity identification data input via said input device; (c) storing said first and said second DNA profile data of each of the first and the second selected family member in said memory, each of the first and the second selected family members uniquely identified by a one dimension bar code and their associated first and second DNA profile data represented by two different two dimension bar codes being uniquely transformable into first and second DNA profile data of the first and the second DNA typing technologies, said first and said second DNA profile data obtained from the specimen associated with each of the first and the second selected typed family member and storing said first and said second DNA profile data from the unidentified remain, said first and said second family member DNA profile data for each of said first and said second selected typed family member being identified with a different two-dimensional bar code representing the same first and second typing technologies used for typing the unidentified remain; (d) displaying a family pedigree representing genetic relationships among the first and the second family members and the hypothesized identity of the unidentified remain, the family pedigree displayed on said display, said family pedigree being responsive to input received by said input device, said input causing information about a selected family member to be displayed including the stored DNA profile data associated with the selected family member, an identity being input by the input device and at least one of a first and a second type of collected DNA profile data each indicated by a predetermined color, each type comprising one of STR, Y-STR and mitochondrial DNA, at least one DNA typing technology comprising STR; (e) evaluating the genetic consistency of said stored genetic relationship by computing a pedigree likelihood ratio for each of said stored first and said second DNA typing technologies using said DNA profile data of each of said selected typed family member with said first and said second DNA profile data of said unidentified remain and a joint likelihood ratio computed as the product of the pedigree likelihood ratios; and (f) using the computed joint likelihood ratio to output a decision whether said stored genetic relationship and said stored first and said second DNA profile data obtained from the specimen associated with the first and second selected typed family member and said unidentified remain are consistent and outputting a decision of whether there exists one of said genetic relationship among the first and second family members and the hypothesized identity of the unidentified remain and exclusion of said genetic relationship among the first and second family members and the unidentified remain, including computing of the pedigree likelihood ratio according to evaluating the genetic consistency using a modified Elston Stewart algorithm for determining a likelihood that the unidentified remain corresponds to a missing person genetically related to each of the typed first and second second family member or can be excluded as not consistent with the typed first and second selected available family member, the modification expressing a probability of mutation. 29. The method of claim 1 wherein said first and said second DNA profile data comprises DNA profile data of one of a selected known available individual member of a family by genetic relationship to another known available individual member of the family and having a genetic family relationship to hypothesized identity of an unidentified remain of a missing person using the same two typing technologies for the first and second selected available family members and for the unidentified remain, one set of first and second DNA profile data taken via STR typing being uniquely transformable to loci data by a two dimension bar code by the input device. | 0.500763 |
8,078,631 | 1 | 2 | 1. A method for comparing query-related information, comprising: providing a data abstraction layer which defines one or more logical fields, wherein a definition for each logical field specifies (i) a name, and (ii) an access method that maps the logical field to data in an underlying data repository; receiving from a first user a first set of abstract queries, associated with the first user, composed from the one or more logical fields defined in the data abstraction layer, wherein the first set of abstract queries comprises more than one query; receiving from a second user, different from the first user, a second set of abstract queries, associated with the second user, composed from the one or more logical fields defined in the data abstraction layer, wherein the second set of abstract queries comprises more than one query; comparing at least one query in the first set of abstract queries with at least one query in the second set of abstract queries to determine a degree of similarity between the first set of abstract queries and the second set of abstract queries; and issuing a notification of the degree of similarity. | 1. A method for comparing query-related information, comprising: providing a data abstraction layer which defines one or more logical fields, wherein a definition for each logical field specifies (i) a name, and (ii) an access method that maps the logical field to data in an underlying data repository; receiving from a first user a first set of abstract queries, associated with the first user, composed from the one or more logical fields defined in the data abstraction layer, wherein the first set of abstract queries comprises more than one query; receiving from a second user, different from the first user, a second set of abstract queries, associated with the second user, composed from the one or more logical fields defined in the data abstraction layer, wherein the second set of abstract queries comprises more than one query; comparing at least one query in the first set of abstract queries with at least one query in the second set of abstract queries to determine a degree of similarity between the first set of abstract queries and the second set of abstract queries; and issuing a notification of the degree of similarity. 2. The method of claim 1 , further comprising: executing the at least one query in the first set of abstract queries and receiving a first plurality of results; executing the at least one query in the second set of abstract queries and receiving a second plurality of results; and adjusting the degree of similarity between the first set of abstract queries and the second set of abstract queries based on a determined degree of similarity between the first plurality of results and the second plurality of results. | 0.800233 |
8,213,719 | 13 | 19 | 13. A computer-readable storage device comprising instructions for controlling a computer system to edit 2D structures using a natural input method, wherein the instructions, upon execution, cause a processor to perform actions comprising: receiving from a typeset application a typeset format representation of a 2D object; converting the 2D object from the typeset format representation to a digital ink representation of the 2D object; providing the converted digital ink representation of the 2D object to a natural input application, wherein the natural input application includes at least one recognizer for a specific 2D domain; receiving modified typeset format representation of the 2D object from the recognizer of the natural input application; and providing the modified typeset format representation of the 2D object to the typeset application. | 13. A computer-readable storage device comprising instructions for controlling a computer system to edit 2D structures using a natural input method, wherein the instructions, upon execution, cause a processor to perform actions comprising: receiving from a typeset application a typeset format representation of a 2D object; converting the 2D object from the typeset format representation to a digital ink representation of the 2D object; providing the converted digital ink representation of the 2D object to a natural input application, wherein the natural input application includes at least one recognizer for a specific 2D domain; receiving modified typeset format representation of the 2D object from the recognizer of the natural input application; and providing the modified typeset format representation of the 2D object to the typeset application. 19. The device of claim 13 wherein the typeset application is a word processing application for editing documents that include 2D objects. | 0.778135 |
7,945,600 | 1 | 10 | 1. A method comprising: generating, by a computer system, a summary representation for each electronic document in a plurality of electronic documents, the summary representation representing a summary of content of the electronic document; filtering, by the computer system, the plurality of electronic documents based upon their summary representations to generate a filtered subset; organizing, by the computer system, the electronic documents in the filtered subset into a hierarchical collection of folders, the organizing comprising: determining similarity metrics between the electronic documents in the filtered subset based upon their summary representations; determining concepts associated with the electronic documents in the filtered subset based upon their summary representations; and grouping the electronic documents in the filtered subset into the hierarchical collection of folders based upon the similarity metrics and the concepts; and assigning, by the computer system based upon a set of rules pertaining to document similarity, a number to each electronic document in the filtered subset by traversing the hierarchical collection of folders, such that when the electronic documents in the filtered subset are sorted based upon the assigned numbers to generate a sorted list of electronic documents, related electronic documents occur consecutively in the sorted list of electronic documents. | 1. A method comprising: generating, by a computer system, a summary representation for each electronic document in a plurality of electronic documents, the summary representation representing a summary of content of the electronic document; filtering, by the computer system, the plurality of electronic documents based upon their summary representations to generate a filtered subset; organizing, by the computer system, the electronic documents in the filtered subset into a hierarchical collection of folders, the organizing comprising: determining similarity metrics between the electronic documents in the filtered subset based upon their summary representations; determining concepts associated with the electronic documents in the filtered subset based upon their summary representations; and grouping the electronic documents in the filtered subset into the hierarchical collection of folders based upon the similarity metrics and the concepts; and assigning, by the computer system based upon a set of rules pertaining to document similarity, a number to each electronic document in the filtered subset by traversing the hierarchical collection of folders, such that when the electronic documents in the filtered subset are sorted based upon the assigned numbers to generate a sorted list of electronic documents, related electronic documents occur consecutively in the sorted list of electronic documents. 10. The method of claim 1 wherein grouping the electronic documents in the filtered subset comprises: generating the hierarchical collection of folders using an existing folder organization comprising a set of folders, the hierarchical collection of folders comprising at least the set of folders, wherein a first document from the filtered subset that is related to a first concept is placed in a folder from the existing folder organization if the existing folder organization comprises a folder representing the first concept, and wherein a new folder is created to store the first document if the existing folder organization does not comprise a folder representing the first concept. | 0.704467 |
9,275,147 | 12 | 14 | 12. A system of one or more computers configured to perform operations comprising: receiving a search string from a user device; selecting a plurality of candidate query suggestions based on the search string; determining, for each candidate query suggestion, a probability for the candidate query suggestion based on a count in a query log of the number of times that the plurality of candidate query suggestions were submitted as search queries and a count in the query log of the number of times that the candidate query was submitted as a search query; determining, by one or more processors, a measure of query completeness for the search string based on an aggregation of the determined probabilities, including determining a probability of receiving the N most probable query suggestions for the search string, wherein N is an integer greater than zero; comparing the measure of query completeness to a threshold measure of query completeness; and providing one or more specific query suggestions to the user device, selected from a plurality of specific query suggestions for the search string, when the measure of query completeness exceeds the threshold measure of query completeness; or providing one or more general query suggestions to the user device, selected from a plurality of general query suggestions for the search string, when the measure of query completeness does not exceed the threshold measure of query completeness. | 12. A system of one or more computers configured to perform operations comprising: receiving a search string from a user device; selecting a plurality of candidate query suggestions based on the search string; determining, for each candidate query suggestion, a probability for the candidate query suggestion based on a count in a query log of the number of times that the plurality of candidate query suggestions were submitted as search queries and a count in the query log of the number of times that the candidate query was submitted as a search query; determining, by one or more processors, a measure of query completeness for the search string based on an aggregation of the determined probabilities, including determining a probability of receiving the N most probable query suggestions for the search string, wherein N is an integer greater than zero; comparing the measure of query completeness to a threshold measure of query completeness; and providing one or more specific query suggestions to the user device, selected from a plurality of specific query suggestions for the search string, when the measure of query completeness exceeds the threshold measure of query completeness; or providing one or more general query suggestions to the user device, selected from a plurality of general query suggestions for the search string, when the measure of query completeness does not exceed the threshold measure of query completeness. 14. The system of claim 12 , wherein determining the probability of receiving a first one of the N most probable query suggestion includes: determining, from the query log, a count of the number of times the plurality of candidate query suggestions were received and a count of the number of times the first one of the N most probable query suggestions was received; and dividing the count of the number of times the first one of the N most probable query suggestions were received by the count of the number of times the plurality of candidate query suggestions were received. | 0.500865 |
8,560,297 | 9 | 11 | 9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs. | 9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs. 11. The computing apparatus of claim 9 , wherein the ranker component outputs the ranked list of word sequence pairs based at least in part upon word sequence alignment between the first electronic document and the second electronic document. | 0.831711 |
9,740,679 | 7 | 8 | 7. The method of claim 4 , wherein the reduced directed graph is generated from the input directed graph by iteratively applying at least one reduction rule to generate a reduced directed graph, the at least one reduction rule comprising a reduction rule selected from: a first reduction rule configured for identifying a division point node of the input directed graph, or of a reduced directed graph generated therefrom, which divides the respective graph into at least two connected components and wherein there is a unique incoming edge to the division point node in the first connected component and a unique outgoing edge from the division point node in the second connected component, the first reduction rule configured for generating a new edge with a label which is derived from the labels of the unique incoming edge and the unique outgoing edge; and a second reduction rule configured for identifying a node of the input directed graph or of a reduced directed graph generated therefrom which includes a first incoming edge and a first outgoing edge for which the multiplicity of one of the first incoming edge and the first outgoing edge is greater than a degree of the node minus the multiplicity of the other of the first incoming edge and the first outgoing edge, where the degree of the node is a sum of incoming edges of the node multiplied by their multiplicities, the second reduction rule configured for merging the first incoming edge and the first outgoing edge to create a new edge with a label which is derived from the first incoming edge and the first outgoing edge. | 7. The method of claim 4 , wherein the reduced directed graph is generated from the input directed graph by iteratively applying at least one reduction rule to generate a reduced directed graph, the at least one reduction rule comprising a reduction rule selected from: a first reduction rule configured for identifying a division point node of the input directed graph, or of a reduced directed graph generated therefrom, which divides the respective graph into at least two connected components and wherein there is a unique incoming edge to the division point node in the first connected component and a unique outgoing edge from the division point node in the second connected component, the first reduction rule configured for generating a new edge with a label which is derived from the labels of the unique incoming edge and the unique outgoing edge; and a second reduction rule configured for identifying a node of the input directed graph or of a reduced directed graph generated therefrom which includes a first incoming edge and a first outgoing edge for which the multiplicity of one of the first incoming edge and the first outgoing edge is greater than a degree of the node minus the multiplicity of the other of the first incoming edge and the first outgoing edge, where the degree of the node is a sum of incoming edges of the node multiplied by their multiplicities, the second reduction rule configured for merging the first incoming edge and the first outgoing edge to create a new edge with a label which is derived from the first incoming edge and the first outgoing edge. 8. The method of claim 7 , wherein the at least one reduction rule comprises the first reduction rule and the second reduction rule. | 0.958827 |
8,190,433 | 1 | 3 | 1. A method for operating a speech recognition system, the method comprising: (a) receiving voice input at a speech recognition engine; (b) receiving an acoustic model at the speech recognition engine; (c) providing a layered grammar and dictionary library to the speech recognition engine, the layered grammar and dictionary library generated before receipt of the voice input at the speech recognition engine, the layered grammar and dictionary library including, (i) a language and non-grammar layer that supplies types of rules a grammar definition layer can use and defines non-grammar the speech recognition system should ignore; (ii) a dictionary layer that defines phonetic transcriptions for word groups the speech recognition system is to recognize; (iii) a grammar definition layer that applies rules from the language and non-grammar layer to define combinations of word groups the speech recognition system is to recognize; (d) using the acoustic model and the layered grammar and dictionary library to process the voice input. | 1. A method for operating a speech recognition system, the method comprising: (a) receiving voice input at a speech recognition engine; (b) receiving an acoustic model at the speech recognition engine; (c) providing a layered grammar and dictionary library to the speech recognition engine, the layered grammar and dictionary library generated before receipt of the voice input at the speech recognition engine, the layered grammar and dictionary library including, (i) a language and non-grammar layer that supplies types of rules a grammar definition layer can use and defines non-grammar the speech recognition system should ignore; (ii) a dictionary layer that defines phonetic transcriptions for word groups the speech recognition system is to recognize; (iii) a grammar definition layer that applies rules from the language and non-grammar layer to define combinations of word groups the speech recognition system is to recognize; (d) using the acoustic model and the layered grammar and dictionary library to process the voice input. 3. A method for operating a speech recognition system as recited in claim 1 , wherein the word groups of the dictionary layer are defined in accordance with a generic group listing or a grammar related group. | 0.917656 |
7,593,843 | 1 | 2 | 1. A method of decoding an input semantic structure to generate an output semantic structure, the method comprising: providing a set of transfer mappings that cover at least portions of an input semantic structure that relates to an input word string of a first language, each transfer mapping having an input semantic side that describes at least one nodes of the input semantic structure and having an output semantic side that describes at least one node of the output semantic structure; using a processor to calculate a score for each of the set of transfer mappings which cover at least a select node of the input semantic structure using a statistical model, wherein calculating the score for each transfer mapping comprises combining scores of the highest scoring mappings for each child node of the select node not covered by the transfer mapping with the score of the transfer mapping; using the processor to select the highest scoring transfer mapping of the set of transfer mappings which cover the at least one select node; and using the processor to construct an output semantic structure that relates to an output word string of a second language using the selected highest scoring transfer mapping. | 1. A method of decoding an input semantic structure to generate an output semantic structure, the method comprising: providing a set of transfer mappings that cover at least portions of an input semantic structure that relates to an input word string of a first language, each transfer mapping having an input semantic side that describes at least one nodes of the input semantic structure and having an output semantic side that describes at least one node of the output semantic structure; using a processor to calculate a score for each of the set of transfer mappings which cover at least a select node of the input semantic structure using a statistical model, wherein calculating the score for each transfer mapping comprises combining scores of the highest scoring mappings for each child node of the select node not covered by the transfer mapping with the score of the transfer mapping; using the processor to select the highest scoring transfer mapping of the set of transfer mappings which cover the at least one select node; and using the processor to construct an output semantic structure that relates to an output word string of a second language using the selected highest scoring transfer mapping. 2. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises calculating the score using a target language model that provides a probability of a set of nodes appearing in the output semantic structure. | 0.618824 |
8,560,387 | 21 | 24 | 21. A method of configuring a collaborative advertising environment, comprising: determining which devices associated with a plurality of users are capable of joining a virtual world environment; inviting a user of the plurality of users having a device capable of joining the virtual world environment to participate in a collaborative virtual world environment; rendering and distributing by a computing device the collaborative virtual world environment to an invited user; synchronizing by the computing device an advertisement with the collaborative virtual world environment; and executing by the computing device the advertisement within the collaborative virtual world environment as the invited user interacts with a media stream, wherein the advertisement is played to the invited user within the collaborative virtual world environment and the media stream is separate from the collaborative virtual world environment. | 21. A method of configuring a collaborative advertising environment, comprising: determining which devices associated with a plurality of users are capable of joining a virtual world environment; inviting a user of the plurality of users having a device capable of joining the virtual world environment to participate in a collaborative virtual world environment; rendering and distributing by a computing device the collaborative virtual world environment to an invited user; synchronizing by the computing device an advertisement with the collaborative virtual world environment; and executing by the computing device the advertisement within the collaborative virtual world environment as the invited user interacts with a media stream, wherein the advertisement is played to the invited user within the collaborative virtual world environment and the media stream is separate from the collaborative virtual world environment. 24. The method as set forth in claim 21 , wherein the plurality of users is characterized by at least one parameter matched to a profile associated with a given user. | 0.756598 |
8,818,979 | 2 | 3 | 2. A document retrieving method, comprising: receiving a search query for a target document and searching a database by using a threshold of similarity to the target document to extract a plurality of documents having larger similarity than the threshold, the similarity between the target document and the respective extracted documents being a first similarity; a two-dimensional map creation step, by using the extracted documents, computing similarity between the respective extracted documents, the similarity between the respective extracted documents being a second similarity, creating a single radar chart in accordance with the first similarity and the second similarity by plotting each of the documents on the single radar chart according to a degree of relevance based on a distance such that the lower the similarity, the further each document is apart from other document, and displaying the created radar chart; an area designation step of designating an area on the displayed single radar chart, the area covering at least two plots of a plurality of plots, each associated with the respective documents, in accordance with an input instruction; an area information detection step of detecting area information representing the designated area for a retrieval with a narrowed range on the displayed map; a document detection step of detecting documents corresponding to the at least two plots covered by the designated area; a document list reading step of reading out a document list which is a list of the detected documents; a document compiling step of compiling bibliographic information of each document included in the document list read in the document list reading step; and a retrieval document extraction step of performing refine search by using a second query which is a compiling result compiled through the document compiling step. | 2. A document retrieving method, comprising: receiving a search query for a target document and searching a database by using a threshold of similarity to the target document to extract a plurality of documents having larger similarity than the threshold, the similarity between the target document and the respective extracted documents being a first similarity; a two-dimensional map creation step, by using the extracted documents, computing similarity between the respective extracted documents, the similarity between the respective extracted documents being a second similarity, creating a single radar chart in accordance with the first similarity and the second similarity by plotting each of the documents on the single radar chart according to a degree of relevance based on a distance such that the lower the similarity, the further each document is apart from other document, and displaying the created radar chart; an area designation step of designating an area on the displayed single radar chart, the area covering at least two plots of a plurality of plots, each associated with the respective documents, in accordance with an input instruction; an area information detection step of detecting area information representing the designated area for a retrieval with a narrowed range on the displayed map; a document detection step of detecting documents corresponding to the at least two plots covered by the designated area; a document list reading step of reading out a document list which is a list of the detected documents; a document compiling step of compiling bibliographic information of each document included in the document list read in the document list reading step; and a retrieval document extraction step of performing refine search by using a second query which is a compiling result compiled through the document compiling step. 3. A non-transitory computer readable storage medium for use in a computer, the computer readable storage medium being encoded with a computer program causing the computer to execute the retrieving method recited in claim 2 . | 0.502212 |
8,515,923 | 1 | 13 | 1. A document repository management (DRM) system for an institution having a defined organization, said DRM system comprising: an input device for receiving a document access request; an electronically readable organization chart and organizational chart information including information identifying individuals on said organization chart; an electronic document repository containing accessible documents; a controller that: controls requested access to each document of said accessible documents in said electronic document repository; and maps to said electronically readable organization chart and said organizational chart information, each said requested access to said each document of said accessible documents; and a display device that displays a document usage summary chart history based on historical tracking of actual usage and treatment of each document by individuals and groups on said organization chart. | 1. A document repository management (DRM) system for an institution having a defined organization, said DRM system comprising: an input device for receiving a document access request; an electronically readable organization chart and organizational chart information including information identifying individuals on said organization chart; an electronic document repository containing accessible documents; a controller that: controls requested access to each document of said accessible documents in said electronic document repository; and maps to said electronically readable organization chart and said organizational chart information, each said requested access to said each document of said accessible documents; and a display device that displays a document usage summary chart history based on historical tracking of actual usage and treatment of each document by individuals and groups on said organization chart. 13. The DRM System of claim 1 , wherein said controller identifies, summarizes and tracks each said requested access in terms of a name of a pre-authorized individual in said electronically readable organization chart. | 0.726131 |
9,355,169 | 12 | 13 | 12. A system for extracting a set of phrases from a plurality of documents, the system comprising: one or more computer readable media comprising executable instructions; and one or more processors configured to execute the instructions, wherein execution of the instructions causes the system to: for each document: identify a plurality of candidate phrases occurring in the document, wherein a candidate phrase includes two or more consecutive words that are determined to occur in the document; score candidate phrases in the document to produce respective document phrase scores for the candidate phrases for the document, the document phrase score for a candidate phrase being based on attributes of individual occurrences of the candidate phrase in the document, with at least some candidate phrases appearing repeatedly having a higher document phrase score than candidate phrases appearing once, and for a candidate phrase of the plurality of the candidate phrases: create, via the one or more processors, a combined score for the candidate phrase based on a plurality of different document phrase scores for the candidate phrase for respective different documents; and selecting the candidate phrase for inclusion in the extracted set based on the combined score for the candidate phrase and based on the document phrase scores for the candidate phrase. | 12. A system for extracting a set of phrases from a plurality of documents, the system comprising: one or more computer readable media comprising executable instructions; and one or more processors configured to execute the instructions, wherein execution of the instructions causes the system to: for each document: identify a plurality of candidate phrases occurring in the document, wherein a candidate phrase includes two or more consecutive words that are determined to occur in the document; score candidate phrases in the document to produce respective document phrase scores for the candidate phrases for the document, the document phrase score for a candidate phrase being based on attributes of individual occurrences of the candidate phrase in the document, with at least some candidate phrases appearing repeatedly having a higher document phrase score than candidate phrases appearing once, and for a candidate phrase of the plurality of the candidate phrases: create, via the one or more processors, a combined score for the candidate phrase based on a plurality of different document phrase scores for the candidate phrase for respective different documents; and selecting the candidate phrase for inclusion in the extracted set based on the combined score for the candidate phrase and based on the document phrase scores for the candidate phrase. 13. The system of claim 12 , wherein identifying a plurality of candidate phrases contained in the document further includes: identifying as a candidate phrase a sequence of words in the document terminated by a semantic marker. | 0.770161 |
8,872,979 | 1 | 9 | 1. A method, comprising: extracting first text from a first video segment and second text from a second video segment; identifying topics within the first text and the second text; comparing the first text with the second text to yield a textual comparison; generating, via a processor, a contextual similarity measure between the first video segment and the second video segment based on the first video segment, the second video segment, the textual comparison, and the topics; generating, via the processor, a visual similarity measure based on video similarity of the first video segment and the second video segment; based on the contextual similarity measure and the visual similarity measure, determining a combined similarity score, represented as a combined distance measure, for the first video segment and the second video segment, wherein the contextual similarity measure is converted to a normalized text distance and the visual similarity measure is converted to a normalized video distance; and outputting the combined similarity score. | 1. A method, comprising: extracting first text from a first video segment and second text from a second video segment; identifying topics within the first text and the second text; comparing the first text with the second text to yield a textual comparison; generating, via a processor, a contextual similarity measure between the first video segment and the second video segment based on the first video segment, the second video segment, the textual comparison, and the topics; generating, via the processor, a visual similarity measure based on video similarity of the first video segment and the second video segment; based on the contextual similarity measure and the visual similarity measure, determining a combined similarity score, represented as a combined distance measure, for the first video segment and the second video segment, wherein the contextual similarity measure is converted to a normalized text distance and the visual similarity measure is converted to a normalized video distance; and outputting the combined similarity score. 9. The method of claim 1 , wherein generating the visual similarity measure comprises using video corresponding to the first video segment and the second video segment. | 0.637931 |
8,706,474 | 17 | 19 | 17. A non-transitory computer program product storing instructions to cause a data processing apparatus to perform operations comprising: receiving a set of data records the data records comprising one or more names of one or more entities in a source language from a source document; generating candidate translations for the names of the data records, the candidate translations being strings of characters in a target language that has a different character set than a character set of the source language; querying a data repository for records matching the candidate translations; and selecting a translation of at least one of the names from the candidate translations based on a comparison of a combination of the candidate translations and properties of the source document with the result of the querying the data repository, the properties comprising of co-occurrence frequency of one or more co-occurring terms in the source document, date of publication of the source document, a first frequency of the names of the data records in the source document, a second frequency of the names of the data records in documents published since a particular date, and cultural conventions associated with the source language and the target language. | 17. A non-transitory computer program product storing instructions to cause a data processing apparatus to perform operations comprising: receiving a set of data records the data records comprising one or more names of one or more entities in a source language from a source document; generating candidate translations for the names of the data records, the candidate translations being strings of characters in a target language that has a different character set than a character set of the source language; querying a data repository for records matching the candidate translations; and selecting a translation of at least one of the names from the candidate translations based on a comparison of a combination of the candidate translations and properties of the source document with the result of the querying the data repository, the properties comprising of co-occurrence frequency of one or more co-occurring terms in the source document, date of publication of the source document, a first frequency of the names of the data records in the source document, a second frequency of the names of the data records in documents published since a particular date, and cultural conventions associated with the source language and the target language. 19. The product of claim 17 wherein the generating of the candidate translations comprises considering a plurality of possible tokenizations of a combination of characters determined to represent an entity name. | 0.513825 |
9,311,426 | 9 | 10 | 9. An electronic device, comprising: a display screen; and a processor in communication with the display screen and configured to execute computer readable instructions stored in a memory to: obtain a structured document that includes a plurality of content elements; after obtaining the structured document: prepare a first rendered document having the plurality of content elements; compute a score for each of the plurality of content elements; select a subset of said plurality of content elements from the structured document by selecting those ones of said plurality of content elements having a score at or above a threshold, said score being determined based on at least one factor selected from the group consisting of: word count, character count, and link density, wherein the link density is based on a count of hyperlinks appearing in the content element in the obtained structured document, the subset excluding one or more of the content elements that are advertisements; prepare a second rendered document having said subset of said plurality of content elements, the second rendered document being a reader-style rendered document having fewer advertisements than the first rendered document; output the first rendered document to the display screen while the display screen is in a landscape orientation; detect a change in orientation of the display screen to a portrait orientation; and in response to said detecting, output the second rendered document to the display screen. | 9. An electronic device, comprising: a display screen; and a processor in communication with the display screen and configured to execute computer readable instructions stored in a memory to: obtain a structured document that includes a plurality of content elements; after obtaining the structured document: prepare a first rendered document having the plurality of content elements; compute a score for each of the plurality of content elements; select a subset of said plurality of content elements from the structured document by selecting those ones of said plurality of content elements having a score at or above a threshold, said score being determined based on at least one factor selected from the group consisting of: word count, character count, and link density, wherein the link density is based on a count of hyperlinks appearing in the content element in the obtained structured document, the subset excluding one or more of the content elements that are advertisements; prepare a second rendered document having said subset of said plurality of content elements, the second rendered document being a reader-style rendered document having fewer advertisements than the first rendered document; output the first rendered document to the display screen while the display screen is in a landscape orientation; detect a change in orientation of the display screen to a portrait orientation; and in response to said detecting, output the second rendered document to the display screen. 10. The electronic device of claim 9 , wherein the processor is configured to prepare the first rendered document and to prepare the second rendered document by rendering the first rendered document and rendering the second rendered document, respectively. | 0.863974 |
4,684,926 | 22 | 23 | 22. The apparatus of claim 21 wherein the four basic patterns are: left-right, up-down, embracing, and singular, corresponding to relative locations of roots within each character, and the four basic patterns are alloted numerical codes 1, 2, 3, and 4, according to their frequencies in practical Chinese usage. | 22. The apparatus of claim 21 wherein the four basic patterns are: left-right, up-down, embracing, and singular, corresponding to relative locations of roots within each character, and the four basic patterns are alloted numerical codes 1, 2, 3, and 4, according to their frequencies in practical Chinese usage. 23. The apparatus of claim 22 wherein the five basic types of strokes are: horizontal, vertical, left-falling, right-falling and turning, and each of the five basic types of strokes encompasses at least two strokes, and the five basic strokes are allotted numerical codes 1, 2, 3, 4, and 5 according to their frequency in practical Chinese usage. | 0.968105 |
8,060,489 | 1 | 4 | 1. A computer-implemented method for realizing a virtual bookshelf, comprising: initiating a search query to locate one or more desired books in either physical or soft copy digital form; producing search metadata corresponding to the one or more desired books; filtering metadata corresponding to books contained within the virtual bookshelf with the search metadata to determine whether the one or more desired books is present in the virtual bookshelf, wherein the virtual bookshelf comprises information representing books, in either physical or soft copy digital form, acquired by and particular to a user; and outputting results of the filtering indicative of whether the one or more desired books is present on the virtual bookshelf. | 1. A computer-implemented method for realizing a virtual bookshelf, comprising: initiating a search query to locate one or more desired books in either physical or soft copy digital form; producing search metadata corresponding to the one or more desired books; filtering metadata corresponding to books contained within the virtual bookshelf with the search metadata to determine whether the one or more desired books is present in the virtual bookshelf, wherein the virtual bookshelf comprises information representing books, in either physical or soft copy digital form, acquired by and particular to a user; and outputting results of the filtering indicative of whether the one or more desired books is present on the virtual bookshelf. 4. The computer-implemented method of claim 1 , further comprising: enabling the user of the virtual bookshelf to modify the metadata of the one or more desired books in the virtual bookshelf. | 0.755102 |
9,201,854 | 5 | 6 | 5. The method of claim 4 , wherein the representing print resources further comprises representing one or more print formats. | 5. The method of claim 4 , wherein the representing print resources further comprises representing one or more print formats. 6. The method of claim 5 , wherein the representing print formats further comprises representing fonts, images and overlays. | 0.973218 |
7,668,388 | 9 | 10 | 9. The method of claim 8 , wherein the focus classification feature that is insensitive to the spatial distribution associated with the pixel intensity variations in the image is selected from a group of focus classification features that are image pixel intensity statistical distribution parameters. | 9. The method of claim 8 , wherein the focus classification feature that is insensitive to the spatial distribution associated with the pixel intensity variations in the image is selected from a group of focus classification features that are image pixel intensity statistical distribution parameters. 10. The method of claim 9 , wherein the group of focus classification features that are image pixel intensity statistical distribution parameters comprises a grayscale intensity variance, an intensity variance derived from converted color channel information, an average grayscale intensity, and an average intensity derived from converted color channel information. | 0.937372 |
8,140,980 | 1 | 2 | 1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information. | 1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information. 2. A method according to claim 1 , wherein the configuration information specifies type of language, the method further comprising: translating the textual information according to the type of language, the augmented textual information including the translated textual information. | 0.754355 |
8,666,982 | 1 | 7 | 1. A method comprising: receiving a document; applying one or more tags to the document, each tag applied to a term, each tag representing a part of speech; extracting one or more terms from the document based on the tags; determining a frequency parameter for each of the one or more extracted terms, wherein the frequency parameter is proportional to a logarithm of a total number of documents in the domain ontology divided by a number of documents in which the term appears; determining, based on the frequency parameter associated with each of the extracted terms, whether a domain ontology comprises the one or more extracted terms; and augmenting, if the domain ontology does not comprise the one or more extracted terms, such that the domain ontology comprises the one or more extracted terms. | 1. A method comprising: receiving a document; applying one or more tags to the document, each tag applied to a term, each tag representing a part of speech; extracting one or more terms from the document based on the tags; determining a frequency parameter for each of the one or more extracted terms, wherein the frequency parameter is proportional to a logarithm of a total number of documents in the domain ontology divided by a number of documents in which the term appears; determining, based on the frequency parameter associated with each of the extracted terms, whether a domain ontology comprises the one or more extracted terms; and augmenting, if the domain ontology does not comprise the one or more extracted terms, such that the domain ontology comprises the one or more extracted terms. 7. The method of claim 1 , wherein determining, based on the frequency parameter associated with each of the extracted terms whether the domain ontology comprises the one or more extracted terms comprises: determining whether the frequency parameter associated with each of the one or more extracted terms is above a threshold frequency parameter; comparing the one or more extracted terms associated with a frequency parameter above the threshold frequency parameter to existing terms in the domain ontology; and determining whether the one or more extracted terms match existing terms in the domain ontology. | 0.527132 |
9,158,860 | 10 | 17 | 10. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. | 10. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. 17. The system of claim 10 , wherein providing for display the query completion template includes providing for display text indicating the category of information. | 0.861252 |
8,392,187 | 8 | 10 | 8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis. | 8. A speech recognition system comprising: a microphone configured to receive a speech signal; a frame constructor configured to create a plurality of frames from the speech signal; a feature extractor configured to produced feature vectors from the frames; and a decoder configured to: expand a search network based on a frame; determine a best hypothesis in the search network; modify a default beam threshold to produce a modified beam threshold, wherein modifying a default beam threshold further comprises modifying the default beam threshold based on at least one selected from a group consisting of: a time the frame is received, a speed with which the search network is increasing in size, and a number of active phones, wherein the default beam threshold is increased by an empirically determined amount if an acceleration of the speed with which the search network is increasing in size for the frame exceeds an empirically determined amount; and prune the search network using the modified beam threshold and the best hypothesis. 10. The speech recognition system of claim 8 , wherein the beam threshold is reduced if the number of active phone is greater than an empirically determined threshold. | 0.632159 |
8,565,526 | 18 | 23 | 18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. | 18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. 23. A system as recited in claim 18 wherein the multiple lexicons include custom lexicons for a particular application. | 0.69797 |
9,847,101 | 18 | 19 | 18. A computer program product to generate a video comprising a plurality of scenes, embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: accessing a set of storage devices to hold a set of data records to form a plurality of search corpora, at least a portion of the search corpora accessible based on a user credential; analyzing information from the portion of the search corpora or from a second search corpus to determine at least one attribute pertaining to the information; executing a rule corresponding to a node of a decision graph, each node comprising one or more selected from a group consisting of: a scene name, a scene indication, an audience description, a template description, and any combination thereof; detecting a scene condition of a scene based on execution of the rule corresponding to the node of the decision graph; generating the scene, the scene comprising information included in the portion of the search corpora; evaluating the scene condition of the scene, the scene condition based at least in part on the attribute; determining a content of a next scene of the plurality of scenes based at least in part on a value obtained by evaluating the scene condition; determining an additional scene should not be generated based on the scene condition of the scene; accessing a second portion of the search corpora accessible based on the scene condition of another scene, the second portion of the search corpora comprising the content of the next scene; selecting a template for presenting the content of the next scene, the template selected based on information found in the second portion of the search corpora; generating the next scene of the plurality of scenes such that the next scene comprises the content; editing the next scene based on information specified in a user interface, the user interface comprising information specifying one or more of a name of the next scene and the template for presenting the next scene; assembling at least the scene and the next scene into the video; and adding narration to the video; wherein evaluating the scene condition of the scene comprises comparing the scene condition to a plurality of scene conditions associated with the node of the decision graph; wherein the portion of the search corpora is defined based on one or more selected from a group consisting of the user credential, a user role of a user associated with the user credential, a rule, and any combination thereof; wherein access to the plurality of search corpora is restricted to the portion of the search corpora based on the user credential; wherein the user credential comprises one or more of a login screen name and a username-password pair; wherein the scene condition evaluates to a quantified value or a Boolean value; wherein the information from the portion of the search corpora is analyzed periodically; wherein determining the content of the next scene comprises using statistical analysis to determine a scope and a relevance of the content of the next scene; wherein determining the content of the next scene of the plurality of scenes comprises traversing the decision graph, the content of the next scene determined based on a set of rules encoded into the decision graph, at least some of the set of rules associated with a determination of one or more statistical quantities; wherein the decision graph is traversed in a depth-first manner or a breadth-first manner; wherein the search corpora comprises structured data and unstructured data; wherein the template comprises a plurality of attribute fields, the attributes comprising one or more selected from a group consisting of: a title, a subtitle, a narration, a transition, and any combination thereof. | 18. A computer program product to generate a video comprising a plurality of scenes, embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: accessing a set of storage devices to hold a set of data records to form a plurality of search corpora, at least a portion of the search corpora accessible based on a user credential; analyzing information from the portion of the search corpora or from a second search corpus to determine at least one attribute pertaining to the information; executing a rule corresponding to a node of a decision graph, each node comprising one or more selected from a group consisting of: a scene name, a scene indication, an audience description, a template description, and any combination thereof; detecting a scene condition of a scene based on execution of the rule corresponding to the node of the decision graph; generating the scene, the scene comprising information included in the portion of the search corpora; evaluating the scene condition of the scene, the scene condition based at least in part on the attribute; determining a content of a next scene of the plurality of scenes based at least in part on a value obtained by evaluating the scene condition; determining an additional scene should not be generated based on the scene condition of the scene; accessing a second portion of the search corpora accessible based on the scene condition of another scene, the second portion of the search corpora comprising the content of the next scene; selecting a template for presenting the content of the next scene, the template selected based on information found in the second portion of the search corpora; generating the next scene of the plurality of scenes such that the next scene comprises the content; editing the next scene based on information specified in a user interface, the user interface comprising information specifying one or more of a name of the next scene and the template for presenting the next scene; assembling at least the scene and the next scene into the video; and adding narration to the video; wherein evaluating the scene condition of the scene comprises comparing the scene condition to a plurality of scene conditions associated with the node of the decision graph; wherein the portion of the search corpora is defined based on one or more selected from a group consisting of the user credential, a user role of a user associated with the user credential, a rule, and any combination thereof; wherein access to the plurality of search corpora is restricted to the portion of the search corpora based on the user credential; wherein the user credential comprises one or more of a login screen name and a username-password pair; wherein the scene condition evaluates to a quantified value or a Boolean value; wherein the information from the portion of the search corpora is analyzed periodically; wherein determining the content of the next scene comprises using statistical analysis to determine a scope and a relevance of the content of the next scene; wherein determining the content of the next scene of the plurality of scenes comprises traversing the decision graph, the content of the next scene determined based on a set of rules encoded into the decision graph, at least some of the set of rules associated with a determination of one or more statistical quantities; wherein the decision graph is traversed in a depth-first manner or a breadth-first manner; wherein the search corpora comprises structured data and unstructured data; wherein the template comprises a plurality of attribute fields, the attributes comprising one or more selected from a group consisting of: a title, a subtitle, a narration, a transition, and any combination thereof. 19. The computer program product of claim 18 , wherein sequence of instructions further has instructions encoded thereon which, when executed by the processor, causes the processor to execute the process, the process further comprising: scheduling one or more of the scene and the next scene to be generated. | 0.665944 |
8,612,483 | 12 | 14 | 12. A method comprising: receiving, by a processor, a request from a user to discuss content with a recipient user in a plurality of groups in a social network, wherein the recipient user is associated with a first group in the plurality of groups, wherein the first group comprising a plurality of the recipient users in the social network; creating, by the processor, a temporary placeholder account for the user; creating, by the processor, a second group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the second group is different from the first group and the second group is not in the plurality of groups; initiating, by the processor, a live discussion between the user and the recipient user about the content in the second group; converting, by the processor, the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the converting comprises allowing the user to join the first group in the social network; and sending, by the processor, a notification of the user joining the first group to the plurality of the recipient users. | 12. A method comprising: receiving, by a processor, a request from a user to discuss content with a recipient user in a plurality of groups in a social network, wherein the recipient user is associated with a first group in the plurality of groups, wherein the first group comprising a plurality of the recipient users in the social network; creating, by the processor, a temporary placeholder account for the user; creating, by the processor, a second group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the second group is different from the first group and the second group is not in the plurality of groups; initiating, by the processor, a live discussion between the user and the recipient user about the content in the second group; converting, by the processor, the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the converting comprises allowing the user to join the first group in the social network; and sending, by the processor, a notification of the user joining the first group to the plurality of the recipient users. 14. The method of claim 12 further comprising determining the recipient user in the plurality of groups for the request based on a relationship between the user and recipient user. | 0.756757 |
9,208,132 | 11 | 12 | 11. The method of claim 10 , wherein the changing of the format includes changing at least one of a font size, a font typeface, or a font style of the text. | 11. The method of claim 10 , wherein the changing of the format includes changing at least one of a font size, a font typeface, or a font style of the text. 12. The method of claim 11 , further including propagating formatting changes within at least one of the product concept, the first variant, or the second variant. | 0.937786 |
9,400,974 | 1 | 7 | 1. A method comprising: receiving, by a server computer system, an electronic document from a user operating a client computing device; converting, by the server computer system, the electronic document into a standard image format; causing, by the server computer system, the converted electronic document to be displayed to the user via the client computing device; receiving, by the server computer system from the user, user input for adding an electronic signature to the electronic document, the receiving comprising: generating, by the server computer system, a unique identifier for the user; instructing, by the server computer system, the user to capture an image of the user's signature using a camera of a smartphone; instructing, by the server computer system, the user to transmit, from the smartphone, an email message to a predefined administrative email address, wherein the email message includes the image of the user's signature as an email attachment and includes the unique identifier in the email's subject line; receiving, by the server computer system, the email message transmitted by the user; associating, by the server computer system, the email message with the user based on the unique identifier included in the email's subject line; extracting, by the server computer system, the image of the user's signature from the email message; generating, by the server computer system, a user interface that presents the image of the user's signature to the user and that includes: a first control for cropping the image of the user's signature; a second control for adjusting contrast of the image of the user's signature; and a third control for rotating the image of the user's signature; receiving, by the server computer system, one or more commands from the user via manipulation of the first, second, and third controls; modifying, by the server computer system, the image of the user's signature based on the one or more commands; and saving, by the server computer system, the modified image of the user's signature as the electronic signature; generating, by the server computer system, an annotated version of the electronic document that includes the electronic signature; and sending, by the server computer system, the annotated version of the electronic document to a recipient designated by the user. | 1. A method comprising: receiving, by a server computer system, an electronic document from a user operating a client computing device; converting, by the server computer system, the electronic document into a standard image format; causing, by the server computer system, the converted electronic document to be displayed to the user via the client computing device; receiving, by the server computer system from the user, user input for adding an electronic signature to the electronic document, the receiving comprising: generating, by the server computer system, a unique identifier for the user; instructing, by the server computer system, the user to capture an image of the user's signature using a camera of a smartphone; instructing, by the server computer system, the user to transmit, from the smartphone, an email message to a predefined administrative email address, wherein the email message includes the image of the user's signature as an email attachment and includes the unique identifier in the email's subject line; receiving, by the server computer system, the email message transmitted by the user; associating, by the server computer system, the email message with the user based on the unique identifier included in the email's subject line; extracting, by the server computer system, the image of the user's signature from the email message; generating, by the server computer system, a user interface that presents the image of the user's signature to the user and that includes: a first control for cropping the image of the user's signature; a second control for adjusting contrast of the image of the user's signature; and a third control for rotating the image of the user's signature; receiving, by the server computer system, one or more commands from the user via manipulation of the first, second, and third controls; modifying, by the server computer system, the image of the user's signature based on the one or more commands; and saving, by the server computer system, the modified image of the user's signature as the electronic signature; generating, by the server computer system, an annotated version of the electronic document that includes the electronic signature; and sending, by the server computer system, the annotated version of the electronic document to a recipient designated by the user. 7. The method of claim 1 further comprising, prior to sending the annotated version of the electronic document, receiving user input for sizing the electronic signature. | 0.709622 |
8,079,046 | 1 | 4 | 1. A method of predicting items of media content most likely to appeal to a user, comprising: accepting ratings, at a multimedia recording device, of media content items from a user, via a graphical user interface, according to a rating system; expressing the rating system using a graphical metaphor; receiving by the multimedia recording device, from a server, correlation data between pairs of available media content; generating ratings at the multimedia recording device of media content items not rated by the user according to one or more predictive algorithms, based on the media content items specifically rated by the user and the correlation data received from the server; displaying, by the multimedia recording device, the media content items ratings by the user and the generated media content ratings in the graphical user interface; and allowing the user to correct generated media content ratings displayed in the graphical user interface in order to obtain generated media content ratings more in line with what the user expects. | 1. A method of predicting items of media content most likely to appeal to a user, comprising: accepting ratings, at a multimedia recording device, of media content items from a user, via a graphical user interface, according to a rating system; expressing the rating system using a graphical metaphor; receiving by the multimedia recording device, from a server, correlation data between pairs of available media content; generating ratings at the multimedia recording device of media content items not rated by the user according to one or more predictive algorithms, based on the media content items specifically rated by the user and the correlation data received from the server; displaying, by the multimedia recording device, the media content items ratings by the user and the generated media content ratings in the graphical user interface; and allowing the user to correct generated media content ratings displayed in the graphical user interface in order to obtain generated media content ratings more in line with what the user expects. 4. The method of claim 1 , wherein the step of rating items according to the rating system by the user comprises at least one of the steps of: assigning an overall rating to an item; and assigning ratings to individual features. | 0.871477 |
5,499,108 | 1 | 4 | 1. A system comprising a document-driven scanning input device communicating with a computer, said input device comprising scanning means for generating image data representing the image of a document, and means, responsive to placement of a document by a user, for drawing the document into scanning relationship with said scanning means so that said scanning means generates image data representing the image of said document, wherein said placement alone is sufficient to initiate said drawing, and said computer comprising means for displaying, in response to said placement, a plurality of user-selectable options for processing said image data. | 1. A system comprising a document-driven scanning input device communicating with a computer, said input device comprising scanning means for generating image data representing the image of a document, and means, responsive to placement of a document by a user, for drawing the document into scanning relationship with said scanning means so that said scanning means generates image data representing the image of said document, wherein said placement alone is sufficient to initiate said drawing, and said computer comprising means for displaying, in response to said placement, a plurality of user-selectable options for processing said image data. 4. A system according to claim 1 wherein said computer further comprises means for establishing which option has been selected by the user and for invoking a process corresponding to the option selected by the user for processing said image data. | 0.654494 |
6,011,865 | 7 | 8 | 7. A method for operating a handwriting recognition system, comprising the steps of: responsive to a handwriting input from a user, providing corresponding dynamic, time ordered stroke information; converting the corresponding dynamic, time ordered stroke information to static stroke information; determining a first list comprised of at least one probable character that the corresponding dynamic, time ordered stroke information is intended to represent; determining a second list comprised of at least one probable character that the static stroke information represents; and merging the first list and the second list to provide a third, unified list comprised of at least one most probable character that the corresponding dynamic, time ordered stroke information is intended to represent. | 7. A method for operating a handwriting recognition system, comprising the steps of: responsive to a handwriting input from a user, providing corresponding dynamic, time ordered stroke information; converting the corresponding dynamic, time ordered stroke information to static stroke information; determining a first list comprised of at least one probable character that the corresponding dynamic, time ordered stroke information is intended to represent; determining a second list comprised of at least one probable character that the static stroke information represents; and merging the first list and the second list to provide a third, unified list comprised of at least one most probable character that the corresponding dynamic, time ordered stroke information is intended to represent. 8. A method as set forth in claim 7 wherein the step of converting includes a step of generating one or more first stroke features based on contour directions of the static stroke information. | 0.845659 |
9,817,813 | 10 | 18 | 10. A system comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, causes the processor to: receive a supplied phrase, the supplied phrase comprising one or more terms, the supplied phrase being associated with a category of a plurality of categories, each category being associated with a different topic and a plurality of phrases each having a meaning semantically related to the different topic, the plurality of categories being used by an analytics system to perform classifications; examine one or more terms included in the supplied phrase; based on examining the one or more terms, determine that a first term of the supplied phrase corresponds to a semantic group; identify a second term that is included in the semantic group; generate, using the supplied phrase and the second term, a suggested phrase having a similar meaning to the supplied phrase, the suggested phrase and the supplied phrase being semantically related to the different topic associated with the category; and configure the analytics system by adding the suggested phrase to the category that includes the supplied phrase. | 10. A system comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, causes the processor to: receive a supplied phrase, the supplied phrase comprising one or more terms, the supplied phrase being associated with a category of a plurality of categories, each category being associated with a different topic and a plurality of phrases each having a meaning semantically related to the different topic, the plurality of categories being used by an analytics system to perform classifications; examine one or more terms included in the supplied phrase; based on examining the one or more terms, determine that a first term of the supplied phrase corresponds to a semantic group; identify a second term that is included in the semantic group; generate, using the supplied phrase and the second term, a suggested phrase having a similar meaning to the supplied phrase, the suggested phrase and the supplied phrase being semantically related to the different topic associated with the category; and configure the analytics system by adding the suggested phrase to the category that includes the supplied phrase. 18. The system of claim 10 , wherein the processor and memory are components of a speech analytics system. | 0.845029 |
9,190,055 | 14 | 16 | 14. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: training, based at least partly on user data regarding a user, a personal model for use in named entity recognition, the personal model comprising a named entity recognition model; interpolating the personal model and a general model to obtain a composite model, the general model comprising a named entity recognition model; receiving audio input of an utterance, the audio input captured via a microphone; generating a transcription of the utterance based at least partly on the audio input and performing named entity recognition on the transcription using the composite model to generate a sequence of named entities. | 14. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: training, based at least partly on user data regarding a user, a personal model for use in named entity recognition, the personal model comprising a named entity recognition model; interpolating the personal model and a general model to obtain a composite model, the general model comprising a named entity recognition model; receiving audio input of an utterance, the audio input captured via a microphone; generating a transcription of the utterance based at least partly on the audio input and performing named entity recognition on the transcription using the composite model to generate a sequence of named entities. 16. The one or more non-transitory computer readable media of claim 14 , wherein interpolation of the personal model and the general model comprises interpolation of an element of the personal model with a corresponding element of the general model. | 0.849819 |
8,543,939 | 16 | 26 | 16. A method comprising: receiving data in a first format, the data including first information having a first type and second information having a second type; providing the data for display via a graphical interface that includes a vertical scroll bar, a length of the vertical scroll bar corresponding to a length of the data, and the graphical interface providing for display only a part of data at a time; receiving a selection of one or more translation rules, from a plurality of translation rules, for converting at least one of the first information or the second information to a second format that differs from the first format; determining an effect of applying the one or more translation rules to the data; providing information associated with the effect of applying the one or more translation rules to the data for display via the graphical interface; determining a portion of the data that is incompatible with the second format; and providing an indication of the portion for display via the graphical interface, providing the indication of the portion including: providing a first graphical symbol for display at a location of the vertical scroll bar, the location of the first graphical symbol in the vertical scroll bar corresponding to a position of the portion in the length of the data, and a selection of the first graphical symbol causing the graphical interface to include the portion in the part of the data provided for display in the graphical interface, receiving the data, providing the data for display, receiving the selection of the one or more translation rules, determining the effect of applying the one or more translation rules, information associated with the effect; determining the portion of the data; and providing the indication of the portion being performed by one or more processors. | 16. A method comprising: receiving data in a first format, the data including first information having a first type and second information having a second type; providing the data for display via a graphical interface that includes a vertical scroll bar, a length of the vertical scroll bar corresponding to a length of the data, and the graphical interface providing for display only a part of data at a time; receiving a selection of one or more translation rules, from a plurality of translation rules, for converting at least one of the first information or the second information to a second format that differs from the first format; determining an effect of applying the one or more translation rules to the data; providing information associated with the effect of applying the one or more translation rules to the data for display via the graphical interface; determining a portion of the data that is incompatible with the second format; and providing an indication of the portion for display via the graphical interface, providing the indication of the portion including: providing a first graphical symbol for display at a location of the vertical scroll bar, the location of the first graphical symbol in the vertical scroll bar corresponding to a position of the portion in the length of the data, and a selection of the first graphical symbol causing the graphical interface to include the portion in the part of the data provided for display in the graphical interface, receiving the data, providing the data for display, receiving the selection of the one or more translation rules, determining the effect of applying the one or more translation rules, information associated with the effect; determining the portion of the data; and providing the indication of the portion being performed by one or more processors. 26. The method of claim 16 , where the one or more translation rules include at least one of: a replacement rule for replacing at least one of the first information or the second information with replacement information, a conversion rule for converting at least one of the first information or the second information to a third format, or an exclusion rule for removing at least one of the first information or the second information from the data. | 0.695387 |
9,501,720 | 3 | 7 | 3. An object detection apparatus comprising: a storage storing, for each of a plurality of part areas forming an area in an input image that is subject to image recognition processing and is referred to as a subject area, image recognition dictionaries that are used to recognize a target object to be detected in the input image and are typed according to variations in appearance of a part of the target object to be detected in the part area; a part score calculator configured to calculate, for each of the part areas forming the subject area cut from the input image, a part score indicative of a degree of similarity between the part area and each of at least some of the image recognition dictionaries stored in the storage; an integrated score calculator configured to calculate an integrated score by selecting, for each of the part areas forming the subject area, one of the scores calculated in the part score calculator and then calculating a weighted sum of the selected part scores for the respective part areas of the subject area; and a determiner configured to determine, on the basis of the integrated score calculated in the integrated score calculator, whether or not the target object is present in the subject area; wherein the integrated score calculator comprises: a candidate score extractor configured to extract, for each of the part areas forming the subject area, scores equal to or greater than a predetermined threshold as candidate scores from the part scores of the part area, and determine the image recognition dictionaries used to calculate the candidate scores for the part area; a temporary integrated score calculator configured to calculate a weighted sum of the candidate part scores for each of combinations of the image recognition dictionaries determined by the candidate score extractor for the respective part areas forming the subject area; and an integrated score selector configured to select, as the integrated score, a maximum of the temporary integrated scores calculated by the temporary integrated score calculator. | 3. An object detection apparatus comprising: a storage storing, for each of a plurality of part areas forming an area in an input image that is subject to image recognition processing and is referred to as a subject area, image recognition dictionaries that are used to recognize a target object to be detected in the input image and are typed according to variations in appearance of a part of the target object to be detected in the part area; a part score calculator configured to calculate, for each of the part areas forming the subject area cut from the input image, a part score indicative of a degree of similarity between the part area and each of at least some of the image recognition dictionaries stored in the storage; an integrated score calculator configured to calculate an integrated score by selecting, for each of the part areas forming the subject area, one of the scores calculated in the part score calculator and then calculating a weighted sum of the selected part scores for the respective part areas of the subject area; and a determiner configured to determine, on the basis of the integrated score calculated in the integrated score calculator, whether or not the target object is present in the subject area; wherein the integrated score calculator comprises: a candidate score extractor configured to extract, for each of the part areas forming the subject area, scores equal to or greater than a predetermined threshold as candidate scores from the part scores of the part area, and determine the image recognition dictionaries used to calculate the candidate scores for the part area; a temporary integrated score calculator configured to calculate a weighted sum of the candidate part scores for each of combinations of the image recognition dictionaries determined by the candidate score extractor for the respective part areas forming the subject area; and an integrated score selector configured to select, as the integrated score, a maximum of the temporary integrated scores calculated by the temporary integrated score calculator. 7. The apparatus of claim 3 , further comprising: an estimator configured to estimate at least one of a scene of the input image and a state of the target object on the basis of the combination of the image recognition dictionaries used to calculate the integrated score. | 0.734834 |
9,053,097 | 34 | 39 | 34. A system for facilitating cross-language communication among users of respective first and second wireless communication devices, the first wireless communication device having a first sensor, other than an antenna, configured to receive a first signal from an ambient signal source and the second wireless communication device having a second sensor, other than an antenna, configured to receive a second signal from an ambient signal source, the system comprising: a server configured to automatically coordinate establishment of a cross-language communication session including the first and second wireless communication devices, the server including: a session initiation receiver configured to receive information about first and second user inputs, received by the respective first and second wireless communication devices, indicating willingness to participate in the cross-language communication session; and a coordination module configured to automatically: compare the first signal to the second signal to determine whether the first signal and the second signal satisfy a similarity criterion; and if the first and second signals satisfy the similarity criterion, associate the first wireless communication device with the second wireless communication device. | 34. A system for facilitating cross-language communication among users of respective first and second wireless communication devices, the first wireless communication device having a first sensor, other than an antenna, configured to receive a first signal from an ambient signal source and the second wireless communication device having a second sensor, other than an antenna, configured to receive a second signal from an ambient signal source, the system comprising: a server configured to automatically coordinate establishment of a cross-language communication session including the first and second wireless communication devices, the server including: a session initiation receiver configured to receive information about first and second user inputs, received by the respective first and second wireless communication devices, indicating willingness to participate in the cross-language communication session; and a coordination module configured to automatically: compare the first signal to the second signal to determine whether the first signal and the second signal satisfy a similarity criterion; and if the first and second signals satisfy the similarity criterion, associate the first wireless communication device with the second wireless communication device. 39. A system according to claim 34 , wherein the coordination module is configured automatically compare the first signal to the second signal to determine whether the first signal and the second signal satisfy a similarity criterion and automatically establish the cross-language communication session, such that each user's privacy is preserved. | 0.868561 |
8,924,419 | 6 | 11 | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. 11. The method of claim 6 wherein the operations are performed in the order as shown. | 0.914487 |
7,876,467 | 11 | 14 | 11. A method for printing and interacting with a document, said method comprising the steps of: receiving, in a computer system, a request for printing said document, said document containing visible information; allocating a document identity to said document; determining coded data for said document, said coded data encoding a plurality of locations on said document and identifying said document identity; sending print data to a printer; printing the document so that the printed document includes said visible information superimposed with said coded data, said visible information and said coded data being printed at the same time by a printer connected to the computer system; interacting with the printed document using an optically imaging pen; imaging at least some of the printed coded data; generating indicating data using the sensed coded data, said indicating data identifying the document identity and a position of the pen relative to the printed document; sending the indicating to the computer system; and interpreting the indicating data using a stored page description retrievable using said document identity contained in said indicating data. | 11. A method for printing and interacting with a document, said method comprising the steps of: receiving, in a computer system, a request for printing said document, said document containing visible information; allocating a document identity to said document; determining coded data for said document, said coded data encoding a plurality of locations on said document and identifying said document identity; sending print data to a printer; printing the document so that the printed document includes said visible information superimposed with said coded data, said visible information and said coded data being printed at the same time by a printer connected to the computer system; interacting with the printed document using an optically imaging pen; imaging at least some of the printed coded data; generating indicating data using the sensed coded data, said indicating data identifying the document identity and a position of the pen relative to the printed document; sending the indicating to the computer system; and interpreting the indicating data using a stored page description retrievable using said document identity contained in said indicating data. 14. The method of claim 11 , wherein said pen comprises a memory buffer for storing said indicating data. | 0.892638 |
7,660,793 | 1 | 8 | 1. A method of providing integrated access to both structured and unstructured data, the method comprising: maintaining metadata in a database of structured data, the metadata comprising data about unstructured data; receiving a query directed toward a combination of structured and unstructured data, the query having a portion directed toward unstructured data, wherein the portion comprises at least one term for searching within unstructured data; retrieving structured data from a database of structured data in accordance with the received query, the retrieved structured data comprising at least a portion of the metadata; processing the retrieved structured data to identify a scope of unstructured data for retrieval from a data store of unstructured data; retrieving unstructured data from the data store of unstructured data corresponding to the identified scope of unstructured data; streaming the retrieved unstructured data through a processing device in a computing system other than a main processor for the system; and searching the retrieved streaming unstructured data based on the at least one query term using the processing device to find unstructured data within the retrieved streaming unstructured data that is responsive to the query. | 1. A method of providing integrated access to both structured and unstructured data, the method comprising: maintaining metadata in a database of structured data, the metadata comprising data about unstructured data; receiving a query directed toward a combination of structured and unstructured data, the query having a portion directed toward unstructured data, wherein the portion comprises at least one term for searching within unstructured data; retrieving structured data from a database of structured data in accordance with the received query, the retrieved structured data comprising at least a portion of the metadata; processing the retrieved structured data to identify a scope of unstructured data for retrieval from a data store of unstructured data; retrieving unstructured data from the data store of unstructured data corresponding to the identified scope of unstructured data; streaming the retrieved unstructured data through a processing device in a computing system other than a main processor for the system; and searching the retrieved streaming unstructured data based on the at least one query term using the processing device to find unstructured data within the retrieved streaming unstructured data that is responsive to the query. 8. The method of claim 1 further comprising: streaming new unstructured data through the processing device; performing a metadata generation operation on the streaming unstructured data using the processing device to thereby generate metadata about the new unstructured data; storing the new unstructured data in the data store of unstructured data; and storing the metadata about the new unstructured data in the database of structured data. | 0.637705 |
9,448,974 | 1 | 2 | 1. A server, comprising: a memory for storing a compressed file containing an XML document of one of a plurality of document types; and a processor connected to the memory and configured to: open the compressed file; load a relationships file of the XML document; parse contents of the relationships file of the XML document to detect an identifier of the one of the plurality of document types in the relationships file; and select a distiller corresponding to the one of the plurality of document types from among a plurality of distillers, and execute the distiller that is selected to parse data in the XML document to build a Document Object Model (DOM) for storage in the memory. | 1. A server, comprising: a memory for storing a compressed file containing an XML document of one of a plurality of document types; and a processor connected to the memory and configured to: open the compressed file; load a relationships file of the XML document; parse contents of the relationships file of the XML document to detect an identifier of the one of the plurality of document types in the relationships file; and select a distiller corresponding to the one of the plurality of document types from among a plurality of distillers, and execute the distiller that is selected to parse data in the XML document to build a Document Object Model (DOM) for storage in the memory. 2. The server of claim 1 , wherein the plurality of distillers includes a different distiller corresponding to each of the plurality of document types. | 0.803385 |
6,141,011 | 32 | 34 | 32. The method of claim 21, further comprising: displaying a status bar having hint information about operation of at least one key of the computing device during input. | 32. The method of claim 21, further comprising: displaying a status bar having hint information about operation of at least one key of the computing device during input. 34. The method of claim 32, wherein the hint information includes graphical information. | 0.980685 |
8,533,480 | 11 | 14 | 11. A system comprising: a processor; and a computer readable storage device storing a computer program which when executed by the processor causes the processor to perform a method comprising: receiving an electronic document including content items, a rule and a digital signature, wherein the rule specifies what parts of the electronic document are allowed to change based on user interaction with the electronic document; generating a digest for the electronic document by digesting all of the content items, using multiple functions based upon complexity of the content items, except for at least a first content item that is ignored in the digestion based on the rule; comparing the generated digest with a stored digest that is associated with the electronic document; and invalidating the digital signature if the generated digest indicates a difference in any of the digested content items, wherein if the generated digest indicates no difference in any of the digested content items, the method further comprises: subsequently receiving a user input attempting to create a new state of the received electronic document; determining whether the user input is allowed by the rule; and invalidating the digital signature if the user input is not allowed by the rule, and wherein the rule applies differently to a first author and a second author, such that the user input causes a first digital signature of the first author to be invalidated but does not cause a second digital signature of the second author to be invalidated. | 11. A system comprising: a processor; and a computer readable storage device storing a computer program which when executed by the processor causes the processor to perform a method comprising: receiving an electronic document including content items, a rule and a digital signature, wherein the rule specifies what parts of the electronic document are allowed to change based on user interaction with the electronic document; generating a digest for the electronic document by digesting all of the content items, using multiple functions based upon complexity of the content items, except for at least a first content item that is ignored in the digestion based on the rule; comparing the generated digest with a stored digest that is associated with the electronic document; and invalidating the digital signature if the generated digest indicates a difference in any of the digested content items, wherein if the generated digest indicates no difference in any of the digested content items, the method further comprises: subsequently receiving a user input attempting to create a new state of the received electronic document; determining whether the user input is allowed by the rule; and invalidating the digital signature if the user input is not allowed by the rule, and wherein the rule applies differently to a first author and a second author, such that the user input causes a first digital signature of the first author to be invalidated but does not cause a second digital signature of the second author to be invalidated. 14. The system of claim 11 , wherein the first content item is ignored in the digestion based on having a content item type specified by the rule. | 0.830233 |
8,171,041 | 15 | 16 | 15. The search engine server of claim 11 wherein the search engine server ranks the listed websites having international support, wherein ranking is based upon a popularity factor of the websites. | 15. The search engine server of claim 11 wherein the search engine server ranks the listed websites having international support, wherein ranking is based upon a popularity factor of the websites. 16. The search engine server of claim 15 wherein the search engine server delivers a first search result page comprising links of a first few of the ranked websites having international support, and wherein the search engine server performs language translation on content provided with the first few of the ranked websites. | 0.910398 |
8,731,945 | 14 | 17 | 14. The method of claim 12 , wherein the frames are used to parse the VP homonyms into VP and TRCC (Table, Row, Column, and Cell) segments, wherein the verb, prepositions and TRCC segments are processed producing a frame score that measures a fit of the frame's VP homonym to the frame's associated thematic patterns. | 14. The method of claim 12 , wherein the frames are used to parse the VP homonyms into VP and TRCC (Table, Row, Column, and Cell) segments, wherein the verb, prepositions and TRCC segments are processed producing a frame score that measures a fit of the frame's VP homonym to the frame's associated thematic patterns. 17. The method of claim 14 , wherein an adjusted advanced frame score includes a factor for a number of homonym changes to the VP homonyms. | 0.953543 |
8,359,020 | 7 | 8 | 7. The computer-implemented method of claim 1 , further comprising: determining, based on the current context, whether monitoring audio data for voice input will have at least a threshold level of convenience for a user associated with the mobile computing device and for the mobile computing device; wherein determining whether to switch to the second mode of operation is based on, at least, the determination of whether the user has at least the threshold likelihood of providing voice input. | 7. The computer-implemented method of claim 1 , further comprising: determining, based on the current context, whether monitoring audio data for voice input will have at least a threshold level of convenience for a user associated with the mobile computing device and for the mobile computing device; wherein determining whether to switch to the second mode of operation is based on, at least, the determination of whether the user has at least the threshold likelihood of providing voice input. 8. The computer-implemented method of claim 7 , wherein the current context indicates at least the threshold level of convenience for the user when manual operation of the mobile computing device is not readily available. | 0.933832 |
8,484,259 | 18 | 19 | 18. A network storage server node as recited in claim 12 , wherein the metadata subsystem is configured to store all of the metadata for each particular data object of the plurality of data objects in the same network storage node. | 18. A network storage server node as recited in claim 12 , wherein the metadata subsystem is configured to store all of the metadata for each particular data object of the plurality of data objects in the same network storage node. 19. A network storage server node as recited in claim 18 , wherein the metadata subsystem is configured to store all of the metadata for any particular data object in a network storage node in which the particular data object is stored. | 0.954317 |
9,372,681 | 6 | 7 | 6. The non-transitory computer-readable storage medium claim 5 , wherein the instructions when executed by one or more microprocessors further configure the web browser on the user's computing device to: in response to a navigation event on the user's computing device which leads to a navigated-to-document URL, determine if the navigated-to-document URL conforms to the declared document URL type in the manifest of the application and accordingly redirect the navigated-to-document URL to the application installed for opening a document associated with the navigated-to-document URL. | 6. The non-transitory computer-readable storage medium claim 5 , wherein the instructions when executed by one or more microprocessors further configure the web browser on the user's computing device to: in response to a navigation event on the user's computing device which leads to a navigated-to-document URL, determine if the navigated-to-document URL conforms to the declared document URL type in the manifest of the application and accordingly redirect the navigated-to-document URL to the application installed for opening a document associated with the navigated-to-document URL. 7. The non-transitory computer-readable storage medium of claim 6 , wherein configuring the web browser on the user's computing device to the navigated-to-document URL to the application includes configuring the web browser to launch the application. | 0.928571 |
4,712,242 | 11 | 12 | 11. A method as set forth in claim 10, wherein said feature vectors, said reference vectors and said mask vectors are binary, and wherein said distance measure-determining step comprises a Hamming distance measurement between said feature vector and a corresponding reference vector as modified in accordance with a respective mask vector associated therewith. | 11. A method as set forth in claim 10, wherein said feature vectors, said reference vectors and said mask vectors are binary, and wherein said distance measure-determining step comprises a Hamming distance measurement between said feature vector and a corresponding reference vector as modified in accordance with a respective mask vector associated therewith. 12. A method as set forth in claim 11, wherein a plurality of mask vectors are respectively associated with said plurality of reference vectors arrangd in each said reference vector sequence such that one mask vector is uniquely associated with a corresponding one of said reference vectors included in each said reference vector sequence. | 0.956281 |
8,135,582 | 6 | 11 | 6. The reduced keyboard system according to claim 5 , wherein at least one filter is operable to reduce the number of candidate words. | 6. The reduced keyboard system according to claim 5 , wherein at least one filter is operable to reduce the number of candidate words. 11. The reduced keyboard system according to claim 6 , wherein a recognition engine is applicable to compare the input word with candidate words selected after filtering. | 0.921875 |
8,914,358 | 2 | 3 | 2. The method of claim 1 , further comprising: determining the second search query is related to the first search query based on a temporal relationship between the first search query and the second search query. | 2. The method of claim 1 , further comprising: determining the second search query is related to the first search query based on a temporal relationship between the first search query and the second search query. 3. The method of claim 2 , wherein the temporal relationship is determined by analyzing log files. | 0.971227 |
9,672,541 | 11 | 15 | 11. A system comprising: a display screen operable to present a user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of web traffic associated with the respective webpage and it's at least one active tag indicator; a user input device operable to receive user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and a communications interface operable to transmit an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action. | 11. A system comprising: a display screen operable to present a user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of web traffic associated with the respective webpage and it's at least one active tag indicator; a user input device operable to receive user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and a communications interface operable to transmit an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action. 15. The system recited in claim 11 , wherein each webpage snapshot includes a respective visual thumbnail view of the webpage depicting how such webpage is presented when the webpage is rendered in a web browser. | 0.868649 |
9,110,983 | 7 | 8 | 7. The system of claim 1 , wherein the third association module further to structure the third association information as a third set of vectors corresponding to the plurality of textual descriptions, and the fourth association module further to structure the fourth association information as a fourth set of vectors corresponding to the one or more words. | 7. The system of claim 1 , wherein the third association module further to structure the third association information as a third set of vectors corresponding to the plurality of textual descriptions, and the fourth association module further to structure the fourth association information as a fourth set of vectors corresponding to the one or more words. 8. The system of claim 7 , wherein each vector in the third set of vectors further to have weight values that identify a frequency of occurrence of the one or more words in a respective textual description. | 0.933333 |
8,442,771 | 1 | 9 | 1. A method of using a data-processing apparatus, having a processor, to normalize an individual mention of a subcellular entity within a biomedical text document, the method comprising using the data-processing apparatus to carry out: inputting said individual mention of a subcellular entity; selecting a group of identifiers of subcellular entities, said subcellular entities being referred to in biomedical text with the same character string and being from different species, each of said species being a taxonomic group of organisms which can interbreed; generating, using said processor, a species identifier that identifies the species of said individual mention of a subcellular entity from the context of said mention of a subcellular entity; selecting an identifier from said group of identifiers, taking into account the species identifier that identifies the species of said individual mention of a subcellular entity; and outputting said identifier to provide a normalized reference to said subcellular entity. | 1. A method of using a data-processing apparatus, having a processor, to normalize an individual mention of a subcellular entity within a biomedical text document, the method comprising using the data-processing apparatus to carry out: inputting said individual mention of a subcellular entity; selecting a group of identifiers of subcellular entities, said subcellular entities being referred to in biomedical text with the same character string and being from different species, each of said species being a taxonomic group of organisms which can interbreed; generating, using said processor, a species identifier that identifies the species of said individual mention of a subcellular entity from the context of said mention of a subcellular entity; selecting an identifier from said group of identifiers, taking into account the species identifier that identifies the species of said individual mention of a subcellular entity; and outputting said identifier to provide a normalized reference to said subcellular entity. 9. A method according to claim 1 , wherein the biomedical text document includes mentions of subcellular entities relating to more than one species of organism. | 0.885387 |
8,417,948 | 22 | 26 | 22. An article of manufacture comprising a computer readable non-transitory storage medium storing a carrier script that is presented in the clear and a hidden script that is steganographically coded in the carrier script, the hidden script being different from the carrier script, the carrier script, when interpreted by a computer processor, causing the computer processor to generate a first sequence of instructions that are executed by the computer processor to carry out the directives of the carrier script and to extract and interpret the hidden script to generate a second sequence of instructions that are executed by the computer processor to carry out the directives of the hidden script. | 22. An article of manufacture comprising a computer readable non-transitory storage medium storing a carrier script that is presented in the clear and a hidden script that is steganographically coded in the carrier script, the hidden script being different from the carrier script, the carrier script, when interpreted by a computer processor, causing the computer processor to generate a first sequence of instructions that are executed by the computer processor to carry out the directives of the carrier script and to extract and interpret the hidden script to generate a second sequence of instructions that are executed by the computer processor to carry out the directives of the hidden script. 26. The article of manufacture of claim 22 wherein the carrier script is scripted in a first scripting language and the hidden script is scripted in a second scripting language that is different from the first scripting language. | 0.680168 |
8,620,909 | 1 | 6 | 1. A computer-implemented method for contextual personalized search, the method comprising: using a computer system to execute method steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. | 1. A computer-implemented method for contextual personalized search, the method comprising: using a computer system to execute method steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. 6. The method of claim 1 , wherein the matching comprises using a combination of both a) and b). | 0.941176 |
8,646,029 | 1 | 12 | 1. One or more computer-readable storage memories comprising computer readable instructions which, when executed, implement: a security module configured to enable secure information transfer between a web browser's scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, the module configured to enable the at least one object to be returned across the one or more domains being configured to return a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. | 1. One or more computer-readable storage memories comprising computer readable instructions which, when executed, implement: a security module configured to enable secure information transfer between a web browser's scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, the module configured to enable the at least one object to be returned across the one or more domains being configured to return a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 12. The one or more computer-readable storage memories of claim 1 , the at least one object associated with the proxy object comprising a function. | 0.849076 |
8,230,016 | 15 | 16 | 15. The method of claim 13 , further comprising: identifying a plurality of views of the application based on the traversed view hierarchy, wherein each of the plurality of views contains at least one of the plurality of components of the application; generating at least one component reference table for the application, the at least one component reference table including, for each of the plurality of views, the at least one component of the application contained in the view; and storing the at least one component reference table generated for the application. | 15. The method of claim 13 , further comprising: identifying a plurality of views of the application based on the traversed view hierarchy, wherein each of the plurality of views contains at least one of the plurality of components of the application; generating at least one component reference table for the application, the at least one component reference table including, for each of the plurality of views, the at least one component of the application contained in the view; and storing the at least one component reference table generated for the application. 16. The method of claim 15 , further comprising mapping the at least one component contained in each of the plurality of views included in the at least one component reference table to the application running on the user device. | 0.928705 |
4,803,641 | 6 | 7 | 6. A knowledge system comprising a computer having a memory, said memory storing a knowledge base including expressions and knowledge for determining values for said expressions, said memory including a cache porton for storing certain ones of said expressions and corresponding determined values for the stored expressions, said memory also storing a control procedure executable by said computer for interpreting the knowledge base to determine values for said expressions, said control procedure including means for recognizing the occurrence of an expression in the knowledge base, means for searching the cache to determine whether the recognized expression is stored in the cache, means for obtaining from the cache the corresponding value of the recognized expression when the recognized expession is in the cache, and means for applying the knowledge in the knowledge base to determine a corresponding value for the recognized expression when the recognized expression is not in the cache and then storing the recognized expression and its corresponding value in the cache. | 6. A knowledge system comprising a computer having a memory, said memory storing a knowledge base including expressions and knowledge for determining values for said expressions, said memory including a cache porton for storing certain ones of said expressions and corresponding determined values for the stored expressions, said memory also storing a control procedure executable by said computer for interpreting the knowledge base to determine values for said expressions, said control procedure including means for recognizing the occurrence of an expression in the knowledge base, means for searching the cache to determine whether the recognized expression is stored in the cache, means for obtaining from the cache the corresponding value of the recognized expression when the recognized expession is in the cache, and means for applying the knowledge in the knowledge base to determine a corresponding value for the recognized expression when the recognized expression is not in the cache and then storing the recognized expression and its corresponding value in the cache. 7. The knowledge system as claimed in claim 6, wherein said means for interpreting the knowledge base to determine a corresponding value includes means for determining a value indicating that the expression is unknown. | 0.896975 |
10,001,759 | 18 | 19 | 18. The apparatus of claim 11 , wherein the transceiver is further configured to transmit the events dictionary to other IoT devices in the IoT network. | 18. The apparatus of claim 11 , wherein the transceiver is further configured to transmit the events dictionary to other IoT devices in the IoT network. 19. The apparatus of claim 18 , wherein the at least one processor is further configured to define home automation rules based on generic events defined in the events dictionary; and wherein the transceiver is further configured to distribute the home automation rules to the other IoT devices in the IoT network. | 0.928571 |
9,373,030 | 29 | 31 | 29. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element, wherein the respective location in the image for each of the text elements includes Cartesian coordinates where the origin lies at a corner of the image and a distance from another location in the image for another text element and a distance from an edge of the image, the distance determined using respective Cartesian coordinates of each of the text elements, the another text element, and the edge of the image; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. | 29. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element, wherein the respective location in the image for each of the text elements includes Cartesian coordinates where the origin lies at a corner of the image and a distance from another location in the image for another text element and a distance from an edge of the image, the distance determined using respective Cartesian coordinates of each of the text elements, the another text element, and the edge of the image; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. 31. The system of claim 29 wherein the method further includes: storing the completed form in a data store. | 0.840299 |
8,271,845 | 9 | 15 | 9. A method for evaluating the operating safety of a system performing a macro function, comprising the following steps: constructing a functional architecture of the system, divided into several functional blocks each comprising data inputs/outputs, the inputs of a functional block being connected to the outputs of other functional blocks of the functional architecture; identifying failures associated with the functional blocks of the functional architecture, the identified failures taking a state selected from a group comprising a first active state, and a second inactive state; constructing a physical architecture divided into physical parts performing functions of the functional architecture; projecting the identified failures, associated with the functional blocks, on the physical parts; identifying physical failures based on the failures identified for the outputs of the functional blocks, the physical failures taking a state selected from a group consisting of a first active state, and a second inactive state; constructing second boolean expressions expressing the states of the outputs of the functional blocks as a function of the identified physical failures, the states of the inputs of the functional blocks, said input states of the blocks being reflected by at least one boolean; constructing one or more third boolean expressions, based on the second boolean expressions, each third boolean expression defining a feared event to be examined; reducing each third boolean expression in a sum of monomials; computing a probability of occurrence for the feared event based on probabilities of occurrence of the identified physical failures; and changing the functional architecture of the system in response to the first probability of occurrence of the feared event exceeding a predetermined threshold. | 9. A method for evaluating the operating safety of a system performing a macro function, comprising the following steps: constructing a functional architecture of the system, divided into several functional blocks each comprising data inputs/outputs, the inputs of a functional block being connected to the outputs of other functional blocks of the functional architecture; identifying failures associated with the functional blocks of the functional architecture, the identified failures taking a state selected from a group comprising a first active state, and a second inactive state; constructing a physical architecture divided into physical parts performing functions of the functional architecture; projecting the identified failures, associated with the functional blocks, on the physical parts; identifying physical failures based on the failures identified for the outputs of the functional blocks, the physical failures taking a state selected from a group consisting of a first active state, and a second inactive state; constructing second boolean expressions expressing the states of the outputs of the functional blocks as a function of the identified physical failures, the states of the inputs of the functional blocks, said input states of the blocks being reflected by at least one boolean; constructing one or more third boolean expressions, based on the second boolean expressions, each third boolean expression defining a feared event to be examined; reducing each third boolean expression in a sum of monomials; computing a probability of occurrence for the feared event based on probabilities of occurrence of the identified physical failures; and changing the functional architecture of the system in response to the first probability of occurrence of the feared event exceeding a predetermined threshold. 15. The method as claimed in claim 9 , wherein the method is suitable for an avionics system. | 0.94593 |
9,405,848 | 1 | 16 | 1. A method for recommending mobile device activities, the method comprising: receiving an indication of a content item contained on a Web page that is currently presented by a mobile device; determining semantic information about the indicated content item, including accessing a semantic network that is a graph data structure that includes multiple entities that each have is-a and/or member-of relations to other entities or categories of the semantic network, wherein the is-a and/or member-of relations are represented as links between the entities or categories of the semantic network, to: identify one or more entities in the semantic network that are referenced by the indicated content item and relationships relating to the identified entities; identify one or more entities in the semantic network that are related to the identified one or more entities; and identify one or more categories in the semantic network that are associated with the identified one or more entities and/or the related one or more entities, wherein the identified one or more categories are part of a taxonomic hierarchy in which each of the identified one or more categories is part of a corresponding taxonomic path that includes multiple categories related to one another via is-a relations, wherein the one or more categories are identified by traversing the links representing relations within the semantic network by traversing at most N taxonomic paths within the semantic network, where N is determined by user setting or data mining; determining a plurality of mobile device activities, wherein each activity has one or more associated entities and/or categories in common with the determined semantic information; and transmitting information about the determined plurality of activities. | 1. A method for recommending mobile device activities, the method comprising: receiving an indication of a content item contained on a Web page that is currently presented by a mobile device; determining semantic information about the indicated content item, including accessing a semantic network that is a graph data structure that includes multiple entities that each have is-a and/or member-of relations to other entities or categories of the semantic network, wherein the is-a and/or member-of relations are represented as links between the entities or categories of the semantic network, to: identify one or more entities in the semantic network that are referenced by the indicated content item and relationships relating to the identified entities; identify one or more entities in the semantic network that are related to the identified one or more entities; and identify one or more categories in the semantic network that are associated with the identified one or more entities and/or the related one or more entities, wherein the identified one or more categories are part of a taxonomic hierarchy in which each of the identified one or more categories is part of a corresponding taxonomic path that includes multiple categories related to one another via is-a relations, wherein the one or more categories are identified by traversing the links representing relations within the semantic network by traversing at most N taxonomic paths within the semantic network, where N is determined by user setting or data mining; determining a plurality of mobile device activities, wherein each activity has one or more associated entities and/or categories in common with the determined semantic information; and transmitting information about the determined plurality of activities. 16. The method of claim 1 wherein at least one of the activities has an associated category that is not the category of any entity that is directly referenced by the content item but that is the category of an entity that is in a relationship with an entity that is directly referenced by the content item. | 0.785414 |
8,321,517 | 10 | 13 | 10. A system for processing emails, comprising: one or more processors and one or more non-transitory computer readable mediums storing executable program instructions comprising: program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive a correction request including an identifier of an original email and an incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to the correction request, create a correction record including the identifier of the original email and the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving relevant emails of the original email, determine whether recipients of the relevant emails include the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that a sender of the correction request is not the incorrect recipient, sending the correction request to the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive from the incorrect recipient acknowledgment to the correction request; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving from the incorrect recipient the acknowledgment to the correction request, determining the correction record to be valid; and program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that recipients of the relevant emails include the incorrect recipient and in response to determining the correction record to be valid, process the relevant emails based on the correction record. | 10. A system for processing emails, comprising: one or more processors and one or more non-transitory computer readable mediums storing executable program instructions comprising: program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive a correction request including an identifier of an original email and an incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to the correction request, create a correction record including the identifier of the original email and the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving relevant emails of the original email, determine whether recipients of the relevant emails include the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that a sender of the correction request is not the incorrect recipient, sending the correction request to the incorrect recipient; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to receive from the incorrect recipient acknowledgment to the correction request; program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to receiving from the incorrect recipient the acknowledgment to the correction request, determining the correction record to be valid; and program instructions stored on the one or more non-transitory computer readable mediums for execution by at least one of the one or more processors to, in response to determining that recipients of the relevant emails include the incorrect recipient and in response to determining the correction record to be valid, process the relevant emails based on the correction record. 13. The system according to claim 10 , wherein, the correction request further includes a correct recipient, and the correction record further includes the correct recipient. | 0.847636 |
8,239,203 | 11 | 12 | 11. A computer program product implemented in a computer readable storage medium for adjusting operation of a speech recognition engine characterized by an associated receiver operating characteristic (ROC) curve, the product comprising: program code for interpreting user confirmation of speech recognition results within a given confidence score threshold to create a confirmed portion of the ROC curve for the speech recognition engine; program code for extending the confirmed portion of the ROC curve by extrapolation of unconfirmed speech recognition results beyond the confidence score threshold to generate an extended ROC curve; and program code for adjusting the confidence score threshold based on the extended ROC curve to meet target operating constraints for operating the speech recognition engine to perform automatic speech recognition of user speech inputs. | 11. A computer program product implemented in a computer readable storage medium for adjusting operation of a speech recognition engine characterized by an associated receiver operating characteristic (ROC) curve, the product comprising: program code for interpreting user confirmation of speech recognition results within a given confidence score threshold to create a confirmed portion of the ROC curve for the speech recognition engine; program code for extending the confirmed portion of the ROC curve by extrapolation of unconfirmed speech recognition results beyond the confidence score threshold to generate an extended ROC curve; and program code for adjusting the confidence score threshold based on the extended ROC curve to meet target operating constraints for operating the speech recognition engine to perform automatic speech recognition of user speech inputs. 12. A product according to claim 11 , wherein the confidence score threshold is an accept threshold such that speech recognition results having a confidence score below the accept threshold require user confirmation and speech recognition results having a confidence score above the accept threshold are accepted as correct without user confirmation. | 0.606742 |
7,958,155 | 1 | 19 | 1. A method for providing at least one client access to a network semantic graph distributed among a plurality of semantic servers wherein the network semantic graph comprises concept instances and relations between the concept instances, the method comprising: receiving first data including semantically distributed annotations from distributed data sources in communication with the plurality of semantic servers; based on the first data including the annotations, linking the concept instances using the relations; storing the concept instances and relations as a local semantic graph comprising a part of the network semantic graph; creating at least one subscription of interest over the network semantic graph in response to a request from the at least one client; collecting second data from the distributed data sources based on the at least one subscription; semantically annotating the second data; updating the local semantic graph based on the semantic annotation; sending alerts to the at least one client based on updates to the local semantic graph matching the at least one subscription of the at least one client. | 1. A method for providing at least one client access to a network semantic graph distributed among a plurality of semantic servers wherein the network semantic graph comprises concept instances and relations between the concept instances, the method comprising: receiving first data including semantically distributed annotations from distributed data sources in communication with the plurality of semantic servers; based on the first data including the annotations, linking the concept instances using the relations; storing the concept instances and relations as a local semantic graph comprising a part of the network semantic graph; creating at least one subscription of interest over the network semantic graph in response to a request from the at least one client; collecting second data from the distributed data sources based on the at least one subscription; semantically annotating the second data; updating the local semantic graph based on the semantic annotation; sending alerts to the at least one client based on updates to the local semantic graph matching the at least one subscription of the at least one client. 19. The method of claim 1 , wherein some of the distributed data sources include attributes of the at least one client. | 0.923816 |
8,127,270 | 10 | 11 | 10. Software stored in one or more computer-readable storage media for execution and when executed operable to: accept, as input at a transformation engine, a data file containing an implementation independent model written in a modeling language, wherein the implementation independent model includes one or more inheritable classes each of which includes zero or more attributes and zero or more relationships to another class; accept, as input at the transformation engine, a configuration file designating as a manageable resource one or more of the inheritable classes included in the implementation independent model, wherein the manageable resource represents a device having manageable capabilities, the manageable capabilities comprising connectivity and identity, and wherein the configuration file identifies one or more of the inheritable classes for exclusion; and output, at the transformation engine, each designated class as a manageable resource, wherein the manageable resource includes any subclasses by inheritance from the designated class unless excluded in the configuration file. | 10. Software stored in one or more computer-readable storage media for execution and when executed operable to: accept, as input at a transformation engine, a data file containing an implementation independent model written in a modeling language, wherein the implementation independent model includes one or more inheritable classes each of which includes zero or more attributes and zero or more relationships to another class; accept, as input at the transformation engine, a configuration file designating as a manageable resource one or more of the inheritable classes included in the implementation independent model, wherein the manageable resource represents a device having manageable capabilities, the manageable capabilities comprising connectivity and identity, and wherein the configuration file identifies one or more of the inheritable classes for exclusion; and output, at the transformation engine, each designated class as a manageable resource, wherein the manageable resource includes any subclasses by inheritance from the designated class unless excluded in the configuration file. 11. The software of claim 10 , wherein the class relationships include association and composition. | 0.830479 |
5,555,344 | 11 | 12 | 11. A method for recognizing patterns in time-variant measurement signals by classifying a temporal sequence of feature vectors and reclassification in pairs, comprising the steps of: segmenting the sequence of feature vectors which is to be classified using a Viterbi decoding algorithm, this sequence to be classified being compared with a set of hidden Markov models; calculating for each hidden Markov model a total emission probability for the generation of the sequence to be classified by this hidden Markov model; determining an optimum assignment path from feature vectors to states of the hidden Markov models by backtracking; calculating, for at least one pair of hidden Markov models, modified total emission probabilities for each hidden Markov model of said at least one pair on a precondition that a respective other hidden Markov model of a same pair competes with the hidden Markov model under review, a local logarithmic modified emission probability being calculated for all feature vectors of the temporal sequence for generating a respective feature vector by the corresponding state of the respective hidden Markov model by adding local logarithmic modified emission probabilities recursively along the already calculated assignment path to an accumulated logarithmic modified emission probability, a total emission probability being calculated, for generating the sequence to be classified by a hidden Markov model, by calculating for all feature vectors of the sequence to be classified and for all states of the hidden Markov model a local logarithmic emission probability for generating the respective feature vector by the respective state, and by calculating an accumulated logarithmic emission probability for each state as a sum of its local logarithmic emission probability and an accumulated logarithmic emission probability of its best possible predecessor state, the best possible predecessor state being logged; determining a respective more probable hidden Markov model of said at least one pair; and selecting the hidden Markov model having the highest total emission probability from among all pairs under review. | 11. A method for recognizing patterns in time-variant measurement signals by classifying a temporal sequence of feature vectors and reclassification in pairs, comprising the steps of: segmenting the sequence of feature vectors which is to be classified using a Viterbi decoding algorithm, this sequence to be classified being compared with a set of hidden Markov models; calculating for each hidden Markov model a total emission probability for the generation of the sequence to be classified by this hidden Markov model; determining an optimum assignment path from feature vectors to states of the hidden Markov models by backtracking; calculating, for at least one pair of hidden Markov models, modified total emission probabilities for each hidden Markov model of said at least one pair on a precondition that a respective other hidden Markov model of a same pair competes with the hidden Markov model under review, a local logarithmic modified emission probability being calculated for all feature vectors of the temporal sequence for generating a respective feature vector by the corresponding state of the respective hidden Markov model by adding local logarithmic modified emission probabilities recursively along the already calculated assignment path to an accumulated logarithmic modified emission probability, a total emission probability being calculated, for generating the sequence to be classified by a hidden Markov model, by calculating for all feature vectors of the sequence to be classified and for all states of the hidden Markov model a local logarithmic emission probability for generating the respective feature vector by the respective state, and by calculating an accumulated logarithmic emission probability for each state as a sum of its local logarithmic emission probability and an accumulated logarithmic emission probability of its best possible predecessor state, the best possible predecessor state being logged; determining a respective more probable hidden Markov model of said at least one pair; and selecting the hidden Markov model having the highest total emission probability from among all pairs under review. 12. The method as claimed in claim 11, wherein the method further comprises calculating the modified local emission probability, for generating a feature vector by a state of a hidden Markov model, by calculating a logarithmic emission probability for each component of this feature vector and multiplying the logarithmic emission probability by a weighting, and by summing these weighted logarithmic emission probabilities over all components of this feature vector; the weighting of a component of a feature vector being in this case a measure of the reliability of this component on an assumption that only two specific states of a hidden Markov model are to be compared with one another. | 0.500723 |
7,707,173 | 14 | 15 | 14. A web services selection server receiving service requests from customers and selecting a workflow from one of a plurality of providers, said web services selection server comprising: a task database storing a set of alternative workflows for requested services, wherein each of said alternative workflows comprises multiple web services executed to accomplish a task and wherein each of said alternative workflows is associated with a different provider; an evaluator module storing performance information from previous web service invocations by said providers; a policies module storing metarules, wherein each of said metarules comprises at least one condition and at least one action to be used in response to an instance of said at least one condition, said at least one condition comprising at least one parameter representing a context of a user and said at least one action comprising at least one directive for selecting services; a workflow engine ranking, for each of said metarules and based on said performance information, said alternative workflows in said set of alternative workflows in order to output a set of context-dependent alternative workflows, including summaries of conditions under which each of said alternative workflows in said set of context-dependent alternative workflows should be executed; and an executor module receiving a customer service request from a customer, matching context information from said customer with a summary of conditions for a first ranked one of said context-dependent alternative workflows, and automatically selecting said first ranked one of said context-dependent alternative workflows for execution in response to said customer service request. | 14. A web services selection server receiving service requests from customers and selecting a workflow from one of a plurality of providers, said web services selection server comprising: a task database storing a set of alternative workflows for requested services, wherein each of said alternative workflows comprises multiple web services executed to accomplish a task and wherein each of said alternative workflows is associated with a different provider; an evaluator module storing performance information from previous web service invocations by said providers; a policies module storing metarules, wherein each of said metarules comprises at least one condition and at least one action to be used in response to an instance of said at least one condition, said at least one condition comprising at least one parameter representing a context of a user and said at least one action comprising at least one directive for selecting services; a workflow engine ranking, for each of said metarules and based on said performance information, said alternative workflows in said set of alternative workflows in order to output a set of context-dependent alternative workflows, including summaries of conditions under which each of said alternative workflows in said set of context-dependent alternative workflows should be executed; and an executor module receiving a customer service request from a customer, matching context information from said customer with a summary of conditions for a first ranked one of said context-dependent alternative workflows, and automatically selecting said first ranked one of said context-dependent alternative workflows for execution in response to said customer service request. 15. The web services selection server according to claim 14 , said executor module further automatically selects a next ranked one of said context-dependent alternative workflows for execution, if an immediately preceding ranked workflow fails to execute. | 0.501953 |
7,596,498 | 4 | 5 | 4. The computer-readable storage medium of claim 3 wherein the monitoring application provides visual indications of the classifications of a plurality of conversations. | 4. The computer-readable storage medium of claim 3 wherein the monitoring application provides visual indications of the classifications of a plurality of conversations. 5. The computer-readable storage medium of claim 4 wherein the visual indications of the classifications of the plurality of conversations are provided while the conversations are in progress. | 0.9 |
9,081,496 | 7 | 8 | 7. A method of controlling the operation of a mobile terminal, the method comprising: displaying an electronic document on a display module of the mobile terminal; responsive to a scroll command received when in an operating mode operable to receive a scroll command, scrolling the electronic document in a first direction; decreasing a scrolling speed of the electronic document upon the first event of 1) receiving a user input other than the scroll command or an event occurs, 2) entering another operating mode, or 3) encountering a predefined item during the scrolling of the electronic document, the predefined item being a favorite item selected in advance by a user and being displayed in a different color or shape from other items of the electronic document; realigning the electronic document around the predefined item by scrolling the electronic document in a second direction different from the first direction so that the predefined item can be displayed at a predefined position on the display module; responsive to detecting a touch on the predefined item, displaying an information window relevant to the predefined item over the electronic document; and responsive to detecting another scroll command within the displayed information window, scrolling contents of the information window in response to the other scroll command, wherein a scroll limit is the predefined item, and responsive to detecting a touch input on a part of the electronic document other than the predefined item while the scrolling is stopped, scrolling the electronic document back in the first direction. | 7. A method of controlling the operation of a mobile terminal, the method comprising: displaying an electronic document on a display module of the mobile terminal; responsive to a scroll command received when in an operating mode operable to receive a scroll command, scrolling the electronic document in a first direction; decreasing a scrolling speed of the electronic document upon the first event of 1) receiving a user input other than the scroll command or an event occurs, 2) entering another operating mode, or 3) encountering a predefined item during the scrolling of the electronic document, the predefined item being a favorite item selected in advance by a user and being displayed in a different color or shape from other items of the electronic document; realigning the electronic document around the predefined item by scrolling the electronic document in a second direction different from the first direction so that the predefined item can be displayed at a predefined position on the display module; responsive to detecting a touch on the predefined item, displaying an information window relevant to the predefined item over the electronic document; and responsive to detecting another scroll command within the displayed information window, scrolling contents of the information window in response to the other scroll command, wherein a scroll limit is the predefined item, and responsive to detecting a touch input on a part of the electronic document other than the predefined item while the scrolling is stopped, scrolling the electronic document back in the first direction. 8. The method of claim 7 , further comprising: generating a screen haptic effect when scrolling past the end portion of the electronic document. | 0.85124 |
7,642,934 | 11 | 15 | 11. A handheld electronic device, comprising: a keyboard having a plurality of input members, a subset of said plurality of input members each having a first character assignment comprising a first set of letters; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines, including a disambiguation routine, which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting a predetermined first input; responsive to said detecting a predetermined first input, displaying a representation of a keypad comprising a plurality of keys wherein at least some of the keys each have a second character assignment comprising a second set of letters, wherein the at least some of said keys have a spatial position that corresponds to a spatial position of an input member in said subset; altering said first character assignments of at least some of said input members of said subset to each correspond with said second character assignment of a key having a corresponding spatial position; subsequent to said altering, detecting a second input; employing said disambiguation function to generate a linguistic interpretation of said second input; and outputting said linguistic interpretation. | 11. A handheld electronic device, comprising: a keyboard having a plurality of input members, a subset of said plurality of input members each having a first character assignment comprising a first set of letters; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines, including a disambiguation routine, which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting a predetermined first input; responsive to said detecting a predetermined first input, displaying a representation of a keypad comprising a plurality of keys wherein at least some of the keys each have a second character assignment comprising a second set of letters, wherein the at least some of said keys have a spatial position that corresponds to a spatial position of an input member in said subset; altering said first character assignments of at least some of said input members of said subset to each correspond with said second character assignment of a key having a corresponding spatial position; subsequent to said altering, detecting a second input; employing said disambiguation function to generate a linguistic interpretation of said second input; and outputting said linguistic interpretation. 15. The handheld electronic device according to claim 11 , wherein said linguistic interpretation is a word stored on said handheld electronic device. | 0.841772 |
8,615,388 | 14 | 16 | 14. A method performed by one or more computers comprised of one or more processors and physical storage, the method comprising: providing a statistical machine translation model, stored in the physical storage, and configured to allow the one or more processors to compute probabilities of translations of phrases, wherein the phrases are in a human language and the translations of the phrases are in the same human language, the statistical machine translation model having been trained with training pairs, the training pairs having been computed from a list of text queries in the human language submitted to a search engine and from a list of text sentences in the human language returned by the search engine when the text queries were submitted to the search engine, and by comparing the text queries to the text sentences to identify which of the text queries are similar to which of the text sentences, where text sentences identified as similar to text queries are respectively paired to form the training pairs; and using, by the processor, the statistical machine translation model to translate between query forms and listing forms of organizations and/or businesses, where the query forms comprise phrases, in the human language, submitted to the search engine, and where the listing forms comprise formal names, in the human language, of organizations and/or businesses searchable by the search engine. | 14. A method performed by one or more computers comprised of one or more processors and physical storage, the method comprising: providing a statistical machine translation model, stored in the physical storage, and configured to allow the one or more processors to compute probabilities of translations of phrases, wherein the phrases are in a human language and the translations of the phrases are in the same human language, the statistical machine translation model having been trained with training pairs, the training pairs having been computed from a list of text queries in the human language submitted to a search engine and from a list of text sentences in the human language returned by the search engine when the text queries were submitted to the search engine, and by comparing the text queries to the text sentences to identify which of the text queries are similar to which of the text sentences, where text sentences identified as similar to text queries are respectively paired to form the training pairs; and using, by the processor, the statistical machine translation model to translate between query forms and listing forms of organizations and/or businesses, where the query forms comprise phrases, in the human language, submitted to the search engine, and where the listing forms comprise formal names, in the human language, of organizations and/or businesses searchable by the search engine. 16. A method according to claim 14 , wherein, given a user query inputted by a user in the human language, given a corresponding listing in the human language that was found by the search engine, and given a set of candidate translations of the listing, the candidate translations also in the human language, the using the statistical machine translation model comprises computing probabilities of the candidate translations. | 0.823358 |
8,744,838 | 1 | 5 | 1. A method for contextualizing operating procedures, comprising: receiving a set of procedures, each procedure including text describing user actions which are to be performed on a physical device to implement the procedure; providing a model of the device which refers to a set of components of the physical device on which user actions are performable, for each of the components in the set, the device model providing a state chart which links an action performable on the component with states assumed by the component before and after the action is performed; for each procedure in the set, segmenting the text into a sequence of instruction steps, each instruction step including an action to be performed on one of the components of the device that is referred to in the device model, the segmenting of the text including natural language processing the text to identify action verbs and their objects in the text, and where an object of the action verb refers to a component in the device model, tagging the object with the referenced component; receiving a request for one of the procedures; retrieving the sequence of instruction steps for the requested procedure; receiving device data from the physical device; for each of a plurality of the instruction steps in the retrieved sequence, contextualizing a current one of the instruction steps, based on the device data and the state chart of the respective component referred to in the device model; and outputting a representation of the contextualized instruction step to a display device. | 1. A method for contextualizing operating procedures, comprising: receiving a set of procedures, each procedure including text describing user actions which are to be performed on a physical device to implement the procedure; providing a model of the device which refers to a set of components of the physical device on which user actions are performable, for each of the components in the set, the device model providing a state chart which links an action performable on the component with states assumed by the component before and after the action is performed; for each procedure in the set, segmenting the text into a sequence of instruction steps, each instruction step including an action to be performed on one of the components of the device that is referred to in the device model, the segmenting of the text including natural language processing the text to identify action verbs and their objects in the text, and where an object of the action verb refers to a component in the device model, tagging the object with the referenced component; receiving a request for one of the procedures; retrieving the sequence of instruction steps for the requested procedure; receiving device data from the physical device; for each of a plurality of the instruction steps in the retrieved sequence, contextualizing a current one of the instruction steps, based on the device data and the state chart of the respective component referred to in the device model; and outputting a representation of the contextualized instruction step to a display device. 5. The method of claim 1 , wherein the device data includes a current state of a component of the physical device and the method includes contextualizing the device model with the current state of the component. | 0.908895 |
9,224,384 | 6 | 9 | 6. A method for acoustic signal processing comprising: receiving acoustic features obtained from an input analog signal representing an incoming voice signal; pruning one or more Hidden Markov Model (HMM) states based on one or more current HMM pruning thresholds to generate one or more active HMM states; pre-pruning the one or more active HMM states based on an adjustable pre-pruning threshold to generate active HMM states output of the pre-pruning unit, wherein the adjustable pre-pruning threshold is based on one or more prior pruning thresholds, and wherein the active HMM states output of the pre-pruning unit each indicate a phoneme of the incoming voice signal and are each associated with a HMM state score; calculating the adjustable pre-pruning threshold based on an HMM state score from a previous frame of data and a senone score, wherein the pre-pruning follows the pruning for a current frame the incoming voice signal and precedes the pruning for a next frame; transferring the phonemes and their associated HMM state scores to a further speech recognition stage; and generating recognized speech corresponding to the incoming voice signal at the further speech recognition stage. | 6. A method for acoustic signal processing comprising: receiving acoustic features obtained from an input analog signal representing an incoming voice signal; pruning one or more Hidden Markov Model (HMM) states based on one or more current HMM pruning thresholds to generate one or more active HMM states; pre-pruning the one or more active HMM states based on an adjustable pre-pruning threshold to generate active HMM states output of the pre-pruning unit, wherein the adjustable pre-pruning threshold is based on one or more prior pruning thresholds, and wherein the active HMM states output of the pre-pruning unit each indicate a phoneme of the incoming voice signal and are each associated with a HMM state score; calculating the adjustable pre-pruning threshold based on an HMM state score from a previous frame of data and a senone score, wherein the pre-pruning follows the pruning for a current frame the incoming voice signal and precedes the pruning for a next frame; transferring the phonemes and their associated HMM state scores to a further speech recognition stage; and generating recognized speech corresponding to the incoming voice signal at the further speech recognition stage. 9. The method according to claim 6 , wherein the calculating the adjustable pre-pruning threshold is based on one or more senone scores from a previous frame of data. | 0.890933 |
8,972,398 | 5 | 6 | 5. A server system, comprising one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions, which when executed by the one or more processors, cause the server system to: receive a search query from a first user; obtain a plurality of candidate identifiers representing the first user, wherein the plurality of candidate identifiers is generated using all or a portion of a name of the first user; provide the first user with a query as to whether they are associated with a first candidate identifier in the plurality of candidate identifiers including: (i) provide the first user with an annotation comprising identification of a second user and a first affordance to confirm the first candidate identifier when the first user selects the affordance; (ii) detect selection of the first affordance; and (iii) in response to detecting selection of the first affordance, confirm the first candidate identifier is associated with the first user; identify a social network set of search results that (i) matches the search query and (ii) satisfies a social network criteria for the first user, wherein the social network criteria is satisfied for a respective search result when the respective search result is annotated by the second user, distinct from the first user, represented by one or more author identifiers, and at least one author identifier of the one or more author identifiers represents the second user and is associated, in a social network application, with the confirmed first candidate identifier; identify a particular social network application on which the first user and the second user are potentially connected; and formatting for concurrent presentation to the first user: (i) a search result, in the social network set of search results, published on the particular social network application by the second user, and (ii) information identifying the particular social network application. | 5. A server system, comprising one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions, which when executed by the one or more processors, cause the server system to: receive a search query from a first user; obtain a plurality of candidate identifiers representing the first user, wherein the plurality of candidate identifiers is generated using all or a portion of a name of the first user; provide the first user with a query as to whether they are associated with a first candidate identifier in the plurality of candidate identifiers including: (i) provide the first user with an annotation comprising identification of a second user and a first affordance to confirm the first candidate identifier when the first user selects the affordance; (ii) detect selection of the first affordance; and (iii) in response to detecting selection of the first affordance, confirm the first candidate identifier is associated with the first user; identify a social network set of search results that (i) matches the search query and (ii) satisfies a social network criteria for the first user, wherein the social network criteria is satisfied for a respective search result when the respective search result is annotated by the second user, distinct from the first user, represented by one or more author identifiers, and at least one author identifier of the one or more author identifiers represents the second user and is associated, in a social network application, with the confirmed first candidate identifier; identify a particular social network application on which the first user and the second user are potentially connected; and formatting for concurrent presentation to the first user: (i) a search result, in the social network set of search results, published on the particular social network application by the second user, and (ii) information identifying the particular social network application. 6. The server system of claim 5 , wherein the social network set of search results includes: a first set of search results authored or annotated by one or more author identifiers associated with at least one candidate identifier of the plurality of candidate identifiers associated with the first user, and a second set of search results authored or annotated by one or more author identifiers associated with at least one known identifier of the first user. | 0.724428 |
8,856,730 | 1 | 5 | 1. A computing system comprising: at least one processor; and one or more storage medium having stored computer-executable instructions which, when executed by the at least one processor, implement a method of defining a layout of diagram elements, the method comprising: a computer system, which includes a processor, receiving user input, the user input comprising one or more declarative statements specifying conditional patterns based on attributes of diagram elements, the conditional patterns defining layouts of diagram elements, wherein implementation of the layouts is dependent on conditions defined in the declarative statements and one or more values of one or more of the attributes; the computer system organizing the conditional patterns as a pattern definition, wherein organizing the conditional patterns as a pattern definition comprises at least one of: combining conditional patterns together to create a higher order pattern with a previously defined pattern being included in a new pattern as a definition field, or breaking down a conditional pattern into the two or more patterns which are both applied to a same situation, but which define different aspects of a diagram; and the computer system storing the pattern definition on a computer readable medium, wherein the pattern definition is stored such that the pattern definition is retrievable by an application program that uses the pattern definition to evaluate the conditional patterns using values of attributes of one or more diagram elements, the application further being configured to display representations of the diagram elements according to the layouts when conditions for implementing the layouts are satisfied. | 1. A computing system comprising: at least one processor; and one or more storage medium having stored computer-executable instructions which, when executed by the at least one processor, implement a method of defining a layout of diagram elements, the method comprising: a computer system, which includes a processor, receiving user input, the user input comprising one or more declarative statements specifying conditional patterns based on attributes of diagram elements, the conditional patterns defining layouts of diagram elements, wherein implementation of the layouts is dependent on conditions defined in the declarative statements and one or more values of one or more of the attributes; the computer system organizing the conditional patterns as a pattern definition, wherein organizing the conditional patterns as a pattern definition comprises at least one of: combining conditional patterns together to create a higher order pattern with a previously defined pattern being included in a new pattern as a definition field, or breaking down a conditional pattern into the two or more patterns which are both applied to a same situation, but which define different aspects of a diagram; and the computer system storing the pattern definition on a computer readable medium, wherein the pattern definition is stored such that the pattern definition is retrievable by an application program that uses the pattern definition to evaluate the conditional patterns using values of attributes of one or more diagram elements, the application further being configured to display representations of the diagram elements according to the layouts when conditions for implementing the layouts are satisfied. 5. The system of claim 1 , wherein organizing the conditional patterns as a pattern definition comprises breaking down the conditional patterns into the two or more patterns. | 0.720257 |
9,123,331 | 13 | 15 | 13. The system of claim 12 , wherein the sample utterance-to-text-string mappings were selected by the system, and wherein selecting the sample utterance-to-text-string mappings further comprises: determining a second word selection probability for a second word based on the second compressed word frequency divided by a second word frequency of the second word, wherein the particular text string also contains the second word; and selecting the particular utterance based on the first word selection probability and second word selection probability. | 13. The system of claim 12 , wherein the sample utterance-to-text-string mappings were selected by the system, and wherein selecting the sample utterance-to-text-string mappings further comprises: determining a second word selection probability for a second word based on the second compressed word frequency divided by a second word frequency of the second word, wherein the particular text string also contains the second word; and selecting the particular utterance based on the first word selection probability and second word selection probability. 15. The system of claim 13 , wherein selecting the particular utterance based on the first word selection probability and second word selection probability comprises: calculating a geometric mean of the first word selection probability and the second word selection probability; and selecting the particular utterance with a probability of the geometric mean. | 0.818687 |
10,095,696 | 2 | 4 | 2. The system of claim 1 , wherein the one or more temporal attributes and/or spatial attributes include one or more of a geolocation attribute, a device attribute, and/or a content attribute. | 2. The system of claim 1 , wherein the one or more temporal attributes and/or spatial attributes include one or more of a geolocation attribute, a device attribute, and/or a content attribute. 4. The system of claim 2 , wherein the device attribute includes a type of capturing device that captured the digital media content. | 0.970284 |
9,213,768 | 14 | 24 | 14. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: cause a query to be transmitted via a network to a query answering system, wherein the query is in an imprecise syntax and includes a word having multiple meanings or senses; receive query results that are based on a first meaning or sense of the word in response to the query, wherein: when the word is not recognized by the query answering system, the query answering system: determines, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, one or more entities to which the word corresponds, or chooses, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, the first meaning or sense; when the word is recognized by the query answering system and the word refers to multiple entities, the query answering system determines, with one or more computing devices, the entities to which the word corresponds; when the word corresponds to multiple entities in a same category, the query answering system ranks, with one or more computing devices, the multiple entities in the same category to which the word corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, the multiple meanings or senses of the word based on attributes of a user; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, one or more meanings or senses of the word based on a measure of popularity of the one or more meanings or senses; and when the word corresponds to multiple entities in a same category, or the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system chooses, with one or more computing devices, the first meaning or sense based on the rankings; receive an indication of the first meaning or sense of the word in response to the query, wherein the first meaning or sense corresponds to an entity in a category; receive a user interface mechanism to permit selection of another meaning or sense from a set of one or more meanings or senses different than the first meaning or sense in response to the query; and cause the query results, the indication of the first meaning or sense of the word, and the user interface mechanism to be displayed on a display device, wherein a list of entities in the same category to which the word corresponds are displayed in an order according to a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories. | 14. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: cause a query to be transmitted via a network to a query answering system, wherein the query is in an imprecise syntax and includes a word having multiple meanings or senses; receive query results that are based on a first meaning or sense of the word in response to the query, wherein: when the word is not recognized by the query answering system, the query answering system: determines, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, one or more entities to which the word corresponds, or chooses, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, the first meaning or sense; when the word is recognized by the query answering system and the word refers to multiple entities, the query answering system determines, with one or more computing devices, the entities to which the word corresponds; when the word corresponds to multiple entities in a same category, the query answering system ranks, with one or more computing devices, the multiple entities in the same category to which the word corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, the multiple meanings or senses of the word based on attributes of a user; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, one or more meanings or senses of the word based on a measure of popularity of the one or more meanings or senses; and when the word corresponds to multiple entities in a same category, or the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system chooses, with one or more computing devices, the first meaning or sense based on the rankings; receive an indication of the first meaning or sense of the word in response to the query, wherein the first meaning or sense corresponds to an entity in a category; receive a user interface mechanism to permit selection of another meaning or sense from a set of one or more meanings or senses different than the first meaning or sense in response to the query; and cause the query results, the indication of the first meaning or sense of the word, and the user interface mechanism to be displayed on a display device, wherein a list of entities in the same category to which the word corresponds are displayed in an order according to a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories. 24. The tangible, non-transitory storage medium according to claim 14 , wherein when the word is not recognized by the query answering system, the query results are determined from a keyword generated based on an analysis of the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word. | 0.734694 |
8,543,511 | 14 | 19 | 14. The method of claim 8 , wherein transforming the at least one digital data element and the at least one attribute to create a legality expression comprises: specifying with one or more of said claim elements a preference policy specifying a preference for one of processing and accepting respective one or more of said clause elements. | 14. The method of claim 8 , wherein transforming the at least one digital data element and the at least one attribute to create a legality expression comprises: specifying with one or more of said claim elements a preference policy specifying a preference for one of processing and accepting respective one or more of said clause elements. 19. The method of claim 14 , wherein said preference policy includes said preference based on a combination of at least two of an order of occurrence of said one or more of said clause elements, issuance times of said one or more of said clause elements, issuers of said one or more of said clause elements, and a type of said one or more of said clause elements. | 0.841346 |
8,688,746 | 10 | 23 | 10. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting to the user a subset of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. | 10. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting to the user a subset of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. 23. The method of claim 10 , wherein the subset of content items selected and presented to the user is presented as a browsable hierarchy of content items. | 0.873366 |
7,933,952 | 1 | 12 | 1. A non-transitory computer-readable medium including executable instructions which, when executed, collaborate information by: using a computer-implemented client to define an assembly workspace including associating one or more users as one or more participants of the assembly workspace, wherein the client is configured to interact with other clients as part of a collaborative authoring effort; associating an assembly document, including using a master assembly document to track and maintain user changes, with the assembly workspace including providing an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions, and using an assembly document proxy to build the assembly document using stored information and an assembly document object to create a number of sections and a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation; applying a number of constraints to the assembly document, wherein the number of constraints determines which of the one or more participants is permitted to interact with the number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; and, generating a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. | 1. A non-transitory computer-readable medium including executable instructions which, when executed, collaborate information by: using a computer-implemented client to define an assembly workspace including associating one or more users as one or more participants of the assembly workspace, wherein the client is configured to interact with other clients as part of a collaborative authoring effort; associating an assembly document, including using a master assembly document to track and maintain user changes, with the assembly workspace including providing an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions, and using an assembly document proxy to build the assembly document using stored information and an assembly document object to create a number of sections and a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation; applying a number of constraints to the assembly document, wherein the number of constraints determines which of the one or more participants is permitted to interact with the number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; and, generating a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. 12. The non-transitory computer-readable medium of claim 1 , wherein the instructions, when executed, collaborate information by using a schema to identify the assembly workspace associated with the assembly document. | 0.881937 |
7,478,100 | 13 | 17 | 13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document; hierarchical information for the node stored in the volatile or non-volatile computer usable storage medium; and node data for the node stored in the volatile or non-volatile computer usable storage medium. | 13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document; hierarchical information for the node stored in the volatile or non-volatile computer usable storage medium; and node data for the node stored in the volatile or non-volatile computer usable storage medium. 17. The computer-implemented structure of claim 13 in which the path string comprises a full path for the node. | 0.847527 |
8,346,815 | 19 | 20 | 19. The method of claim 18 , wherein determining an insertion score further comprises: determining an image intent score for the search query; and determining the insertion score from the image intent score and the central tendency score. | 19. The method of claim 18 , wherein determining an insertion score further comprises: determining an image intent score for the search query; and determining the insertion score from the image intent score and the central tendency score. 20. The method of claim 19 , wherein determining the image intent score for the search query comprises: determining a search property ratio of the search query that is proportional to a number of times the search query was submitted by client devices a search of the image corpus to a number of times that the search query was submitted by client devices for a search of the resource corpus; determining an image click-through rate of image search results presented with general search results in response to the search query; and determining the image intent score from the search property ratio and the image click-through rate. | 0.851904 |
7,567,951 | 10 | 11 | 10. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer, will cause the computer to: provide a user interface operative to receive the selection of a user interface object corresponding to an organizational electronic mail folder, the organizational electronic mail folder being associated with at least one electronic mail user; and in response to receiving the selection of the user interface object, display an organizational policy statement associated with the selected organizational folder, the organizational policy statement comprising a plurality of words describing a policy applied to the organizational folder and data identifying at least one of the following: an intended use for the organizational electronic mail folder and a retention period for electronic mail messages stored in the organizational electronic mail folder, wherein a length of the retention period is dependent upon the intended use for the organizational electronic mail folder, and wherein the retention period and the intended use are dependent upon at least one employment aspect of the at least one electronic mail user associated with the organizational folder. | 10. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer, will cause the computer to: provide a user interface operative to receive the selection of a user interface object corresponding to an organizational electronic mail folder, the organizational electronic mail folder being associated with at least one electronic mail user; and in response to receiving the selection of the user interface object, display an organizational policy statement associated with the selected organizational folder, the organizational policy statement comprising a plurality of words describing a policy applied to the organizational folder and data identifying at least one of the following: an intended use for the organizational electronic mail folder and a retention period for electronic mail messages stored in the organizational electronic mail folder, wherein a length of the retention period is dependent upon the intended use for the organizational electronic mail folder, and wherein the retention period and the intended use are dependent upon at least one employment aspect of the at least one electronic mail user associated with the organizational folder. 11. The computer-readable storage medium of claim 10 , wherein the computer-executable instructions are further operative to display the user interface object corresponding to the organizational electronic mail folder in a manner that differentiates the user interface object from other user interface objects corresponding to other types of mail folders. | 0.501404 |
7,908,234 | 3 | 7 | 3. The method of claim 1 , using the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising: generating a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generating a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and comparing the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL. | 3. The method of claim 1 , using the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising: generating a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generating a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and comparing the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL. 7. The method of claim 3 , the generating a negative usefulness prediction value further comprising: determining the negative usefulness prediction value to be a ratio of a negative probability to a sum of the negative probability and a positive probability, the positive probability being a product of a positive URL probability and a positive feature probability for each feature extracted from the given URL, the negative probability being a product of a negative URL probability and a negative feature probability for each feature extracted from the given URL, the positive URL probability being a ratio of a number of URLs classified as positive in the training set to a total number of URLs in the training set, the negative URL probability being a ratio of a number of URLs classified as negative in the training set to the total number of URLs in the training set, the positive feature probability for each feature being a ratio of a number of URLs in the training set that are classified as positive that include the feature to the number of URLs classified as positive in the training set, and the negative feature probability for each feature being a number of URLs in the training set that are classified as negative that include the feature to the number of URLs classified as negative in the training set. | 0.580471 |
9,372,093 | 7 | 8 | 7. A system comprising: a processor; a memory coupled with the processor; first logic stored in the memory and executable by the processor to cause the processor to receive at least a portion of a conversational narrative descriptive of a route to a destination expressed by a provider, the expressed conversational narrative comprising a plurality of conversational elements, a portion of which includes at least one non-verbal physical movement of a portion of a human body, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements, the first logic being further executable by the processor to cause the processor to receive the portion of the conversational narrative comprising the at least one non-verbal physical movement of a portion of a human body via an optical sensor, a motion sensor, or a combination thereof; second logic stored in the memory and executable by the processor to cause the processor to identify the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; third logic stored in the memory and executable by the processor to cause the processor to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive and relational elements; fourth logic stored in the memory and executable by the processor to cause the processor to compile the navigation data elements into a navigation route; and fifth logic stored in the memory and executable by the processor to cause the processor to present at least a portion of the navigation route. | 7. A system comprising: a processor; a memory coupled with the processor; first logic stored in the memory and executable by the processor to cause the processor to receive at least a portion of a conversational narrative descriptive of a route to a destination expressed by a provider, the expressed conversational narrative comprising a plurality of conversational elements, a portion of which includes at least one non-verbal physical movement of a portion of a human body, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements, the first logic being further executable by the processor to cause the processor to receive the portion of the conversational narrative comprising the at least one non-verbal physical movement of a portion of a human body via an optical sensor, a motion sensor, or a combination thereof; second logic stored in the memory and executable by the processor to cause the processor to identify the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; third logic stored in the memory and executable by the processor to cause the processor to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive and relational elements; fourth logic stored in the memory and executable by the processor to cause the processor to compile the navigation data elements into a navigation route; and fifth logic stored in the memory and executable by the processor to cause the processor to present at least a portion of the navigation route. 8. The system of claim 7 wherein the third logic is further executable by the processor to cause the processor to access a navigation database operative to relate one or more navigation oriented conversational elements to one or more navigation data elements. | 0.650943 |
8,762,318 | 1 | 3 | 1. A method comprising: receiving, using at least one processor, an item recommendation request, the request identifying a user; responsive to a determination made using web page interaction data that the user is a frequent user, using item scoring in a model trained using the web page interaction data for a plurality of users, the item scoring identifying a plurality of scored items and the corresponding scores; responsive to a determination made using the web page interaction data that the user is an infrequent user, the at least one processor; identifying, using a current item identified from behavior of the user and the trained model, a probability for each cluster identified in the trained model that the user belongs to the cluster; and generating the plurality of scored items, each item of the plurality of scored items having an item score determined using the item's cluster score and the probability that the user belongs to the cluster; selecting, by the at least one processor, items from the plurality of scored items based on the item scoring; and providing, by the at least one processor, the selected items as item recommendations in response to the request. | 1. A method comprising: receiving, using at least one processor, an item recommendation request, the request identifying a user; responsive to a determination made using web page interaction data that the user is a frequent user, using item scoring in a model trained using the web page interaction data for a plurality of users, the item scoring identifying a plurality of scored items and the corresponding scores; responsive to a determination made using the web page interaction data that the user is an infrequent user, the at least one processor; identifying, using a current item identified from behavior of the user and the trained model, a probability for each cluster identified in the trained model that the user belongs to the cluster; and generating the plurality of scored items, each item of the plurality of scored items having an item score determined using the item's cluster score and the probability that the user belongs to the cluster; selecting, by the at least one processor, items from the plurality of scored items based on the item scoring; and providing, by the at least one processor, the selected items as item recommendations in response to the request. 3. The method of claim 1 , further comprising: generating a short-term cluster membership vector using the current item identified from the behavior of the user and the trained model, the short-term membership vector being used to identify the probability for each cluster identified in the trained model that the user belongs to the cluster. | 0.646694 |
9,170,738 | 14 | 15 | 14. The system of claim 11 , wherein the control circuitry is further configured to apply a set of segment markers to the stored media asset. | 14. The system of claim 11 , wherein the control circuitry is further configured to apply a set of segment markers to the stored media asset. 15. The system of claim 14 , wherein the control circuitry is further configured to generate the set of segment markers based on a content of the stored media asset. | 0.944594 |
9,710,451 | 10 | 11 | 10. A computer program product, comprising a computer-readable hardware storage device having a computer-readable program code stored therein, said program code configured to be executed by a processor of a computer system to implement a method for natural-language processing based on DNA computing, the method comprising: the processor translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. | 10. A computer program product, comprising a computer-readable hardware storage device having a computer-readable program code stored therein, said program code configured to be executed by a processor of a computer system to implement a method for natural-language processing based on DNA computing, the method comprising: the processor translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. 11. The computer program product of claim 10 , wherein an unfilled slot of the ordered set of slots is compatible with the first token if a first grammatical classification associated with the unfilled slot matches a second grammatical classification associated with the first token, and wherein the first grammatical classification and the second grammatical classification each identifies a characteristic selected from a group comprising: a part of speech, a sentence, a clause, a syntactical classification, a semantic classification, and combinations thereof. | 0.520408 |
7,882,100 | 12 | 13 | 12. The method of claim 1 , wherein said generating step includes identifying portions of the left deep nested loop join tree requiring transformation. | 12. The method of claim 1 , wherein said generating step includes identifying portions of the left deep nested loop join tree requiring transformation. 13. The method of claim 12 , wherein said transforming step includes transforming identified portions of the left deep nested loop join tree. | 0.927245 |
9,059,851 | 1 | 10 | 1. A method for generating an encryption dictionary, the method comprises: generating a random value for each plaintext symbol of multiple plaintext symbols; and calculating a random token for each plaintext symbol based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol; wherein the calculating comprises applying a monotonic increasing function; wherein the encryption dictionary comprises a mapping between the multiple plaintext symbols and random token of the multiple plaintext symbols based on a sensitivity level of one or more of the symbols, wherein the random token for each plaintext symbol is based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol. | 1. A method for generating an encryption dictionary, the method comprises: generating a random value for each plaintext symbol of multiple plaintext symbols; and calculating a random token for each plaintext symbol based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol; wherein the calculating comprises applying a monotonic increasing function; wherein the encryption dictionary comprises a mapping between the multiple plaintext symbols and random token of the multiple plaintext symbols based on a sensitivity level of one or more of the symbols, wherein the random token for each plaintext symbol is based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol. 10. The method according to claim 1 , further comprising: receiving a group of plaintext symbols to be encrypted; encrypting by a second computerized entity plaintext symbols of the group of plaintext symbols by using the encryption dictionary to provide a group of random tokens; and providing the group of random tokens to a first computerized entity that differs from the second computerized entity. | 0.700447 |
9,263,046 | 9 | 14 | 9. A method of distributed dictation and transcription performed using at least one processor associated with a dictation manager, the method comprising the steps of: receiving an audio signal from a user operating a client station; identifying a user profile stored in a memory of the dictation manager associated with the user of the received audio signal; determining whether the identified user profile of the user is stored in at least one of a plurality of servers coupled to the dictation manager; if it is determined that the user profile is stored in at least one of the plurality of servers, then selecting the one server having the user profiled stored to transcribe the received audio signal; and causing the received audio signal to be transmitted to the one server wherein the received audio signal is converted into a textual data signal. | 9. A method of distributed dictation and transcription performed using at least one processor associated with a dictation manager, the method comprising the steps of: receiving an audio signal from a user operating a client station; identifying a user profile stored in a memory of the dictation manager associated with the user of the received audio signal; determining whether the identified user profile of the user is stored in at least one of a plurality of servers coupled to the dictation manager; if it is determined that the user profile is stored in at least one of the plurality of servers, then selecting the one server having the user profiled stored to transcribe the received audio signal; and causing the received audio signal to be transmitted to the one server wherein the received audio signal is converted into a textual data signal. 14. The method of claim 9 wherein the step of causing the received audio to be transmitted includes causing the client station to transmit the audio signal to the one server. | 0.871681 |
9,298,263 | 10 | 11 | 10. A system for providing visual feedback, comprising: a processor; and a memory communicatively coupled to the processor when the system is operational, the memory bearing processor-executable instructions that, when executed on the processor, cause the system at least to: identify data representative of a target's motion or position in a physical space; compare the identified data to a plurality of gesture filters, wherein each of said plurality of gesture filters comprises one or more parameters defining a gesture along with associated thresholds and ranges for said one or more parameters; identify a confidence rating output for each of the comparisons to the plurality of gesture filters, wherein each of the plurality of confidence rating outputs indicates a likelihood that the identified data corresponds to a gesture of a respective gesture filter; in response to determining that no confidence rating output is above a threshold level of acceptance, predict an intended gesture based on a comparison of the confidence rating outputs for identified data of failed executions of gestures; determine that a variation between the captured data for a failed execution of a gesture and the filter parameters for the intended gesture is below a threshold level; and provide feedback comprising a visual representation of the target's motion or position and an example of a correct performance of the intended gesture for which the variation is below the threshold level. | 10. A system for providing visual feedback, comprising: a processor; and a memory communicatively coupled to the processor when the system is operational, the memory bearing processor-executable instructions that, when executed on the processor, cause the system at least to: identify data representative of a target's motion or position in a physical space; compare the identified data to a plurality of gesture filters, wherein each of said plurality of gesture filters comprises one or more parameters defining a gesture along with associated thresholds and ranges for said one or more parameters; identify a confidence rating output for each of the comparisons to the plurality of gesture filters, wherein each of the plurality of confidence rating outputs indicates a likelihood that the identified data corresponds to a gesture of a respective gesture filter; in response to determining that no confidence rating output is above a threshold level of acceptance, predict an intended gesture based on a comparison of the confidence rating outputs for identified data of failed executions of gestures; determine that a variation between the captured data for a failed execution of a gesture and the filter parameters for the intended gesture is below a threshold level; and provide feedback comprising a visual representation of the target's motion or position and an example of a correct performance of the intended gesture for which the variation is below the threshold level. 11. The system in accordance with claim 10 , wherein the memory further comprises processor-executable instructions that, when executed on the processor, cause the system at least to: receive feedback representing the example of a correct performance of the intended gesture over a network. | 0.892193 |
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