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5,392,428 | 1 | 27 | 1. A computer-based information analysis system for creating a representation of at least a portion of at least one of first and second predetermined bodies of text, the representation comprising records which correspond to text segments each of which have a length determined by the system user, the system comprising: a) input means for entering data, the input means comprising topic input means for inputting a set of user-defined topics; b) organization means for structuring the representation, the organization means comprising: i) record division means for creating at least one of first and second sets of records, wherein each set of records corresponds to a particular body of text and wherein each record comprises data which characterizes a particular text segment chosen by a system user, the record division means comprising demarcation indicia means for entering demarcation indicia representing the user selected length of each record; ii) one-to-one association organizing means comprising demarcation indicia association means for establishing a one-to-one association between a predetermined record and the corresponding demarcation indicia for indicating the length of the record; and iii) one-to-many association organizing means comprising topic organizing means for establishing a user-designated one-to-many association between at least one user-defined topic and at least one of the records; and c) output means for generating a report. | 1. A computer-based information analysis system for creating a representation of at least a portion of at least one of first and second predetermined bodies of text, the representation comprising records which correspond to text segments each of which have a length determined by the system user, the system comprising: a) input means for entering data, the input means comprising topic input means for inputting a set of user-defined topics; b) organization means for structuring the representation, the organization means comprising: i) record division means for creating at least one of first and second sets of records, wherein each set of records corresponds to a particular body of text and wherein each record comprises data which characterizes a particular text segment chosen by a system user, the record division means comprising demarcation indicia means for entering demarcation indicia representing the user selected length of each record; ii) one-to-one association organizing means comprising demarcation indicia association means for establishing a one-to-one association between a predetermined record and the corresponding demarcation indicia for indicating the length of the record; and iii) one-to-many association organizing means comprising topic organizing means for establishing a user-designated one-to-many association between at least one user-defined topic and at least one of the records; and c) output means for generating a report. 27. The system of claim 1 wherein: (a) the input means further comprises time period input means for inputting a user-defined range of times associated with at least one of the records; and (b) the output means further comprises record retrieval means for retrieving one or more records according to one or more ranges of times associated with at least one record. | 0.817269 |
9,317,594 | 7 | 8 | 7. The method of claim 6 , wherein the data files classified within the upper node are linked together by a thread. | 7. The method of claim 6 , wherein the data files classified within the upper node are linked together by a thread. 8. The method of claim 7 , wherein the thread is defined by email header fields, a common thread field in a database, a common topic on a discussion forum, or a common social media message. | 0.952128 |
9,348,925 | 1 | 6 | 1. A method performed by one or more data processing apparatuses, the method comprising: identifying a general search query that does not include a location phrase, wherein a location phrase is one or more terms that specify a geographic location; determining, for the general search query, a map query rate based on a ratio of a number of times that the general search query was received through an online map interface presenting the geographic location relative to a total number of times that the general search query was received; determining that the general search query is a locally significant query for the geographic location based, at least in part, on the map query rate for the general search query exceeding a threshold value; creating a local search query using the general search query and a location phrase representing the geographic location; requesting a set of general search results responsive to the general search query and a set of local search results responsive to the local search query; selecting, from the set of general search results and the set of local search results, a final set of search results including at least one local search result from the set of local search results and at least one general search result from the set of general search results; and providing data that cause presentation of the final set of search results. | 1. A method performed by one or more data processing apparatuses, the method comprising: identifying a general search query that does not include a location phrase, wherein a location phrase is one or more terms that specify a geographic location; determining, for the general search query, a map query rate based on a ratio of a number of times that the general search query was received through an online map interface presenting the geographic location relative to a total number of times that the general search query was received; determining that the general search query is a locally significant query for the geographic location based, at least in part, on the map query rate for the general search query exceeding a threshold value; creating a local search query using the general search query and a location phrase representing the geographic location; requesting a set of general search results responsive to the general search query and a set of local search results responsive to the local search query; selecting, from the set of general search results and the set of local search results, a final set of search results including at least one local search result from the set of local search results and at least one general search result from the set of general search results; and providing data that cause presentation of the final set of search results. 6. The method of claim 1 , wherein creating a local search query using a general search query and a location phrase representing the geographic location comprises: selecting, from a set of locally significant search queries for the geographic location, a locally significant search query that matches the general search query; and creating a local search query that includes the selected locally significant search query and the location phrase. | 0.744839 |
8,555,250 | 1 | 8 | 1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. | 1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. 8. The method of claim 1 , wherein the correctness analysis identifies unreachable code. | 0.89 |
8,973,128 | 1 | 7 | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, the tagged data tagged from one or more documents, for each of the one or more documents, the tagged data identifying items in the document for which the document may be searched and the tagged data also identifying portions of the document that are eligible for alteration, based on classification of the identified portions; a presentation engine for processing a plurality of search results, the presentation engine configured to: identify a search result from within a previously returned plurality of search results, the previously returned plurality of search results including the one or more documents, the identified search result for a document from among the one or more documents, the search result referencing a tagged portion of the document; determine that a user has access privileges to at least a portion of the document based on an access policy; determine that the user does not have access to the tagged portion of the document based on classification of the tagged portion and based on the access policy; and alter the search result so that that the tagged portion is not presented as part of the search result to the user. | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, the tagged data tagged from one or more documents, for each of the one or more documents, the tagged data identifying items in the document for which the document may be searched and the tagged data also identifying portions of the document that are eligible for alteration, based on classification of the identified portions; a presentation engine for processing a plurality of search results, the presentation engine configured to: identify a search result from within a previously returned plurality of search results, the previously returned plurality of search results including the one or more documents, the identified search result for a document from among the one or more documents, the search result referencing a tagged portion of the document; determine that a user has access privileges to at least a portion of the document based on an access policy; determine that the user does not have access to the tagged portion of the document based on classification of the tagged portion and based on the access policy; and alter the search result so that that the tagged portion is not presented as part of the search result to the user. 7. The system of claim 1 , the presentation engine further configured to: identify the search result from within a second plurality of search results for a second user; determine that the second user has access privileges to at least a portion of the document based on the access policy; determine that the second user does not have access to a second tagged portion of the document based on classification of the second tagged portion and based on the access policy; differently alter the search result so that the second tagged portion is not presented as part of the search result; and transmits the differently altered search result, including the tagged portion of the document, for presentation to the second user. | 0.500693 |
8,719,707 | 7 | 8 | 7. The method of claim 1 , wherein identifying the movie associated with the movie quote comprises: identifying a plurality of movies associated with the movie quote; determining a number of references to the movie quote associated with each of the plurality of movies; and identifying the movie of the plurality of movies associated with the greatest number of references to the movie quote. | 7. The method of claim 1 , wherein identifying the movie associated with the movie quote comprises: identifying a plurality of movies associated with the movie quote; determining a number of references to the movie quote associated with each of the plurality of movies; and identifying the movie of the plurality of movies associated with the greatest number of references to the movie quote. 8. The method of claim 7 , further comprising providing two or more movie trailers in response to the query, based on two or more of the plurality of movies, wherein each of the two or more movie trailers includes the movie quote. | 0.813614 |
8,898,294 | 13 | 22 | 13. One or more non-transitory machine-readable media storing instructions for execution by a device associated with an apparatus to report a state of the apparatus to a remote computer, the instructions for causing the device to perform operations comprising: detecting the state of the apparatus; generating a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and sending the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using eXtensible Markup Language (XML); wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot initiate communication to an address of the device on the internal network; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. | 13. One or more non-transitory machine-readable media storing instructions for execution by a device associated with an apparatus to report a state of the apparatus to a remote computer, the instructions for causing the device to perform operations comprising: detecting the state of the apparatus; generating a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and sending the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using eXtensible Markup Language (XML); wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot initiate communication to an address of the device on the internal network; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. 22. The one or more machine-readable media of claim 13 , wherein the message comprises an error condition history, the error condition history indicating error conditions in the apparatus over time. | 0.732432 |
9,053,152 | 3 | 4 | 3. The computer-implemented method of claim 1 , further comprising, identifying a ranking associated with each identified data artifact. | 3. The computer-implemented method of claim 1 , further comprising, identifying a ranking associated with each identified data artifact. 4. The computer-implemented method of claim 3 , wherein the subset of injected identified artifacts presented on the enterprise workspace page is selected based upon the identified ranking. | 0.92663 |
7,542,820 | 20 | 23 | 20. An article of manufacture comprising a program storage medium having computer readable code embodied therein, said computer readable code being configured to facilitating creation of at least a recipe for processing at least a substrate in at least a processing system, the article of manufacture comprising: computer readable code for creating a recipe editor, said best-known method driven recipe editor incorporating best-known methods (BKMs), said BKMs being practice specifications for said recipe; computer readable code for creating a plurality of BKM modules based on said BKMs for said recipe, wherein each BKM module of said plurality of BKM modules relates to a process stage for processing said substrate and includes a plurality of recipe steps of said recipe; computer readable code for applying rules in defining parameters in said plurality of BKM modules; computer readable code for translating, using said recipe editor, user-propagated parameter values into updated rules, said user-propagated parameter values being propagated by a first user in at least one of said processing system and said plurality of BKM modules; computer readable code for generating at least an updated BKM module using said updated rules; and computer readable code for providing said updated BKM module to at least a second processing system that is used by a second user. | 20. An article of manufacture comprising a program storage medium having computer readable code embodied therein, said computer readable code being configured to facilitating creation of at least a recipe for processing at least a substrate in at least a processing system, the article of manufacture comprising: computer readable code for creating a recipe editor, said best-known method driven recipe editor incorporating best-known methods (BKMs), said BKMs being practice specifications for said recipe; computer readable code for creating a plurality of BKM modules based on said BKMs for said recipe, wherein each BKM module of said plurality of BKM modules relates to a process stage for processing said substrate and includes a plurality of recipe steps of said recipe; computer readable code for applying rules in defining parameters in said plurality of BKM modules; computer readable code for translating, using said recipe editor, user-propagated parameter values into updated rules, said user-propagated parameter values being propagated by a first user in at least one of said processing system and said plurality of BKM modules; computer readable code for generating at least an updated BKM module using said updated rules; and computer readable code for providing said updated BKM module to at least a second processing system that is used by a second user. 23. The article of manufacture of claim 20 wherein said rules define permissible values for said parameters. | 0.672727 |
8,504,561 | 1 | 3 | 1. A method comprising: for each ngram of a plurality of ngrams, determining a click entropy that represents an extent to which a plurality of clicks that occurs with respect to a plurality of search queries that include the ngram is diversified among a plurality of domains based on a proportion of the plurality of clicks that corresponds to each domain of the plurality of domains; comparing the click entropy for each ngram to an entropy threshold to determine a subset of the plurality of ngrams such that the click entropy of each ngram in the subset is less than the entropy threshold; determining that each ngram in the subset is associated with an intent to access a respective designated domain of the plurality of domains, the designated domain for each ngram in the subset corresponding to a relatively greater proportion of the plurality of clicks that occurs with respect to the plurality of search queries that include that ngram than others of the plurality of domains; and increasing a number of search results that correspond to the designated domain for a specified ngram from the subset that are to be provided in response to receipt of a search query that includes the specified ngram to be greater than a specified maximum number, using at least one processor, based on the specified ngram being associated with the intent to access the designated domain for the specified ngram. | 1. A method comprising: for each ngram of a plurality of ngrams, determining a click entropy that represents an extent to which a plurality of clicks that occurs with respect to a plurality of search queries that include the ngram is diversified among a plurality of domains based on a proportion of the plurality of clicks that corresponds to each domain of the plurality of domains; comparing the click entropy for each ngram to an entropy threshold to determine a subset of the plurality of ngrams such that the click entropy of each ngram in the subset is less than the entropy threshold; determining that each ngram in the subset is associated with an intent to access a respective designated domain of the plurality of domains, the designated domain for each ngram in the subset corresponding to a relatively greater proportion of the plurality of clicks that occurs with respect to the plurality of search queries that include that ngram than others of the plurality of domains; and increasing a number of search results that correspond to the designated domain for a specified ngram from the subset that are to be provided in response to receipt of a search query that includes the specified ngram to be greater than a specified maximum number, using at least one processor, based on the specified ngram being associated with the intent to access the designated domain for the specified ngram. 3. The method of claim 1 , wherein increasing the number of the search results that correspond to the designated domain for the specified ngram that are to be provided in response to receipt of the search query comprises: increasing the number of the search results that correspond to the designated domain for the specified ngram that are to be provided in response to receipt of the search query to be a specified number that is selected based on the click entropy for the specified ngram. | 0.638971 |
8,655,111 | 20 | 25 | 20. A computer system for creating photo stories, comprising: a computer memory configured to store photos and metadata associated with the photos; and one or more computer processors configured to analyze the photos, or the metadata, or a combination thereof and to produce an analysis result, wherein the one or more computer processors are configured to automatically selecting a plurality of different groups of photos from the photos stored in the computer memory based on the analysis result, wherein the plurality of different groups of photos comprises a first group of photos and a second group of photos, wherein the one or more computer processors are configured to automatically produce a plurality of photo story templates based on the plurality of different groups of photos, wherein the plurality of photo story templates comprises a first photo story template based on the first group of photos and a second photo story template based on the second group of photos, wherein the one or more computer processors are configured to rank a first photo story formed by the first group of photos in the first photo story template and a second photo story formed by the second group of photos in the second photo story template to create ranking score, and to select one of the first photo story and the second photo story based on the ranking score, wherein the selected one of the first photo story or the second photo story is to be presented to a use. | 20. A computer system for creating photo stories, comprising: a computer memory configured to store photos and metadata associated with the photos; and one or more computer processors configured to analyze the photos, or the metadata, or a combination thereof and to produce an analysis result, wherein the one or more computer processors are configured to automatically selecting a plurality of different groups of photos from the photos stored in the computer memory based on the analysis result, wherein the plurality of different groups of photos comprises a first group of photos and a second group of photos, wherein the one or more computer processors are configured to automatically produce a plurality of photo story templates based on the plurality of different groups of photos, wherein the plurality of photo story templates comprises a first photo story template based on the first group of photos and a second photo story template based on the second group of photos, wherein the one or more computer processors are configured to rank a first photo story formed by the first group of photos in the first photo story template and a second photo story formed by the second group of photos in the second photo story template to create ranking score, and to select one of the first photo story and the second photo story based on the ranking score, wherein the selected one of the first photo story or the second photo story is to be presented to a use. 25. The computer system for creating photo stories of claim 20 , wherein the one or more computer processors are configured to automatically ranking comprises calculating a weighting score for at least one of attributes associated with the first photo story template or the second photo story template. | 0.691837 |
8,775,442 | 5 | 18 | 5. The method of claim 1 , wherein the reference source comprises an online source of articles on a wide range of subjects. | 5. The method of claim 1 , wherein the reference source comprises an online source of articles on a wide range of subjects. 18. The method of claim 5 , wherein the reference source is Wikipedia. | 0.972826 |
9,208,229 | 1 | 12 | 1. A computer-implemented method for corroborating a set of facts included in a fact repository, the method comprising: at a back end computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: identifying a set of facts associated with an object, the set of facts having been previously extracted from multiple documents, each fact comprising an attribute-value pair, including a fact attribute type and a fact value, and wherein the object is associated with an entity having a name fact attribute type; receiving a first document not included in the multiple documents and a reference to the first document, said reference comprising user-viewable anchor text extracted from a second document; determining that the user-viewable anchor text matches the name of the entity associated with the object; determining that one or both of the name of the entity associated with the object or the user-viewable anchor text appears in the first document; and responsive to determining that the user-viewable anchor text matches the name of the entity associated with the object and that one or both of the name of the entity associated with the object or the user-viewable anchor text appears in the first document, corroborating the set of facts using the first document; the corroborating comprising: identifying one or more facts in the first document, each identified fact having an attribute-value pair; and comparing a respective attribute-value pair of the set of facts to an identified attribute-value pair in the first document; and updating the set of facts in accordance with the corroborating, wherein the updating includes one or both of storing an attribute-value pair from the first document in the set of facts in association with the object or adjusting a status of an attribute-value pair of the set of facts. | 1. A computer-implemented method for corroborating a set of facts included in a fact repository, the method comprising: at a back end computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: identifying a set of facts associated with an object, the set of facts having been previously extracted from multiple documents, each fact comprising an attribute-value pair, including a fact attribute type and a fact value, and wherein the object is associated with an entity having a name fact attribute type; receiving a first document not included in the multiple documents and a reference to the first document, said reference comprising user-viewable anchor text extracted from a second document; determining that the user-viewable anchor text matches the name of the entity associated with the object; determining that one or both of the name of the entity associated with the object or the user-viewable anchor text appears in the first document; and responsive to determining that the user-viewable anchor text matches the name of the entity associated with the object and that one or both of the name of the entity associated with the object or the user-viewable anchor text appears in the first document, corroborating the set of facts using the first document; the corroborating comprising: identifying one or more facts in the first document, each identified fact having an attribute-value pair; and comparing a respective attribute-value pair of the set of facts to an identified attribute-value pair in the first document; and updating the set of facts in accordance with the corroborating, wherein the updating includes one or both of storing an attribute-value pair from the first document in the set of facts in association with the object or adjusting a status of an attribute-value pair of the set of facts. 12. The method of claim 1 , wherein the name of the entity associated with the object comprises an object name. | 0.863971 |
9,986,419 | 1 | 2 | 1. An electronic device comprising: one or more processors; memory storing computer-readable instructions, which when executed by the one or more processors, cause the one or more processors to: receive input representing user instruction to provide a reminder in the future, the instruction identifying an entity; and after receiving the input: detect, by a microphone of the electronic device, an audio input; identify, in the detected audio input, a voice corresponding to the entity; and in response to identifying the voice, provide the reminder. | 1. An electronic device comprising: one or more processors; memory storing computer-readable instructions, which when executed by the one or more processors, cause the one or more processors to: receive input representing user instruction to provide a reminder in the future, the instruction identifying an entity; and after receiving the input: detect, by a microphone of the electronic device, an audio input; identify, in the detected audio input, a voice corresponding to the entity; and in response to identifying the voice, provide the reminder. 2. The device of claim 1 , wherein identifying the voice corresponding to the entity is performed using a voiceprint of the entity stored in association with the electronic device. | 0.81289 |
9,262,158 | 11 | 13 | 11. A reverse engineering mockup system, comprising: at least one central processing unit; a gesture component configured to receive a selection of the target application from a plurality of applications currently operating; an introspection manager component configured to capture a plurality of states associated with a plurality of user interface (UI) control hierarchies of a target application; a tracking component configured to monitor a progression between a plurality of screens of the target application, wherein at least a portion of the plurality of screens are intermediate screens accessed during the progression from a first screen to a second screen and wherein the plurality of screens are distinct screens from each other; a navigation component configured to generate links that represent the progression between the plurality of screens; a mockup processing component configured to generate a model representation based on the plurality of states wherein the plurality of states comprises a state for each of the plurality of screens in the progression; and an output component configured to render the model representation in an editable format. | 11. A reverse engineering mockup system, comprising: at least one central processing unit; a gesture component configured to receive a selection of the target application from a plurality of applications currently operating; an introspection manager component configured to capture a plurality of states associated with a plurality of user interface (UI) control hierarchies of a target application; a tracking component configured to monitor a progression between a plurality of screens of the target application, wherein at least a portion of the plurality of screens are intermediate screens accessed during the progression from a first screen to a second screen and wherein the plurality of screens are distinct screens from each other; a navigation component configured to generate links that represent the progression between the plurality of screens; a mockup processing component configured to generate a model representation based on the plurality of states wherein the plurality of states comprises a state for each of the plurality of screens in the progression; and an output component configured to render the model representation in an editable format. 13. The reverse engineering mockup system of claim 11 , further comprising: a converter component configured to convert the model representation into a format compatible with the target application, wherein the output component is further configured to convey the model representation in the format compatible with the target application for use as a mockup. | 0.698145 |
9,753,995 | 1 | 5 | 1. A method comprising, by a computing device: receiving, from a client system of a user, an indication of the user accessing a query field of a currently accessed interface of an online social network at the client device of the user, wherein the query field is in a null state; generating a plurality of structured queries that each comprise one or more unique query tokens referencing one or more unique objects associated with the online social network; calculating a score for each structured query based on one or more user-engagement factors, the score for each structured query representing a probability that the user will engage with the structured query; and sending, to the client system responsive to the indication of the user accessing the query field, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, having respective scores greater than a threshold score, and wherein each suggested query that is displayed is selectable by the user to retrieve search results corresponding to the selected query. | 1. A method comprising, by a computing device: receiving, from a client system of a user, an indication of the user accessing a query field of a currently accessed interface of an online social network at the client device of the user, wherein the query field is in a null state; generating a plurality of structured queries that each comprise one or more unique query tokens referencing one or more unique objects associated with the online social network; calculating a score for each structured query based on one or more user-engagement factors, the score for each structured query representing a probability that the user will engage with the structured query; and sending, to the client system responsive to the indication of the user accessing the query field, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, having respective scores greater than a threshold score, and wherein each suggested query that is displayed is selectable by the user to retrieve search results corresponding to the selected query. 5. The method of claim 1 , wherein calculating the score for each structured query based on the one or more user-engagement factors comprises calculating the score based at least in part on a click-thru rate for the structured query. | 0.732184 |
9,547,673 | 6 | 10 | 6. The method of claim 5 wherein receiving a request for information stored in the first database using a first protocol and transmitting the information received from the first database to the second database using a second protocol comprises: receiving and transmitting an RDF triplet whose subject reflects transactional information. | 6. The method of claim 5 wherein receiving a request for information stored in the first database using a first protocol and transmitting the information received from the first database to the second database using a second protocol comprises: receiving and transmitting an RDF triplet whose subject reflects transactional information. 10. The method of claim 6 wherein receiving a request for information stored in the first database using a first protocol and transmitting the information received from the first database to the second database using a second protocol comprises: receiving and transmitting an RDF triplet representing any of marketing information or an e-commerce or other transaction. | 0.85489 |
7,549,170 | 14 | 15 | 14. The method according to claim 12 , wherein the one or more alphanumeric character received in response to each displayed authentication inkblot is a user-computable hash of a natural language description of the displayed authentication inkblot. | 14. The method according to claim 12 , wherein the one or more alphanumeric character received in response to each displayed authentication inkblot is a user-computable hash of a natural language description of the displayed authentication inkblot. 15. The method according to claim 14 , wherein the user-computable hash of the natural language description of the displayed authentication inkblot results in a constant number of alphanumeric characters independent of the length of the natural language description. | 0.912787 |
9,514,108 | 12 | 17 | 12. A non-transitory computer-readable medium having computer-executable instructions for performing a method for reference note generation comprising: receiving a first user input that identifies a designated insertion point in a destination document; subsequent to receiving the first user input, receiving a second user input that causes an information element to be copied to a transfer buffer from a source application; collecting source reference information associated with the information element, wherein the source reference information includes a source identifier indicative of an origin of the information element; generating a reference note based on the source reference information and a reference note format specification; inserting the information element into the destination document, wherein the information is inserted automatically at the designated insertion point without receiving a further user input from a user interface that is associated with the destination document; and inserting the reference note into the destination document, wherein the reference note is inserted without receiving a user input from a user interface that is associated with the destination document. | 12. A non-transitory computer-readable medium having computer-executable instructions for performing a method for reference note generation comprising: receiving a first user input that identifies a designated insertion point in a destination document; subsequent to receiving the first user input, receiving a second user input that causes an information element to be copied to a transfer buffer from a source application; collecting source reference information associated with the information element, wherein the source reference information includes a source identifier indicative of an origin of the information element; generating a reference note based on the source reference information and a reference note format specification; inserting the information element into the destination document, wherein the information is inserted automatically at the designated insertion point without receiving a further user input from a user interface that is associated with the destination document; and inserting the reference note into the destination document, wherein the reference note is inserted without receiving a user input from a user interface that is associated with the destination document. 17. The non-transitory computer-readable medium of claim 12 , wherein the reference note is inserted into the destination document in a same content field as the information element. | 0.614407 |
7,917,286 | 14 | 16 | 14. A method for performing optical character recognition (OCR) of an image, the image associated with GPS location data identifying an actual location of the image, the method executed by a computer and comprising: storing in a database a plurality of images, each image associated with one or more keywords; querying the database to select at least one image; performing optical character recognition of the selected image to recognize text that may be contained in the image, wherein the optical character recognition of the image is constrained by at least one of the keywords associated with the image in the database; determining if the recognized text contained in the image corresponds to the at least one of the keywords associated with the image; and in response to determining that the recognized text contained in the image corresponds to at least one of the keywords associated with the image, updating a street address to be associated with the GPS location data, the street address being associated with the image. | 14. A method for performing optical character recognition (OCR) of an image, the image associated with GPS location data identifying an actual location of the image, the method executed by a computer and comprising: storing in a database a plurality of images, each image associated with one or more keywords; querying the database to select at least one image; performing optical character recognition of the selected image to recognize text that may be contained in the image, wherein the optical character recognition of the image is constrained by at least one of the keywords associated with the image in the database; determining if the recognized text contained in the image corresponds to the at least one of the keywords associated with the image; and in response to determining that the recognized text contained in the image corresponds to at least one of the keywords associated with the image, updating a street address to be associated with the GPS location data, the street address being associated with the image. 16. The method of claim 14 wherein querying the database identifies a number of textual and non-textual features that is in the image. | 0.93802 |
8,549,467 | 1 | 6 | 1. A computerized method comprising: modeling a software system having pairs of coupled software components to yield a platform-independent model of pairs of respective platform-independent software component models, such that each software component model being a placeholder associated with a respective variable set of concrete platform-specific software components; applying a materialization process to the platform-independent model to yield a platform-specific model by selecting respective concrete platform-specific software components for at least some of the software component models; analyzing using a processor the platform-specific model to identify automatically mismatched pairs of concrete -platform-specific software components; automatically re-modeling the platform-specific model such that each automatically identified mismatched pair becomes coupled together via a configurable glue component model which comprises interface maps usable to eliminate the mismatch; configuring the respective glue component model of each of the mismatched pairs by determining, in response to a feedback from a user, at least: the interface maps, method maps associated with the_determined interface maps, parameter maps associated with the determined methods, and code snippets associated with at least one of the determined interface maps, the determined method maps, and the determined parameter maps; and transforming each configured glue component model into a computer code in the platform-specific language to eliminate the respective mismatch, said glue component model is transformed by assembling all determined code snippets into a single piece of code. | 1. A computerized method comprising: modeling a software system having pairs of coupled software components to yield a platform-independent model of pairs of respective platform-independent software component models, such that each software component model being a placeholder associated with a respective variable set of concrete platform-specific software components; applying a materialization process to the platform-independent model to yield a platform-specific model by selecting respective concrete platform-specific software components for at least some of the software component models; analyzing using a processor the platform-specific model to identify automatically mismatched pairs of concrete -platform-specific software components; automatically re-modeling the platform-specific model such that each automatically identified mismatched pair becomes coupled together via a configurable glue component model which comprises interface maps usable to eliminate the mismatch; configuring the respective glue component model of each of the mismatched pairs by determining, in response to a feedback from a user, at least: the interface maps, method maps associated with the_determined interface maps, parameter maps associated with the determined methods, and code snippets associated with at least one of the determined interface maps, the determined method maps, and the determined parameter maps; and transforming each configured glue component model into a computer code in the platform-specific language to eliminate the respective mismatch, said glue component model is transformed by assembling all determined code snippets into a single piece of code. 6. The computerized method according to claim 1 , wherein the determined code snippets are editable by the user. | 0.918129 |
9,274,646 | 1 | 13 | 1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point. | 1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point. 13. The apparatus of claim 1 , wherein the second text selection point is a text position associated with an end of a word preceding the second word. | 0.905815 |
9,135,344 | 11 | 13 | 11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. | 11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. 13. The system of claim 11 , wherein the click tracker identifies data about the user from a cookie communicated via a click by the user on the encoded URL link. | 0.746855 |
9,646,082 | 2 | 6 | 2. The system of claim 1 , wherein the metadata research module includes a learning machine for processing a set of feature vectors including one or more features from the group consisting of: a feature based on text similarity; a feature based on number of shared legal classification codes; and a feature based on number of shared legal citations. | 2. The system of claim 1 , wherein the metadata research module includes a learning machine for processing a set of feature vectors including one or more features from the group consisting of: a feature based on text similarity; a feature based on number of shared legal classification codes; and a feature based on number of shared legal citations. 6. The system of claim 2 , wherein the feature based on text similarity includes one or more from the group consisting of TFIDFScore, RPWeightedScore, and NumSharedRPDocs. | 0.933463 |
8,788,469 | 1 | 3 | 1. A computer-implemented method, comprising: storing the data of a first version of a design document in a first version table within a memory of a computer associated with a second entity, the first version of the design document being sent from a computer associated with a first entity, the first version of the design document being produced at the computer associated with the first entity before the first version of the design document is sent from the computer associated with the first entity; storing the data of a second version of the design document in a second version table within the memory of the computer associated with the second entity, the second version of the design document being received from the computer associated with the first entity after first version of the design document was received from the computer associated with the first entity; and comparing the data of the second version table with the data of the first version table to detect a change in the data between the first version of the design document and the second version of the design document, if a change in the data is detected, setting the first version table to the second version table; using, at the computer associated with the second entity, a dictionary with correct data for the design document to correct and validate the data of the second version table to produce a corrected and validated internal version table; and storing the corrected and validated internal version table within the memory of the computer associated with the second entity such that the memory of the computer associated with the second entity includes the corrected and validated internal version table and the first version table at a given time. | 1. A computer-implemented method, comprising: storing the data of a first version of a design document in a first version table within a memory of a computer associated with a second entity, the first version of the design document being sent from a computer associated with a first entity, the first version of the design document being produced at the computer associated with the first entity before the first version of the design document is sent from the computer associated with the first entity; storing the data of a second version of the design document in a second version table within the memory of the computer associated with the second entity, the second version of the design document being received from the computer associated with the first entity after first version of the design document was received from the computer associated with the first entity; and comparing the data of the second version table with the data of the first version table to detect a change in the data between the first version of the design document and the second version of the design document, if a change in the data is detected, setting the first version table to the second version table; using, at the computer associated with the second entity, a dictionary with correct data for the design document to correct and validate the data of the second version table to produce a corrected and validated internal version table; and storing the corrected and validated internal version table within the memory of the computer associated with the second entity such that the memory of the computer associated with the second entity includes the corrected and validated internal version table and the first version table at a given time. 3. The method of claim 1 , wherein the first version table and the second version table is a bill of materials listing a plurality of produce parts or an approved manufacturing list listing a plurality of part suppliers. | 0.502262 |
9,251,221 | 29 | 30 | 29. A computer system, comprising: a memory; and one or more processing devices, coupled to the memory, to: access a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; access an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; execute the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generate a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identify, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculate the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 29. A computer system, comprising: a memory; and one or more processing devices, coupled to the memory, to: access a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; access an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; execute the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generate a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identify, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculate the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 30. The computer system of claim 29 , wherein the object-scoring rule variably identifies the object whose score should be adjusted when the triggering condition is met based on a value for a field in one or more particular events that caused the triggering condition to be met, the value for the field derived by applying an extraction rule or regular expression to the portion of machine data in the one or more particular events. | 0.649351 |
8,977,628 | 6 | 8 | 6. A system for assessing an innovation farming level of an entity, said system comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: gather information relating to a capability sphere of the entity, wherein the capability sphere includes one or more categories that correspond to one or more capabilities of the entity and wherein in the information is gathered through interaction with the entity; gather information relating to a behavior sphere of the entity, wherein the behavior sphere includes one or more categories that correspond to one or more behaviors of the entity and wherein the information is gathered through interaction with the entity; gather information relating to an outcome sphere of the entity, wherein the outcome sphere includes one or more outcome metrics associated with the entity and wherein the information is gathered through interaction with the entity; determine one or more strengths and one or more improvement opportunities of the entity based at least in part on the gathered information; generate one or more scores for the capability sphere of the entity, the behavior sphere of the entity, and the outcome sphere of the entity based at least in part on the gathered information; gather trending information reflecting a change in the one or more scores over time; generate a report based on at least one of (i) the one or more strengths, (ii) the one or more improvement opportunities, (iii) the one or more scores, or (iv) the trending information, wherein the report includes an assessed innovation farming level of the entity; and transmit report to the entity. | 6. A system for assessing an innovation farming level of an entity, said system comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: gather information relating to a capability sphere of the entity, wherein the capability sphere includes one or more categories that correspond to one or more capabilities of the entity and wherein in the information is gathered through interaction with the entity; gather information relating to a behavior sphere of the entity, wherein the behavior sphere includes one or more categories that correspond to one or more behaviors of the entity and wherein the information is gathered through interaction with the entity; gather information relating to an outcome sphere of the entity, wherein the outcome sphere includes one or more outcome metrics associated with the entity and wherein the information is gathered through interaction with the entity; determine one or more strengths and one or more improvement opportunities of the entity based at least in part on the gathered information; generate one or more scores for the capability sphere of the entity, the behavior sphere of the entity, and the outcome sphere of the entity based at least in part on the gathered information; gather trending information reflecting a change in the one or more scores over time; generate a report based on at least one of (i) the one or more strengths, (ii) the one or more improvement opportunities, (iii) the one or more scores, or (iv) the trending information, wherein the report includes an assessed innovation farming level of the entity; and transmit report to the entity. 8. The system of claim 6 , wherein the gathered information includes information relating to one or more acts performed by the entity within each of one or more disciplines. | 0.852389 |
10,154,274 | 1 | 17 | 1. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: decode an identifier indicating that all samples within a scope of the bitstream have been coded with a prediction restriction; determine that the scope covers a region of interest within a picture; decode at least a first coding unit preceding said region of interest in decoding order in a parse mode such that syntax elements belonging to said at least first coding unit are parsed, but a sample reconstruction process of said syntax elements is omitted; and decode at least a second coding unit belonging to said region of interest such that syntax elements belonging to said at least second coding unit are parsed and a sample reconstruction process is performed to said syntax elements. | 1. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: decode an identifier indicating that all samples within a scope of the bitstream have been coded with a prediction restriction; determine that the scope covers a region of interest within a picture; decode at least a first coding unit preceding said region of interest in decoding order in a parse mode such that syntax elements belonging to said at least first coding unit are parsed, but a sample reconstruction process of said syntax elements is omitted; and decode at least a second coding unit belonging to said region of interest such that syntax elements belonging to said at least second coding unit are parsed and a sample reconstruction process is performed to said syntax elements. 17. The apparatus according to claim 1 , wherein the full decoding mode involves a modified decoding process when only a region is decoded which is different than the standard compliant decoding. | 0.814286 |
9,262,384 | 1 | 47 | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. 47. The apparatus of claim 1 , wherein the system is operable for addressing a problem of custom programming or manual input by automatically retrieving one or more of the original values from one or more of the original documents and making a transformation. | 0.966451 |
9,894,415 | 21 | 24 | 21. The method of claim 16 wherein the media event data is received by the data manager system from a portable communication device through an application program interface. | 21. The method of claim 16 wherein the media event data is received by the data manager system from a portable communication device through an application program interface. 24. The method of claim 21 wherein the rendered data is presented on a networked media playback device, communication device, network database, web service, or electronic television programming guide. | 0.960784 |
9,747,890 | 1 | 8 | 1. A method of automated evaluation of a transcription quality, the method comprising: obtaining audio data; segmenting the audio data into a plurality of utterances with a voice activity detector operating on a computer processor; transcribing the plurality of utterances into at least one word lattice with a large vocabulary continuous speech recognition system operating on the processor, wherein each of the plurality of utterances is transcribed by the processor into a respective word lattice; applying, by the processor, a minimum Bayes risk decoder to the at least one word lattice to create at least one confusion network representing the at least one word lattice as a plurality sequential word bins and ε-bins, wherein the processor creates a confusion network for each word lattice; and calculating, with the processor, at least one conformity ratio from the least one confusion network, wherein the processor calculates a conformity ratio for each confusion network; calculating, with the processor, a transcription quality score from the at least one conformity ratio; filtering, by the processor, the plurality confusion networks based upon the calculated transcription plurality score of each confusion network; selecting, by the processor, those confusion networks from the plurality of confusion networks having a transcription quality score greater than a predetermined value; and storing, by the processor, the selected confusion networks as a plurality of high quality transcriptions. | 1. A method of automated evaluation of a transcription quality, the method comprising: obtaining audio data; segmenting the audio data into a plurality of utterances with a voice activity detector operating on a computer processor; transcribing the plurality of utterances into at least one word lattice with a large vocabulary continuous speech recognition system operating on the processor, wherein each of the plurality of utterances is transcribed by the processor into a respective word lattice; applying, by the processor, a minimum Bayes risk decoder to the at least one word lattice to create at least one confusion network representing the at least one word lattice as a plurality sequential word bins and ε-bins, wherein the processor creates a confusion network for each word lattice; and calculating, with the processor, at least one conformity ratio from the least one confusion network, wherein the processor calculates a conformity ratio for each confusion network; calculating, with the processor, a transcription quality score from the at least one conformity ratio; filtering, by the processor, the plurality confusion networks based upon the calculated transcription plurality score of each confusion network; selecting, by the processor, those confusion networks from the plurality of confusion networks having a transcription quality score greater than a predetermined value; and storing, by the processor, the selected confusion networks as a plurality of high quality transcriptions. 8. The method of claim 1 , further comprising producing an indication of the of the transcription quality score. | 0.851852 |
9,761,278 | 11 | 13 | 11. A method that generates recommendations of post-capture users to edit digital media content, the method comprising: obtaining contextual parameters of digital media content, the digital media content being associated with a content capture user and/or an end user, the contextual parameters defining one or more temporal attributes and/or spatial attributes associated with capture of the digital media content; receiving editing parameters selected by the content capture user and/or the end user, the editing parameters defining one or more editing attributes of an edited version of the digital media content to be created, the one or more editing attributes including one or more selected moments of interest within the digital media content to include within the edited version of the digital media content, wherein receiving the one or more selected moments of interest includes: obtaining, via a first client computing platform, a portion of the digital media content, the portion of the digital media content having a time duration; effectuate transmission of the portion of the digital media content to the first client computing platform for presentation; and receiving, from the first client computing platform, a selection of one or more moments of interest within the portion of the digital media content, individual moments of interest corresponding to individual points in time within the time duration of the portion of the digital media content; obtaining post-capture user profiles, individual post-capture user profiles including expertise attributes associated with individual post-capture users, the expertise attributes including stated information and feedback information, the stated information being provided by the post-capture users themselves and the feedback information including information provided by one or more of content capture users and/or end users for whom the individual post-capture users have created edited versions of other digital media content; identifying a set of post-capture users as potential matches for creating the edited version of the digital media content based upon the contextual parameters, the editing parameters, and the one or more expertise attributes of the post-capture user profiles; and effectuate presentation of the set of post-capture users to the content capture user and/or the end user for selection by the content capture user and/or the end user of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. | 11. A method that generates recommendations of post-capture users to edit digital media content, the method comprising: obtaining contextual parameters of digital media content, the digital media content being associated with a content capture user and/or an end user, the contextual parameters defining one or more temporal attributes and/or spatial attributes associated with capture of the digital media content; receiving editing parameters selected by the content capture user and/or the end user, the editing parameters defining one or more editing attributes of an edited version of the digital media content to be created, the one or more editing attributes including one or more selected moments of interest within the digital media content to include within the edited version of the digital media content, wherein receiving the one or more selected moments of interest includes: obtaining, via a first client computing platform, a portion of the digital media content, the portion of the digital media content having a time duration; effectuate transmission of the portion of the digital media content to the first client computing platform for presentation; and receiving, from the first client computing platform, a selection of one or more moments of interest within the portion of the digital media content, individual moments of interest corresponding to individual points in time within the time duration of the portion of the digital media content; obtaining post-capture user profiles, individual post-capture user profiles including expertise attributes associated with individual post-capture users, the expertise attributes including stated information and feedback information, the stated information being provided by the post-capture users themselves and the feedback information including information provided by one or more of content capture users and/or end users for whom the individual post-capture users have created edited versions of other digital media content; identifying a set of post-capture users as potential matches for creating the edited version of the digital media content based upon the contextual parameters, the editing parameters, and the one or more expertise attributes of the post-capture user profiles; and effectuate presentation of the set of post-capture users to the content capture user and/or the end user for selection by the content capture user and/or the end user of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. 13. The method of claim 11 , wherein receiving the one or more selected moments of interest includes: receiving, from the first client computing platform, tag information associated with the one or more moments of interest, the tag information including instructions for editing the digital media content. | 0.691296 |
8,160,964 | 5 | 7 | 5. A computer-implemented method for processing information associated with end-user license agreements (“EULAs”), the computer-implemented method comprising: transmitting, over an electronic computer network, a request for material subject to a EULA, wherein the request is associated with a user profile, and wherein the material is for use with an application program; receiving, by a computing device, in response to the request for material subject to the EULA, a markup document including a licensing clause and markup tags that describe the licensing clause; and determining that the markup document includes the markup tags that describe the licensing clause; determining, based at least in part on analysis of the markup tags, that the licensing clause and the user profile meet of one or more conditions defined in one or more licensing administration rules, wherein the license administration rules enumerate the one or more conditions, and wherein the one or more conditions indicate the licensing clause is acceptable. | 5. A computer-implemented method for processing information associated with end-user license agreements (“EULAs”), the computer-implemented method comprising: transmitting, over an electronic computer network, a request for material subject to a EULA, wherein the request is associated with a user profile, and wherein the material is for use with an application program; receiving, by a computing device, in response to the request for material subject to the EULA, a markup document including a licensing clause and markup tags that describe the licensing clause; and determining that the markup document includes the markup tags that describe the licensing clause; determining, based at least in part on analysis of the markup tags, that the licensing clause and the user profile meet of one or more conditions defined in one or more licensing administration rules, wherein the license administration rules enumerate the one or more conditions, and wherein the one or more conditions indicate the licensing clause is acceptable. 7. The method of claim 5 , wherein the markup document also includes key words that identify the licensing clause, and wherein the method further includes analyzing the key words. | 0.730422 |
7,650,272 | 50 | 51 | 50. A computer program product for automatically evaluating Bayesian network models for decision support as set forth in claim 49 , wherein the BN model further includes at least one auxiliary node causally linked between at least one evidence node and at least one conclusion node. | 50. A computer program product for automatically evaluating Bayesian network models for decision support as set forth in claim 49 , wherein the BN model further includes at least one auxiliary node causally linked between at least one evidence node and at least one conclusion node. 51. A computer program product for automatically evaluating Bayesian network models for decision support as set forth in claim 50 , wherein the sampling is performed by a Monte Carlo algorithm. | 0.941657 |
10,069,870 | 10 | 12 | 10. An apparatus comprising: a processor; a memory that stores code executable by the processor to: parse communication data into lingual units, wherein each lingual unit is a phoneme and each phoneme is a perceptually distinct unit of sound; generate a validation nonce from the lingual units; generate at least two transform units for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; select one of the at least two transform units for each lingual unit using a selection rule; generate an encrypted message from the selected transform units; parse the encrypted message into a plurality of transform units; generate two or more decrypted lingual units for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; select one of the two or more decrypted lingual units for each transform unit for the decrypted communication data; determine if the selected decrypted lingual satisfies the validation nonce; in response to the selected decrypted lingual unit not satisfying the validation nonce, determine if an alternate decrypted lingual unit of the two or more decrypted lingual units satisfies the validation nonce, and in response to the alternate decrypted lingual unit satisfying the validation nonce, select the alternate decrypted lingual unit for the decrypted communication data. | 10. An apparatus comprising: a processor; a memory that stores code executable by the processor to: parse communication data into lingual units, wherein each lingual unit is a phoneme and each phoneme is a perceptually distinct unit of sound; generate a validation nonce from the lingual units; generate at least two transform units for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; select one of the at least two transform units for each lingual unit using a selection rule; generate an encrypted message from the selected transform units; parse the encrypted message into a plurality of transform units; generate two or more decrypted lingual units for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; select one of the two or more decrypted lingual units for each transform unit for the decrypted communication data; determine if the selected decrypted lingual satisfies the validation nonce; in response to the selected decrypted lingual unit not satisfying the validation nonce, determine if an alternate decrypted lingual unit of the two or more decrypted lingual units satisfies the validation nonce, and in response to the alternate decrypted lingual unit satisfying the validation nonce, select the alternate decrypted lingual unit for the decrypted communication data. 12. The apparatus of claim 10 , the processor further modifying the lingual message transformation in response to communication data exchanged with a node satisfying a modification policy by identifying a modification phrase in the communication data. | 0.659892 |
9,305,227 | 4 | 6 | 4. A system comprising: at least one processor; and a memory device including instructions that, when executed by the at least one processor, cause the at least one processor to: receive an image at the system; determine an OCR latency of the system; determine an OCR accuracy of the system; send the image to a remote device to perform remote optical character recognition (OCR) on the image; generate mobile OCR data, wherein the mobile OCR data comprises mobile OCR results; receive remote OCR data, wherein the remote OCR data includes remote OCR results from the remote device; determining differences between the mobile OCR data and the remote OCR data; generate hybrid OCR results based at least in part on: the differences, the mobile OCR data, the remote OCR data, and at least one of the OCR latency being less than a threshold amount of time or the OCR accuracy being less than an accuracy threshold; and cause the hybrid OCR results to be displayed. | 4. A system comprising: at least one processor; and a memory device including instructions that, when executed by the at least one processor, cause the at least one processor to: receive an image at the system; determine an OCR latency of the system; determine an OCR accuracy of the system; send the image to a remote device to perform remote optical character recognition (OCR) on the image; generate mobile OCR data, wherein the mobile OCR data comprises mobile OCR results; receive remote OCR data, wherein the remote OCR data includes remote OCR results from the remote device; determining differences between the mobile OCR data and the remote OCR data; generate hybrid OCR results based at least in part on: the differences, the mobile OCR data, the remote OCR data, and at least one of the OCR latency being less than a threshold amount of time or the OCR accuracy being less than an accuracy threshold; and cause the hybrid OCR results to be displayed. 6. The system of claim 4 , wherein merging the mobile OCR data and the remote OCR data comprises: adding a first mobile OCR result associated with a first word from the mobile OCR results to a second remote OCR result associated with a second word from the remote OCR results to create a list of OCR results to be displayed. | 0.874321 |
9,418,203 | 8 | 9 | 8. The method of claim 1 , wherein the annotation of the second set of variants comprises identifying a chromosome on which each variant is located. | 8. The method of claim 1 , wherein the annotation of the second set of variants comprises identifying a chromosome on which each variant is located. 9. The method of claim 8 , further comprising generating annotations for a first set of annotation types for each of the variants in a plurality of parallel processes, the plurality of parallel processes corresponding to the different chromosomes on which the variants are located. | 0.911746 |
7,720,680 | 12 | 22 | 12. An interactive manual system, comprising: a speech engine to receive and process speech from a user, convert the speech into a word sequence, and identify a structure to which the word sequence conforms; a structured manual including information related to an operation of a device; a visual model to relate a visual representation of the information; a dialog management arrangement to interpret the structure in a context and to extract pertinent information and the visual representation from the structured manual and the visual model, wherein the structure is categorized into one of a “how-to” meaning structure category and a “what-is” meaning structure category, each of the meaning structure categories characterizing the structures of its members as being of a single respective underlying meaning structure, different information being deemed pertinent for the extraction depending upon the meaning structure category into which the structure of the word sequence has been categorized; and an output arrangement to output the information and visual representation, wherein the structure manual and the visual model form a model package that includes a grammar package and a grammar table defined using a grammar specification language, wherein the model package further includes an objects file to define device model information that includes a model of at least one device component, wherein the object file is associated with at least one of a surrounding table, a slide table, a how-to table, and a what-is table, wherein the grammar package includes a set of phrases and sentences as grammars for the speech recognition engine to recognize, and the grammar table includes animation clips associated with the specified grammars, and wherein a categorization into the “what-is” meaning structure category causes the dialog arrangement to: determine an object in the “what-is” meaning structure; determine an object identification of the object; search the surrounding table for information of adjacent objects based on the object identification; search the what-is table based on the object identification for a textual description associated with a feature of the object; and display the textual description when the associated feature is displayed. | 12. An interactive manual system, comprising: a speech engine to receive and process speech from a user, convert the speech into a word sequence, and identify a structure to which the word sequence conforms; a structured manual including information related to an operation of a device; a visual model to relate a visual representation of the information; a dialog management arrangement to interpret the structure in a context and to extract pertinent information and the visual representation from the structured manual and the visual model, wherein the structure is categorized into one of a “how-to” meaning structure category and a “what-is” meaning structure category, each of the meaning structure categories characterizing the structures of its members as being of a single respective underlying meaning structure, different information being deemed pertinent for the extraction depending upon the meaning structure category into which the structure of the word sequence has been categorized; and an output arrangement to output the information and visual representation, wherein the structure manual and the visual model form a model package that includes a grammar package and a grammar table defined using a grammar specification language, wherein the model package further includes an objects file to define device model information that includes a model of at least one device component, wherein the object file is associated with at least one of a surrounding table, a slide table, a how-to table, and a what-is table, wherein the grammar package includes a set of phrases and sentences as grammars for the speech recognition engine to recognize, and the grammar table includes animation clips associated with the specified grammars, and wherein a categorization into the “what-is” meaning structure category causes the dialog arrangement to: determine an object in the “what-is” meaning structure; determine an object identification of the object; search the surrounding table for information of adjacent objects based on the object identification; search the what-is table based on the object identification for a textual description associated with a feature of the object; and display the textual description when the associated feature is displayed. 22. The interactive manual system of claim 12 , wherein the speech synthesis arrangement includes a text-to-speech (TTS) application. | 0.847477 |
8,458,164 | 21 | 23 | 21. The computer-implemented method of claim 19 , further comprising the step of confirming selection of the one or more grouped predicates for ungrouping. | 21. The computer-implemented method of claim 19 , further comprising the step of confirming selection of the one or more grouped predicates for ungrouping. 23. The computer-implemented method of claim 21 , wherein the confirming step comprises one or more of the group comprising: selecting a confirmation button displayed in a second display area, entering a mouse click, entering a keystroke, and the equivalent of any of the foregoing. | 0.900494 |
8,661,065 | 13 | 20 | 13. A system, comprising: one or more processors; one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. | 13. A system, comprising: one or more processors; one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. 20. The system of claim 13 , wherein the data storage system further facilitates associating problems in the data with defined terms used within the data storage system. | 0.688192 |
7,565,630 | 35 | 36 | 35. The system of claim 34 , wherein the degree of influence is received from an operator of the third party website. | 35. The system of claim 34 , wherein the degree of influence is received from an operator of the third party website. 36. The system of claim 35 , wherein the degree of influence is determined by the site operator using a slider type graphical control along a graphical axis, wherein the position of the slider is scaled to the weight. | 0.940319 |
8,312,376 | 12 | 14 | 12. A content distributor, comprising: a storage media configured to: maintain bookmarks when initiated at media devices as bookmark save events that are associated with video streams of media content that are rendered by the media devices: maintain bookmark representations that correspond to the bookmarks; and maintain user profiles of users to track user requests for media content; a bookmark interpretation service configured to: receive a bookmark save event from a media device to create a bookmark; interpret the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content from which the bookmark save event is initiated and based on the user requests from a user that are tracked in a user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; and provide one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. | 12. A content distributor, comprising: a storage media configured to: maintain bookmarks when initiated at media devices as bookmark save events that are associated with video streams of media content that are rendered by the media devices: maintain bookmark representations that correspond to the bookmarks; and maintain user profiles of users to track user requests for media content; a bookmark interpretation service configured to: receive a bookmark save event from a media device to create a bookmark; interpret the bookmark to determine one or more bookmark representations based on a context interpretation of the bookmark with respect to the media content from which the bookmark save event is initiated and based on the user requests from a user that are tracked in a user profile for different types of the media content, the one or more bookmark representations derived from metadata that accompanies the media content; and provide one or more of the bookmark representations that correspond to the bookmark when a request for the bookmark is received. 14. A content distributor as recited in claim 12 , wherein the bookmark interpretation service is further configured to initiate a recording of the media content from which the bookmark save event is initiated, and wherein a bookmark representation corresponds to an on-demand recording of the media content. | 0.628916 |
9,817,620 | 1 | 3 | 1. A method for rendering a page description language (PDL) document, the method comprising: receiving a plurality of display lists, each display list comprising a plurality of display list objects; determining a repeated sequence of a predetermined number of consecutive display list objects across the display lists; determining a reusable sequence of display list objects, for the repeated sequence, by extending the repeated sequence to further consecutive display list objects, each occurrence of the reusable sequence being associated with a z-order position in a corresponding display list; subdividing at least one display list, at the z-order position of the reusable sequence in said display list, into a plurality of z-bands including a reusable z-band for the determined reusable sequence; generating a reusable intermediate graphical representation for the determined reusable sequence and a further intermediate graphical representation for at least one other z-band; merging said further intermediate graphical representation with the reusable intermediate graphical representation in accordance with an order of said z-bands; and rendering the page description language (PDL) document using the merged representations. | 1. A method for rendering a page description language (PDL) document, the method comprising: receiving a plurality of display lists, each display list comprising a plurality of display list objects; determining a repeated sequence of a predetermined number of consecutive display list objects across the display lists; determining a reusable sequence of display list objects, for the repeated sequence, by extending the repeated sequence to further consecutive display list objects, each occurrence of the reusable sequence being associated with a z-order position in a corresponding display list; subdividing at least one display list, at the z-order position of the reusable sequence in said display list, into a plurality of z-bands including a reusable z-band for the determined reusable sequence; generating a reusable intermediate graphical representation for the determined reusable sequence and a further intermediate graphical representation for at least one other z-band; merging said further intermediate graphical representation with the reusable intermediate graphical representation in accordance with an order of said z-bands; and rendering the page description language (PDL) document using the merged representations. 3. The method according to claim 1 , further comprising: determining a second reusable sequence of display list objects by extending the repeated sequence of display list objects to a further plurality of consecutive display list objects of a further display list, the second reusable sequence being longer than the previously detected reusable sequence; generating a second reusable intermediate graphical representation for the identified second reusable sequence by merging an intermediate representation for the further plurality of consecutive display list objects with the previously generated reusable intermediate graphical representation. | 0.500772 |
9,053,423 | 1 | 3 | 1. A method for proposing candidate solutions for updating a knowledge base, comprising: for each of a set of knowledge base solutions, each knowledge base solution comprising a sequence of main steps, expressed in a natural language, to be performed on a class of device, processing the knowledge base solution to generate a first action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; receiving a recorded solution, expressed in a natural language, comprising actions performed on a device in the device class; processing the recorded solution to generate a second action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; with a processor, comparing the second action sequence with each of the first action sequences to determine whether the recorded solution corresponds to one of the knowledge base solutions; and based on the comparison, providing for proposing an update to the knowledge base, based on the recorded solution. | 1. A method for proposing candidate solutions for updating a knowledge base, comprising: for each of a set of knowledge base solutions, each knowledge base solution comprising a sequence of main steps, expressed in a natural language, to be performed on a class of device, processing the knowledge base solution to generate a first action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; receiving a recorded solution, expressed in a natural language, comprising actions performed on a device in the device class; processing the recorded solution to generate a second action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; with a processor, comparing the second action sequence with each of the first action sequences to determine whether the recorded solution corresponds to one of the knowledge base solutions; and based on the comparison, providing for proposing an update to the knowledge base, based on the recorded solution. 3. The method of claim 1 , wherein the processing of at least one of the knowledge base solution and the recorded solution to generate an action sequence comprises: extracting syntactic dependencies that involve an imperative verb and a head noun; building an atomic step from the imperative verb and an object, the object comprising the head noun and any other nouns that are in a syntactic dependency with the head noun, and optionally any context. | 0.501109 |
8,316,353 | 9 | 11 | 9. A computer program product, comprising a computer readable storage medium having a computer readable program code stored therein, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method of analyzing a problem in a computing environment, said method comprising: generating, by a computing system, a plurality of symptom rules in a symptom catalog that includes a plurality of sets of information (problem information) about a plurality of problems, wherein said plurality of symptom rules includes a plurality of sets of keywords, wherein said symptom catalog associates said sets of keywords to said sets of problem information in a one-to-one correspondence, and wherein said generating said plurality of symptom rules includes: receiving a document that includes a plurality of tagged keywords included in a prior stack trace, wherein said plurality of tagged keywords indicate said problem; identifying a range of lines in said document, wherein said range of lines indicates said prior stack trace; identifying said plurality of tagged keywords in a set of contiguous lines within said range of lines; extracting said plurality of tagged keywords from said set of contiguous lines; in response to said extracting, converting said plurality of tagged keywords into a plurality of expressions that facilitate said matching; and subsequent to said converting, storing said plurality of expressions in a symptom rule of said plurality of symptom rules residing in a computer data storage device; receiving, by said computing system, an input file that includes a stack trace provided in response to a detection of said problem; identifying, by said computing system, a set of function names included in a plurality of contiguous lines in said stack trace; searching, by said computing system, said symptom catalog for said set of function names; matching, by said computing system and in response to said searching, said set of function names to a set of keywords of said plurality of sets of keywords; retrieving, by said computing system, a set of problem information of said plurality of sets of problem information, wherein said set of problem information corresponds to said set of keywords and includes a solution to said problem; and generating, by said computing system, a report that includes said stack trace and said solution, wherein said report displays said set of function names included in said stack trace in a text having at least one attribute that emphasizes said text. | 9. A computer program product, comprising a computer readable storage medium having a computer readable program code stored therein, said computer readable program code containing instructions configured to be executed by a processor of a computer system to implement a method of analyzing a problem in a computing environment, said method comprising: generating, by a computing system, a plurality of symptom rules in a symptom catalog that includes a plurality of sets of information (problem information) about a plurality of problems, wherein said plurality of symptom rules includes a plurality of sets of keywords, wherein said symptom catalog associates said sets of keywords to said sets of problem information in a one-to-one correspondence, and wherein said generating said plurality of symptom rules includes: receiving a document that includes a plurality of tagged keywords included in a prior stack trace, wherein said plurality of tagged keywords indicate said problem; identifying a range of lines in said document, wherein said range of lines indicates said prior stack trace; identifying said plurality of tagged keywords in a set of contiguous lines within said range of lines; extracting said plurality of tagged keywords from said set of contiguous lines; in response to said extracting, converting said plurality of tagged keywords into a plurality of expressions that facilitate said matching; and subsequent to said converting, storing said plurality of expressions in a symptom rule of said plurality of symptom rules residing in a computer data storage device; receiving, by said computing system, an input file that includes a stack trace provided in response to a detection of said problem; identifying, by said computing system, a set of function names included in a plurality of contiguous lines in said stack trace; searching, by said computing system, said symptom catalog for said set of function names; matching, by said computing system and in response to said searching, said set of function names to a set of keywords of said plurality of sets of keywords; retrieving, by said computing system, a set of problem information of said plurality of sets of problem information, wherein said set of problem information corresponds to said set of keywords and includes a solution to said problem; and generating, by said computing system, a report that includes said stack trace and said solution, wherein said report displays said set of function names included in said stack trace in a text having at least one attribute that emphasizes said text. 11. The program product of claim 9 , wherein each tagged keyword of said plurality of tagged keywords includes a tag indicating a bold typeface. | 0.941176 |
10,073,838 | 7 | 8 | 7. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a semantic rule verifying system to perform acts of: receiving, by a semantic rule verifying system, a semantic rule associated with the semantic data as input, wherein the semantic rule verifying system comprises a processor, a memory, a natural language interpretation module, and a visual user interface; determining, by the semantic rule verifying system, a natural language interpretation corresponding to the input semantic rule based on a predetermined semantic rule structure, wherein the predetermined semantic rule structure for each semantic rule comprises: one or more unique variable name information, one or more nodes corresponding to antecedent and consequent clauses of the semantic rule, node information associated with the one or more nodes, and edge information associated with one or more edges representing the relationship between the one or more nodes; receiving, by a visual user interface of the semantic rule verifying system, a plurality of user actions to modify the natural language interpretation, wherein the plurality of user actions further comprises receiving modifications on one or more sub-clauses of the natural language interpretation performed by the user; identifying one or more edges corresponding to the one or more modified sub-clauses of the natural language interpretation and deriving one or more input edge identification information of the one or more identified edges; mapping the edge identification information stored in the predetermined semantic rule structure with the derived edge identification information associated with the one or more identified edges; modifying the edge information associated with the one or more identified edges and updating the predetermined semantic rule structure based on the mapping and the modification of the one or more modified sub-clauses; generating, by the semantic rule verifying system, a modified natural language interpretation and a modified semantic rule based on the plurality of user actions and the updated predetermined semantic rule structure; executing, by a processor, the modified semantic rule on semantic the data; and displaying, by the visual user interface, one ore more results of the execution. | 7. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a semantic rule verifying system to perform acts of: receiving, by a semantic rule verifying system, a semantic rule associated with the semantic data as input, wherein the semantic rule verifying system comprises a processor, a memory, a natural language interpretation module, and a visual user interface; determining, by the semantic rule verifying system, a natural language interpretation corresponding to the input semantic rule based on a predetermined semantic rule structure, wherein the predetermined semantic rule structure for each semantic rule comprises: one or more unique variable name information, one or more nodes corresponding to antecedent and consequent clauses of the semantic rule, node information associated with the one or more nodes, and edge information associated with one or more edges representing the relationship between the one or more nodes; receiving, by a visual user interface of the semantic rule verifying system, a plurality of user actions to modify the natural language interpretation, wherein the plurality of user actions further comprises receiving modifications on one or more sub-clauses of the natural language interpretation performed by the user; identifying one or more edges corresponding to the one or more modified sub-clauses of the natural language interpretation and deriving one or more input edge identification information of the one or more identified edges; mapping the edge identification information stored in the predetermined semantic rule structure with the derived edge identification information associated with the one or more identified edges; modifying the edge information associated with the one or more identified edges and updating the predetermined semantic rule structure based on the mapping and the modification of the one or more modified sub-clauses; generating, by the semantic rule verifying system, a modified natural language interpretation and a modified semantic rule based on the plurality of user actions and the updated predetermined semantic rule structure; executing, by a processor, the modified semantic rule on semantic the data; and displaying, by the visual user interface, one ore more results of the execution. 8. The medium as claimed in claim 7 , wherein the instructions, on execution, cause the at least one processor to determine the natural language interpretation of the input semantic rule by the steps of: deriving the list of one or more unique variable names, one or more nodes representing entity of the input semantic rule and one or more edges representing the relationship between the nodes; obtaining a plurality of labels from the semantic data repository for each of the derived unique variable name, one or more nodes and one or more edges of the input semantic rule; and appending the plurality of labels to determine the natural language interpretation of the input semantic rule. | 0.500724 |
9,026,540 | 1 | 9 | 1. A system, comprising a processor; and a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions, comprising: a communication component that receives unstructured metadata included in a probe media item, wherein the unstructured metadata comprises a free-form text description of the media item; a matching component that matches the unstructured metadata to structured metadata comprising a structured text description of a reference media item in a reference database based upon a matching function value; and a scoring component that determines a confidence score for the reference media item based upon a scoring function comprised of a first product of the matching function value and a first sum of one and a reference weight, the first product divided by a second sum of a normalized unstructured function value for the probe media item and a second product of the reference weight and a normalized structured function value of the reference media item. | 1. A system, comprising a processor; and a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions, comprising: a communication component that receives unstructured metadata included in a probe media item, wherein the unstructured metadata comprises a free-form text description of the media item; a matching component that matches the unstructured metadata to structured metadata comprising a structured text description of a reference media item in a reference database based upon a matching function value; and a scoring component that determines a confidence score for the reference media item based upon a scoring function comprised of a first product of the matching function value and a first sum of one and a reference weight, the first product divided by a second sum of a normalized unstructured function value for the probe media item and a second product of the reference weight and a normalized structured function value of the reference media item. 9. The system of claim 1 , further comprising a filtering component that selectively filters the reference media item based upon the confidence score. | 0.746622 |
8,856,156 | 1 | 5 | 1. A non-transitory Computer-readable media having computer-executable instructions embodied thereon that when executed provide a method for facilitating decision support by determining nomenclature linkages between variables in databases that have different ontologies, the method comprising: identifying a first set of documents from a first record system having a first ontology; identifying a second set of documents from a second record system having a second ontology that is different than the first ontology; determining a use-case present in the first and second sets of documents; determining a set of variables relevant to the use-case; receiving from the first set of documents, a first document containing at least one first-document variable from the set of variables; wherein each first-document variable has a first-document value associated with it; receiving from the second set of documents, a second document containing at least one second-document variable from the set of variables; (1) wherein the second-document variable has a second-document value associated with it, and (2) wherein the second-document variable is also contained in the first document; based on the determined use-case and set of variables, generating a decision-tree classifier; for each first-document variable contained in the first document, applying the decision tree classifier to transform the first-document value associated with the first-document variable to a categorical datatype; for each second-document variable contained in the second document, applying the decision tree classifier to transform the second-document value associated with the second-document variable to a categorical datatype; based on the categorical datatypes of the first document and the categorical datatypes of the second document, generating a set of textmatrices; applying latent semantic analysis to the set of textmatrices to determine a latent semantic space associated with the at least one first-document variable and the at least one second document variable; specifying a threshold of similarity; for a first comparison-variable, from the at least one first-document variables associated with the latent semantic space: determining a measure of similarity to a second-comparison variable from the at least one second-document variables associated with the latent semantic space: performing a comparison of the measure similarity to the threshold; and based on the comparison, determining that the measure similarity satisfies the threshold, associating the first comparison variable with the second comparison variable, and designating the association as a synonymy, wherein the threshold is satisfied if the measure of similarity is greater than the threshold. | 1. A non-transitory Computer-readable media having computer-executable instructions embodied thereon that when executed provide a method for facilitating decision support by determining nomenclature linkages between variables in databases that have different ontologies, the method comprising: identifying a first set of documents from a first record system having a first ontology; identifying a second set of documents from a second record system having a second ontology that is different than the first ontology; determining a use-case present in the first and second sets of documents; determining a set of variables relevant to the use-case; receiving from the first set of documents, a first document containing at least one first-document variable from the set of variables; wherein each first-document variable has a first-document value associated with it; receiving from the second set of documents, a second document containing at least one second-document variable from the set of variables; (1) wherein the second-document variable has a second-document value associated with it, and (2) wherein the second-document variable is also contained in the first document; based on the determined use-case and set of variables, generating a decision-tree classifier; for each first-document variable contained in the first document, applying the decision tree classifier to transform the first-document value associated with the first-document variable to a categorical datatype; for each second-document variable contained in the second document, applying the decision tree classifier to transform the second-document value associated with the second-document variable to a categorical datatype; based on the categorical datatypes of the first document and the categorical datatypes of the second document, generating a set of textmatrices; applying latent semantic analysis to the set of textmatrices to determine a latent semantic space associated with the at least one first-document variable and the at least one second document variable; specifying a threshold of similarity; for a first comparison-variable, from the at least one first-document variables associated with the latent semantic space: determining a measure of similarity to a second-comparison variable from the at least one second-document variables associated with the latent semantic space: performing a comparison of the measure similarity to the threshold; and based on the comparison, determining that the measure similarity satisfies the threshold, associating the first comparison variable with the second comparison variable, and designating the association as a synonymy, wherein the threshold is satisfied if the measure of similarity is greater than the threshold. 5. The computer-readable media of claim 1 , wherein the measure of similarity is determined using Pearson's correlation coefficient. | 0.721519 |
8,688,673 | 2 | 55 | 2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. | 2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. 55. The method according to claim 2 , wherein the annotations are restricted to annotations that have taken place in a predetermined time interval. | 0.971108 |
10,146,755 | 8 | 11 | 8. A computer program product for assisting users to generate the desired meme in a document, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a document to be evaluated for one or more types of memes for one or more designated primary objects within said document; receiving a type of meme for each of said one or more designated primary objects, wherein each of said one or more designated primary objects is evaluated in accordance with said received type of meme; scanning said document to identify terms providing one or more of positive and negative memes within said document, wherein said identified terms comprise one or more of the following: parts of speech, images, numerical text and numbers; assigning a score for each identified term that provides one or more of positive and negative memes within said document; assigning a score for each of said one or more designated primary objects based on said score assigned for said each identified term; and providing one or more options to modify said document to provide said received type of meme for each of said one or more designated primary objects using said score assigned for each of said one or more designated primary objects. | 8. A computer program product for assisting users to generate the desired meme in a document, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a document to be evaluated for one or more types of memes for one or more designated primary objects within said document; receiving a type of meme for each of said one or more designated primary objects, wherein each of said one or more designated primary objects is evaluated in accordance with said received type of meme; scanning said document to identify terms providing one or more of positive and negative memes within said document, wherein said identified terms comprise one or more of the following: parts of speech, images, numerical text and numbers; assigning a score for each identified term that provides one or more of positive and negative memes within said document; assigning a score for each of said one or more designated primary objects based on said score assigned for said each identified term; and providing one or more options to modify said document to provide said received type of meme for each of said one or more designated primary objects using said score assigned for each of said one or more designated primary objects. 11. The computer program product as recited in claim 8 , wherein the program code further comprises the programming instructions for: assigning said score for each of said one or more designated primary objects based on closeness in location of said each identified term with respect to each of said one or more designated primary objects in said document. | 0.501401 |
8,943,129 | 1 | 3 | 1. A computerized method comprising: generating an identifier of a document, the identifier of the document being a hash value generated as a function of the document; receiving a designation of a collaboration server, the collaboration server to synchronize an action across multiple instances of the document during a collaboration session, each document instance stored locally by a collaboration session participant; adding the identifier of the document and an identifier of the designated collaboration server within data of the document; storing the document, including the identifier of the document and the identifier of the designated collaboration server added within the data of the document, to a local data storage device of a computer performing the computerized method, the identifier of the document and the identifier of the designated collaboration server providing information to a collaboration session participant to connect to a collaboration session based on the document. | 1. A computerized method comprising: generating an identifier of a document, the identifier of the document being a hash value generated as a function of the document; receiving a designation of a collaboration server, the collaboration server to synchronize an action across multiple instances of the document during a collaboration session, each document instance stored locally by a collaboration session participant; adding the identifier of the document and an identifier of the designated collaboration server within data of the document; storing the document, including the identifier of the document and the identifier of the designated collaboration server added within the data of the document, to a local data storage device of a computer performing the computerized method, the identifier of the document and the identifier of the designated collaboration server providing information to a collaboration session participant to connect to a collaboration session based on the document. 3. The computerized method of claim 1 , wherein the document is a document created within a web-based, collaboration enabled document authoring application. | 0.842742 |
7,542,979 | 14 | 15 | 14. A computer system as in claim 12 wherein the attributes in the attribute tab that are mandatory for the selected business object are distinguished from attributes that are not mandatory. | 14. A computer system as in claim 12 wherein the attributes in the attribute tab that are mandatory for the selected business object are distinguished from attributes that are not mandatory. 15. A computer system as in claim 14 wherein the mandatory attributes are distinguished by color. | 0.976295 |
8,447,773 | 8 | 9 | 8. The apparatus of claim 1 , wherein the query statement is configured as a structured query language (SQL) statement. | 8. The apparatus of claim 1 , wherein the query statement is configured as a structured query language (SQL) statement. 9. The apparatus of claim 8 , wherein the SQL statement further comprises a work flow print command. | 0.958368 |
7,856,594 | 1 | 5 | 1. A related text comparison system stored in a non-transitory computer readable medium, comprising: a first collection of data including a plurality of first text pages, each of the first text pages including a plurality of words, each of the first text pages being characterized as one of a directory page and a content page, each of the directory page including a reference to one or more of the first text pages, a first directory page being selected from the first collection as a base directory, the based directory having a first reference to a first content page being selected from the base directory as a base page, the first reference including a category name for the base directory; a second collection of data including a plurality of second text pages, each of the second text pages including a plurality of words, each of the second text pages being characterized as one of a second directory page and a content page, each of the second directory page including a reference to one or more of the second text pages; and a related page specifying unit for receiving the category name of the base page and parsing the second collection of data to specify one of the second directory page by matching the category name to the specified directory as a compare directory, the compare directory referencing one or more content pages from the second collection of data as compare pages, wherein the compare pages are determined to be related to the base page, wherein further comprising: a word information unit for parsing the base page and the compare pages to determine a degree of comparison between the base page and each of the compare pages, wherein the word information unit produces a topic structure TS={t 1 . . . t i . . . t n } consisting of a set of topics t i for each of the base page and the compare pages, each t i including a set of subject words s i and a set of content words C i , wherein a word (t) from a given text page tf(t) can be considered as a subject word s i from the set of subject words based on an objective measure, the objective measure being a product of frequency of appearance of the word (t) in the given text page tf(t) and a weighting factor weight(t) according to part of speech of the word (t), and the word (t) being considered a subject word s i when the product exceeds a threshold value α, the product being expressed as:
tf ( t )×weight( t )>α. | 1. A related text comparison system stored in a non-transitory computer readable medium, comprising: a first collection of data including a plurality of first text pages, each of the first text pages including a plurality of words, each of the first text pages being characterized as one of a directory page and a content page, each of the directory page including a reference to one or more of the first text pages, a first directory page being selected from the first collection as a base directory, the based directory having a first reference to a first content page being selected from the base directory as a base page, the first reference including a category name for the base directory; a second collection of data including a plurality of second text pages, each of the second text pages including a plurality of words, each of the second text pages being characterized as one of a second directory page and a content page, each of the second directory page including a reference to one or more of the second text pages; and a related page specifying unit for receiving the category name of the base page and parsing the second collection of data to specify one of the second directory page by matching the category name to the specified directory as a compare directory, the compare directory referencing one or more content pages from the second collection of data as compare pages, wherein the compare pages are determined to be related to the base page, wherein further comprising: a word information unit for parsing the base page and the compare pages to determine a degree of comparison between the base page and each of the compare pages, wherein the word information unit produces a topic structure TS={t 1 . . . t i . . . t n } consisting of a set of topics t i for each of the base page and the compare pages, each t i including a set of subject words s i and a set of content words C i , wherein a word (t) from a given text page tf(t) can be considered as a subject word s i from the set of subject words based on an objective measure, the objective measure being a product of frequency of appearance of the word (t) in the given text page tf(t) and a weighting factor weight(t) according to part of speech of the word (t), and the word (t) being considered a subject word s i when the product exceeds a threshold value α, the product being expressed as:
tf ( t )×weight( t )>α. 5. The system of claim 1 , wherein the first and second text pages are browser readable pages associated with a global communication network site. | 0.825359 |
8,331,656 | 12 | 17 | 12. A system, comprising: one or more computer configured to: obtain a trainable recognition system using the one or more computers; obtain, by or to the one or more computers, a first item to be recognized comprising one or more units to be recognized; obtain, using the one or more computers, a plurality of hypotheses for class labels of said one or more units; create, using the one or more computers, a plurality of trained model variants for said trainable recognition system by training said recognition system based at least in part on said first item to be recognized, and labeling each of the trained model variants respectively with the class labels based at least in part on a different one of the hypotheses in said plurality of hypotheses for the class of labels of said one or more units; obtain, by or to the one or more computers, a set of practice data with labels; perform recognition, using the one or more computers, of said practice data respectively using each of said plurality of trained model variants to obtain recognition results; measure performance, using the one or more computers, of each of said trained model variants based at least in part on the recognition results obtained for the set of practice data and the labels for the practice data; determine, using the one or more computers, one of said trained model variants with a best measured performance; and select, using the one or more computers, as the class labels for said first item to be recognized the class labels of said one or more units associated with the one trained model variant determined to have the best measured performance, thereby using the hypothesis that among the plurality of hypotheses has a best measured performance. | 12. A system, comprising: one or more computer configured to: obtain a trainable recognition system using the one or more computers; obtain, by or to the one or more computers, a first item to be recognized comprising one or more units to be recognized; obtain, using the one or more computers, a plurality of hypotheses for class labels of said one or more units; create, using the one or more computers, a plurality of trained model variants for said trainable recognition system by training said recognition system based at least in part on said first item to be recognized, and labeling each of the trained model variants respectively with the class labels based at least in part on a different one of the hypotheses in said plurality of hypotheses for the class of labels of said one or more units; obtain, by or to the one or more computers, a set of practice data with labels; perform recognition, using the one or more computers, of said practice data respectively using each of said plurality of trained model variants to obtain recognition results; measure performance, using the one or more computers, of each of said trained model variants based at least in part on the recognition results obtained for the set of practice data and the labels for the practice data; determine, using the one or more computers, one of said trained model variants with a best measured performance; and select, using the one or more computers, as the class labels for said first item to be recognized the class labels of said one or more units associated with the one trained model variant determined to have the best measured performance, thereby using the hypothesis that among the plurality of hypotheses has a best measured performance. 17. The pattern recognition system as in claim 12 , wherein said obtained practice data has been read from a known script. | 0.897133 |
10,083,362 | 8 | 14 | 8. A method for synthesizing and outputting synthesized Arabic handwritten text, comprising: accessing, with circuitry, character shape images of Arabic characters of the Arabic alphabet; determining, with the circuitry, a connection point location between two or more character shapes based on a calculated right edge position and a calculated left edge position of the character shape images; extracting, with the circuitry, character features that indicate Arabic language attributes and width attributes of characters of the character shape images, the Arabic language attributes including character Kashida attributes; identifying, with the circuitry, Kashida extensions as part of the character Kashida attributes; isolating, with the circuitry, the identified Kashida extensions from pepper noise components based on a predetermined ground-truth label, by constraining the extracted character features to be two consecutive characters; extracting, with the circuitry, the identified Kashida extensions based on the predetermined ground-truth label; and generating, with the circuitry, images of Arabic cursive text based on the character Kashida attributes and the width attributes. | 8. A method for synthesizing and outputting synthesized Arabic handwritten text, comprising: accessing, with circuitry, character shape images of Arabic characters of the Arabic alphabet; determining, with the circuitry, a connection point location between two or more character shapes based on a calculated right edge position and a calculated left edge position of the character shape images; extracting, with the circuitry, character features that indicate Arabic language attributes and width attributes of characters of the character shape images, the Arabic language attributes including character Kashida attributes; identifying, with the circuitry, Kashida extensions as part of the character Kashida attributes; isolating, with the circuitry, the identified Kashida extensions from pepper noise components based on a predetermined ground-truth label, by constraining the extracted character features to be two consecutive characters; extracting, with the circuitry, the identified Kashida extensions based on the predetermined ground-truth label; and generating, with the circuitry, images of Arabic cursive text based on the character Kashida attributes and the width attributes. 14. The method of claim 8 , further comprising: filtering out attributes relating to a thickness of a left edge segment and a thickness of a right edge segment of the extracted Kashida. | 0.502688 |
8,943,184 | 1 | 3 | 1. A method of managing network devices in a network, the method comprising: receiving a trigger for an operation command to be executed by a network device; connecting to the network device; supplying to the network device a command line interface command for execution of the operation command, a randomly generated string being included at the end of the command line interface command; receiving the output of the operation command from the network device; detecting an end of the operation command output based on the randomly generated string; and parsing the operation command output generated by the device using an XML based parser. | 1. A method of managing network devices in a network, the method comprising: receiving a trigger for an operation command to be executed by a network device; connecting to the network device; supplying to the network device a command line interface command for execution of the operation command, a randomly generated string being included at the end of the command line interface command; receiving the output of the operation command from the network device; detecting an end of the operation command output based on the randomly generated string; and parsing the operation command output generated by the device using an XML based parser. 3. The method of claim 1 , and further comprising configuring the XML based parser to parse different operation command outputs with XML files using anchors and regular expressions irrespective of whether the operation command output is free style or in tabular form. | 0.852649 |
8,792,715 | 1 | 4 | 1. A method for classifying forms, said method comprising: receiving by at least one processor an image representing a form of an unknown document type, the image including line-art; receiving by the at least one processor a plurality of template models corresponding to a plurality of different document types; selecting by the at least one processor a subset of the plurality of template models as candidate template models, the candidate template models including line-art junctions best matching line-art junctions of the received image; and, selecting by the at least one processor one of the candidate template models as a best candidate template model, the best candidate template model including horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model. | 1. A method for classifying forms, said method comprising: receiving by at least one processor an image representing a form of an unknown document type, the image including line-art; receiving by the at least one processor a plurality of template models corresponding to a plurality of different document types; selecting by the at least one processor a subset of the plurality of template models as candidate template models, the candidate template models including line-art junctions best matching line-art junctions of the received image; and, selecting by the at least one processor one of the candidate template models as a best candidate template model, the best candidate template model including horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model. 4. The method according to claim 1 , wherein the selecting the one of the candidate template models includes: extracting horizontal and vertical lines from the received image; for each of the candidate template models: aligning the extracted horizontal and vertical lines to horizontal and vertical lines of the candidate template model, respectively; determining a forward match score indicating a match quality of the aligned horizontal and vertical lines to the horizontal and vertical lines of the candidate template model, respectively; and, determining a backward match score indicating a match quality of the horizontal and vertical lines of the candidate template model to the aligned horizontal and vertical lines, respectively; and, determining the best candidate template model based on the forward and backward match scores. | 0.548596 |
9,058,331 | 8 | 9 | 8. A system comprising: one or more processors; a visual search engine stored on a memory and executable by the one or more processors, the visual search engine for receiving an image from a user device, searching the database of mixed media objects to identify and retrieve a mixed media object in which the image occurs, and identifying a cluster including the mixed media object in which the image occurs; and a social network application that is coupled to the visual search engine, the social network application for receiving, from the visual search engine, a reference to the cluster, determining whether a conversation associated with the cluster exists in a social network, and responsive to an absence of the conversation, generating the conversation associated with the cluster in the social network. | 8. A system comprising: one or more processors; a visual search engine stored on a memory and executable by the one or more processors, the visual search engine for receiving an image from a user device, searching the database of mixed media objects to identify and retrieve a mixed media object in which the image occurs, and identifying a cluster including the mixed media object in which the image occurs; and a social network application that is coupled to the visual search engine, the social network application for receiving, from the visual search engine, a reference to the cluster, determining whether a conversation associated with the cluster exists in a social network, and responsive to an absence of the conversation, generating the conversation associated with the cluster in the social network. 9. The system of claim 8 , wherein the mixed media object corresponds to a source material and the conversation includes a plurality of discussions that relate to the source material. | 0.77182 |
8,423,899 | 10 | 13 | 10. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a request to input a character into a text field; at least partly in response to the receiving of the request, causing display of the character within the text field; receiving an instruction to mask a subsequent character requested to be input into the text field; receiving a request to input a subsequent character into the text field; and at least partly in response to the receiving of the request to input the subsequent character, masking the subsequent character within the text field. | 10. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a request to input a character into a text field; at least partly in response to the receiving of the request, causing display of the character within the text field; receiving an instruction to mask a subsequent character requested to be input into the text field; receiving a request to input a subsequent character into the text field; and at least partly in response to the receiving of the request to input the subsequent character, masking the subsequent character within the text field. 13. One or more computer-readable media recited in claim 10 , wherein the receiving of the instruction to mask a subsequent character comprises receiving a request to input a predefined string of characters into the text field. | 0.924983 |
8,533,224 | 7 | 9 | 7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system. | 7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system. 9. The system of claim 7 , wherein assigning a richness score to the particular data sample comprises determining the richness score based on how many data samples have similar input data but different output data than the particular data sample and based on how many data samples have similar input data and similar or different output data than the particular data sample. | 0.683051 |
7,809,562 | 10 | 11 | 10. A non-transitory computer-readable storage medium having a program recorded thereon for executing a procedure with a computer, said procedure comprising: inputting a voice information of a user; performing primary voice recognition of the voice information based on a recognition dictionary storing voice information to produce a primary voice recognition result of the input voice information; judging whether to accept or reject the primary voice recognition result; sending the input voice information of the user to additional voice recognition means for performing secondary voice recognition when the primary voice recognition result is rejected; receiving a secondary voice recognition result produced by the additional voice recognition means; outputting the primary voice recognition result or the secondary voice recognition result to an exterior of a voice recognition system; inputting settlement information on the primary voice recognition result or the secondary voice recognition result outputted to the exterior of the voice recognition system; updating the recognition dictionary based on the inputted settlement information by the use of a word history list which includes an order of use of each word and a frequency of use of each word, and deleting, from the recognition dictionary, a word based on at least one of the oldest word and the smallest word of the frequency included in the word history list when an amount of the words in said recognition dictionary exceeds a processing capability of said voice recognition system. | 10. A non-transitory computer-readable storage medium having a program recorded thereon for executing a procedure with a computer, said procedure comprising: inputting a voice information of a user; performing primary voice recognition of the voice information based on a recognition dictionary storing voice information to produce a primary voice recognition result of the input voice information; judging whether to accept or reject the primary voice recognition result; sending the input voice information of the user to additional voice recognition means for performing secondary voice recognition when the primary voice recognition result is rejected; receiving a secondary voice recognition result produced by the additional voice recognition means; outputting the primary voice recognition result or the secondary voice recognition result to an exterior of a voice recognition system; inputting settlement information on the primary voice recognition result or the secondary voice recognition result outputted to the exterior of the voice recognition system; updating the recognition dictionary based on the inputted settlement information by the use of a word history list which includes an order of use of each word and a frequency of use of each word, and deleting, from the recognition dictionary, a word based on at least one of the oldest word and the smallest word of the frequency included in the word history list when an amount of the words in said recognition dictionary exceeds a processing capability of said voice recognition system. 11. The non-transitory computer-readable storage medium claimed in claim 10 , wherein the judging step comprises the steps of: presenting the primary voice recognition result to an external decision system; and receiving a decision result to accept or reject the primary voice recognition result from the external decision system. | 0.818282 |
9,104,750 | 8 | 14 | 8. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a first term, a second term, and a third term; determining that a phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of a meaning of the first term, a meaning of the second term, and a meaning of the third term; in response to determining that the phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of the meaning of the first term, the meaning of the second term, and the meaning of the third term: identifying, in a collection of search queries, an original search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, original search query term that is not included in the phrase; determining a number of times that, in the collection of search queries, the original query that includes (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term that is not included in the phrase, is followed by a revised search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, revised search query term that is different than the additional term and that is not included in the phrase; and determining, based on the number of times, whether to revise a subsequently received search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term, to include the additional, revised search query term. | 8. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a first term, a second term, and a third term; determining that a phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of a meaning of the first term, a meaning of the second term, and a meaning of the third term; in response to determining that the phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of the meaning of the first term, the meaning of the second term, and the meaning of the third term: identifying, in a collection of search queries, an original search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, original search query term that is not included in the phrase; determining a number of times that, in the collection of search queries, the original query that includes (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term that is not included in the phrase, is followed by a revised search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, revised search query term that is different than the additional term and that is not included in the phrase; and determining, based on the number of times, whether to revise a subsequently received search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term, to include the additional, revised search query term. 14. The non-transitory computer-readable storage medium of claim 8 , wherein determining the collective meaning of the phrase that includes the first term, the second term, and the third term comprises: determining whether the collective meaning of the phrase that includes the first term, the second term, and the third term matches a stored concept. | 0.715559 |
7,792,858 | 1 | 2 | 1. A computer-implemented method comprising: receiving a list of keywords via a data network interface for processing by a processor of a computer system; ordering the list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events; partitioning the list into at least two sets, a head partition including keywords with an activity level above a predefined threshold, a tail partition including the remainder of the keywords in the list; modeling the keywords in the head partition based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords in the head partition, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword; scoring the keywords in the head partition based on the modeling; and clustering head partition keywords with tail partition keywords having at least one common variable into at least one keyword cluster. | 1. A computer-implemented method comprising: receiving a list of keywords via a data network interface for processing by a processor of a computer system; ordering the list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events; partitioning the list into at least two sets, a head partition including keywords with an activity level above a predefined threshold, a tail partition including the remainder of the keywords in the list; modeling the keywords in the head partition based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords in the head partition, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword; scoring the keywords in the head partition based on the modeling; and clustering head partition keywords with tail partition keywords having at least one common variable into at least one keyword cluster. 2. The method as claimed in claim 1 wherein the set of variables include seasonality variables. | 0.82852 |
9,448,652 | 11 | 12 | 11. A method for controlling an application based on a handwriting input in a first terminal, the method comprising: receiving a message from a second terminal while displaying an application screen on a touch screen display of the first terminal; displaying a notification indicating the message receipt on the touch screen display of the first terminal while displaying a portion of the application screen; if the notification is displayed on the touch screen display, activating a handwriting recognition module to recognize a handwriting input in an area of the touch screen display associated with the displayed notification receiving the handwriting input on the touch screen display of the first terminal without launching a message application; determining a symbol corresponding to the handwriting input; associating the symbol with a function of the message application; and transmitting the associated symbol to the second terminal through the message application. | 11. A method for controlling an application based on a handwriting input in a first terminal, the method comprising: receiving a message from a second terminal while displaying an application screen on a touch screen display of the first terminal; displaying a notification indicating the message receipt on the touch screen display of the first terminal while displaying a portion of the application screen; if the notification is displayed on the touch screen display, activating a handwriting recognition module to recognize a handwriting input in an area of the touch screen display associated with the displayed notification receiving the handwriting input on the touch screen display of the first terminal without launching a message application; determining a symbol corresponding to the handwriting input; associating the symbol with a function of the message application; and transmitting the associated symbol to the second terminal through the message application. 12. The method of claim 11 , further comprising: transmitting a reply message to the second terminal, the reply message comprising a text corresponding to the symbol. | 0.800481 |
8,386,450 | 4 | 7 | 4. The method of claim 3 , wherein the statistics are used to improve a combined selectivity estimate of one or more predicates of the query. | 4. The method of claim 3 , wherein the statistics are used to improve a combined selectivity estimate of one or more predicates of the query. 7. The method of claim 4 , wherein zero or more predicates of the query are applied by one of the pre-defined queries and wherein the remaining predicates are eligible to be applied on the pre-defined query. | 0.869153 |
8,799,351 | 26 | 27 | 26. The non-transitory computer readable storage medium of claim 19 , wherein the electronic file conforms to a public or private format for sharing information. | 26. The non-transitory computer readable storage medium of claim 19 , wherein the electronic file conforms to a public or private format for sharing information. 27. The non-transitory computer readable storage medium of claim 26 , wherein the format is portable document format (PDF). | 0.95348 |
8,949,280 | 15 | 16 | 15. A non-transitory computer readable storage medium comprising instructions, that when executed by a processor, cause the processor to: receive, from a user device via a database query interface, a selection of a logical field of a data abstraction model of a database; query a discovery registry associated with the data abstraction model of the database to discover three or more web services that are resolvable based on the selected logical field, wherein a web service output of each discovered web service is associated with the selected logical field; modify the database query interface based on the three or more discovered web services; display the modified database query interface, wherein the modified database query interface includes at least three or more input elements associated with the of three or more discovered web services and a text entry element; display a form input interface in response to a selection of a wizard button wherein the form input interface includes input fields associated with the three or more discovered web services and a control that executes the three or more discovered web services; and execute, in response to selection of the control, the three or more discovered web services based on search terms received via the input fields associated with the three or more discovered web services. | 15. A non-transitory computer readable storage medium comprising instructions, that when executed by a processor, cause the processor to: receive, from a user device via a database query interface, a selection of a logical field of a data abstraction model of a database; query a discovery registry associated with the data abstraction model of the database to discover three or more web services that are resolvable based on the selected logical field, wherein a web service output of each discovered web service is associated with the selected logical field; modify the database query interface based on the three or more discovered web services; display the modified database query interface, wherein the modified database query interface includes at least three or more input elements associated with the of three or more discovered web services and a text entry element; display a form input interface in response to a selection of a wizard button wherein the form input interface includes input fields associated with the three or more discovered web services and a control that executes the three or more discovered web services; and execute, in response to selection of the control, the three or more discovered web services based on search terms received via the input fields associated with the three or more discovered web services. 16. The non-transitory computer readable storage medium of claim 15 , further comprising instructions, that when executed by the processor, cause the processor to display one or more help inputs associated with the three or more discovered web services, wherein each help input provides information associated with a particular discovered web service. | 0.773256 |
8,762,934 | 17 | 18 | 17. The method of claim 16 , wherein generating the plurality of presentation objects further comprises building a plurality of properties for each presentation object, the plurality of properties based on parameters of the plurality of business object model structures that are either part of input/output structures of business object operations or part of standalone structures defined in the business object model, wherein each of the plurality of structures is configured to be a part of the current presentation object. | 17. The method of claim 16 , wherein generating the plurality of presentation objects further comprises building a plurality of properties for each presentation object, the plurality of properties based on parameters of the plurality of business object model structures that are either part of input/output structures of business object operations or part of standalone structures defined in the business object model, wherein each of the plurality of structures is configured to be a part of the current presentation object. 18. The method of claim 17 , wherein parameters that have the same name result in a generation of a single presentation object property as long as their types are the same; otherwise an error is reported. | 0.918595 |
10,162,811 | 10 | 13 | 10. A computer-implemented system for identifying a language in a message, comprising: one or more computer processors programmed to implement a sanitizer module, a grouper module, and a language detector module, wherein the sanitizer module obtains a text message generated by a user and removes non-language characters from the text message to generate a sanitized text message, wherein the grouper module detects an alphabet and a script present in the sanitized text message, and wherein (i) detecting the alphabet comprises performing an alphabet-based language detection test to determine a first set of scores, and wherein each score in the first set of scores represents a likelihood that the sanitized text message comprises the alphabet for one of a plurality of different languages, and (ii) detecting the script comprises performing a script-based language detection test to determine a second set of scores, and wherein each score in the second set of scores represents a likelihood that the sanitized text message comprises the script for one of the plurality of different languages, and wherein the language detector module is operable to perform operations comprising: providing one or more combinations of the first and second sets of scores as input to one or more classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of language detection tests and the second classifier was trained using outputs from a second combination of language detection tests; obtaining as output from at least one of the one or more classifiers a respective confidence score that the sanitized text message is in one of a plurality of different languages; and identifying the language in the sanitized text message based on the confidence score from at least one of the one or more classifiers. | 10. A computer-implemented system for identifying a language in a message, comprising: one or more computer processors programmed to implement a sanitizer module, a grouper module, and a language detector module, wherein the sanitizer module obtains a text message generated by a user and removes non-language characters from the text message to generate a sanitized text message, wherein the grouper module detects an alphabet and a script present in the sanitized text message, and wherein (i) detecting the alphabet comprises performing an alphabet-based language detection test to determine a first set of scores, and wherein each score in the first set of scores represents a likelihood that the sanitized text message comprises the alphabet for one of a plurality of different languages, and (ii) detecting the script comprises performing a script-based language detection test to determine a second set of scores, and wherein each score in the second set of scores represents a likelihood that the sanitized text message comprises the script for one of the plurality of different languages, and wherein the language detector module is operable to perform operations comprising: providing one or more combinations of the first and second sets of scores as input to one or more classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of language detection tests and the second classifier was trained using outputs from a second combination of language detection tests; obtaining as output from at least one of the one or more classifiers a respective confidence score that the sanitized text message is in one of a plurality of different languages; and identifying the language in the sanitized text message based on the confidence score from at least one of the one or more classifiers. 13. The system of claim 10 , wherein the grouper module is operable to perform operations comprising: selecting the language detector module from a plurality of language detector modules based on at least one of the first set of scores, the second set of scores, and a combination of the first and second sets of scores. | 0.612591 |
7,530,020 | 1 | 5 | 1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object. | 1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object. 5. The method according to claim 1 , wherein the set of objects is produced by an Internet search engine. | 0.816434 |
8,621,629 | 17 | 18 | 17. A non-transitory computer-readable media comprising routines which are executed on a processor for detecting and defeating an unauthorized intrusion within a computer network of an infrastructure element of a high value target, the non-transitory computer-readable media configured for: receiving data from the computer network of the infrastructure element of a high value target; filtering the received data; applying grammars produced with a grammar based compression and learning algorithm to the filtered data; expanding a sampling of the filtered data, after the grammars have been applied, with polymorphic transformation; analyzing the expanded sampled data to determine the unauthorized intrusion; and recommending whether the unauthorized intrusion has occurred based on the analyzed data. | 17. A non-transitory computer-readable media comprising routines which are executed on a processor for detecting and defeating an unauthorized intrusion within a computer network of an infrastructure element of a high value target, the non-transitory computer-readable media configured for: receiving data from the computer network of the infrastructure element of a high value target; filtering the received data; applying grammars produced with a grammar based compression and learning algorithm to the filtered data; expanding a sampling of the filtered data, after the grammars have been applied, with polymorphic transformation; analyzing the expanded sampled data to determine the unauthorized intrusion; and recommending whether the unauthorized intrusion has occurred based on the analyzed data. 18. The non-transitory computer-readable media according to claim 17 , further configured for: expanding the sampled filtered data using an application of distance metrics, hierarchical processing and ranking, and/or fuzzy models; and estimating Kolmogorov complexity which forms compressive grammar based on Minimum Description Length principles as part of the grammar based compression and learning algorithm. | 0.639474 |
8,280,823 | 224 | 226 | 224. The computer program product of claim 220 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for at least one of said at least one job requirement, the required skill or experience-related phrase or at least one implying phrase of the required skill or experience-related phrase, and wherein the term of experience for the required skill or experience-related phrase or said at least one implying phrase of the required skill or experience-related phrase is greater than or equal to the required term of experience. | 224. The computer program product of claim 220 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for at least one of said at least one job requirement, the required skill or experience-related phrase or at least one implying phrase of the required skill or experience-related phrase, and wherein the term of experience for the required skill or experience-related phrase or said at least one implying phrase of the required skill or experience-related phrase is greater than or equal to the required term of experience. 226. The computer program product of claim 224 , wherein the required term of experience is rounded up to a unit of time. | 0.964558 |
8,004,539 | 1 | 23 | 1. A method, comprising: receiving, by a graphical editing tool of a computer, a command associated with a graphical editing operation directed to performing a transformation to a graphical object, wherein the transformation is associated with changing a value of a first parameter of the graphical object; displaying, by the graphical editing tool, a transformation object associated with the transformation, wherein the transformation object comprises a second parameter comprising a value associated with the transformation, and wherein the value of the first parameter of the graphical object is related to the value of the second parameter; receiving, by the graphical editing tool, an indication to convert the transformation object into a new parameter of the graphical object; converting, by the graphical editing tool, the transformation object into the new parameter of the graphical object; retaining, by the graphical editing tool, the converted transformation object during operations on other objects; and determining a function that defines the value of the first parameter based upon the value of the second parameter; wherein the new parameter comprises a derived parameter formed from expressions and/or functions that relate the derived parameter to one or more other parameters of the graphical object. | 1. A method, comprising: receiving, by a graphical editing tool of a computer, a command associated with a graphical editing operation directed to performing a transformation to a graphical object, wherein the transformation is associated with changing a value of a first parameter of the graphical object; displaying, by the graphical editing tool, a transformation object associated with the transformation, wherein the transformation object comprises a second parameter comprising a value associated with the transformation, and wherein the value of the first parameter of the graphical object is related to the value of the second parameter; receiving, by the graphical editing tool, an indication to convert the transformation object into a new parameter of the graphical object; converting, by the graphical editing tool, the transformation object into the new parameter of the graphical object; retaining, by the graphical editing tool, the converted transformation object during operations on other objects; and determining a function that defines the value of the first parameter based upon the value of the second parameter; wherein the new parameter comprises a derived parameter formed from expressions and/or functions that relate the derived parameter to one or more other parameters of the graphical object. 23. The method of claim 1 , further comprising: changing the transformation object in appearance to indicate that the transformation object has been converted into the new parameter of the graphical object. | 0.909171 |
7,945,553 | 2 | 3 | 2. The method of claim 1 , wherein correlating the received search argument to the particular advertisement includes the second search engine selecting the particular advertisement based on the received search argument and user profile data. | 2. The method of claim 1 , wherein correlating the received search argument to the particular advertisement includes the second search engine selecting the particular advertisement based on the received search argument and user profile data. 3. The method of claim 2 , wherein the user profile data includes selections of the user from previous search results. | 0.929678 |
8,117,037 | 20 | 27 | 20. Computer readable apparatus comprising a storage medium, said storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a digitized speech input relating to an organization or entity which a user wishes to locate; based at least in part on the input, identify a location associated with the organization or entity; and provide a graphical or visual representation of the location in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity. | 20. Computer readable apparatus comprising a storage medium, said storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a digitized speech input relating to an organization or entity which a user wishes to locate; based at least in part on the input, identify a location associated with the organization or entity; and provide a graphical or visual representation of the location in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity. 27. The apparatus of claim 20 , wherein the digitized speech is received via a microphone disposed in a transport apparatus. | 0.940327 |
8,024,715 | 18 | 20 | 18. A computer system including a processor and a memory for storing a just-in-time (JIT) compiler unit implemented on the processor, comprising: a binary code translator unit to translate binary code to an intermediate language code; an instruction identifier unit to identify an instruction of interest; a reliability instruction generation unit to insert reliability instructions in the intermediate language code to validate values; and an intermediate code translator unit to translate the intermediate language code to binary code. | 18. A computer system including a processor and a memory for storing a just-in-time (JIT) compiler unit implemented on the processor, comprising: a binary code translator unit to translate binary code to an intermediate language code; an instruction identifier unit to identify an instruction of interest; a reliability instruction generation unit to insert reliability instructions in the intermediate language code to validate values; and an intermediate code translator unit to translate the intermediate language code to binary code. 20. The JIT compiler unit of claim 18 , further comprising a JIT compiler manager to direct the reliable code unit to insert reliability instructions in the intermediate language code at locations specified by a user. | 0.502294 |
8,694,540 | 2 | 3 | 2. The computer-implemented method of claim 1 , further comprising: applying at least one of the identified predictive models to the database table to obtain one or more predicted values; and adding the one or more predicted values to the database table. | 2. The computer-implemented method of claim 1 , further comprising: applying at least one of the identified predictive models to the database table to obtain one or more predicted values; and adding the one or more predicted values to the database table. 3. The computer-implemented method of claim 2 , wherein adding the one or more predicted values to the database table comprises replacing a missing column value in the database table. | 0.953904 |
9,208,149 | 11 | 12 | 11. A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising: translating an original sentence which is a character string of a first language into a forward-translated sentence which is a character string of a second language; acquiring, by translating an original word in the original sentence corresponding to a first forward-translated word in the forward-translated sentence, at least one second forward-translated word different from the first forward-translated word, to obtain candidate words including the first forward-translated word and the at least one second forward-translated word; calculating a fluency for each of the candidate words, the fluency indicating naturalness of the forward-translated sentence if each of the candidate words is replaced with the first forward-translated word; obtaining at least one reverse-translated word for each of the candidate words by reverse-translating each candidate word into the first language; calculating a semantic similarity between the original word and each reverse-translated word; and selecting a corrected forward-translated word to be replaced with the first forward-translated word from among the candidate words based on the semantic similarity and fluency. | 11. A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising: translating an original sentence which is a character string of a first language into a forward-translated sentence which is a character string of a second language; acquiring, by translating an original word in the original sentence corresponding to a first forward-translated word in the forward-translated sentence, at least one second forward-translated word different from the first forward-translated word, to obtain candidate words including the first forward-translated word and the at least one second forward-translated word; calculating a fluency for each of the candidate words, the fluency indicating naturalness of the forward-translated sentence if each of the candidate words is replaced with the first forward-translated word; obtaining at least one reverse-translated word for each of the candidate words by reverse-translating each candidate word into the first language; calculating a semantic similarity between the original word and each reverse-translated word; and selecting a corrected forward-translated word to be replaced with the first forward-translated word from among the candidate words based on the semantic similarity and fluency. 12. The medium according to claim 11 , wherein the acquiring the at least one second forward-translated word adds, a word of the second language having the fluency not less than a threshold when being replaced with the first forward-translated word, as a new candidate word. | 0.588589 |
9,122,740 | 7 | 9 | 7. A product data management (PDM) data processing system comprising a processor and accessible memory, the data processing system particularly configured to: receive traversal parameters including a plurality of unique object identifiers (UIDs) corresponding to objects in a data structure; receive input objects, including input runtime objects, and closure rule clauses; configure runtime objects, from the objects in the data structure, according to the traversal parameters; store the runtime objects in a temporary table; construct database queries corresponding to the closure rule clauses; execute the database queries on the data structure and the temporary table; traverse the data structure and the temporary table using the closure rules to produce traversed objects; and serialize and store the traversed objects. | 7. A product data management (PDM) data processing system comprising a processor and accessible memory, the data processing system particularly configured to: receive traversal parameters including a plurality of unique object identifiers (UIDs) corresponding to objects in a data structure; receive input objects, including input runtime objects, and closure rule clauses; configure runtime objects, from the objects in the data structure, according to the traversal parameters; store the runtime objects in a temporary table; construct database queries corresponding to the closure rule clauses; execute the database queries on the data structure and the temporary table; traverse the data structure and the temporary table using the closure rules to produce traversed objects; and serialize and store the traversed objects. 9. The PDM data processing system of claim 7 , wherein the data structure is a bill of materials (BOM) structure, and the runtime objects are BOMLines. | 0.587432 |
7,987,174 | 5 | 7 | 5. A computer-implemented method of providing video content comprising: using an Internet communication interface, soliciting a user to submit information regarding a video file, wherein the information comprises a location of the video file and a description of the video file; receiving at least a portion of the information from submitted by the user in response to the solicitation; generating a file comprising the received information; providing the file for display, wherein displaying the file comprises displaying at least a portion of the video file; wherein providing the file for display comprises providing the video file as a stream of packets; and generating an identifier of the video file using the user-submitted information about the video file and saving the identifier in a storage device. | 5. A computer-implemented method of providing video content comprising: using an Internet communication interface, soliciting a user to submit information regarding a video file, wherein the information comprises a location of the video file and a description of the video file; receiving at least a portion of the information from submitted by the user in response to the solicitation; generating a file comprising the received information; providing the file for display, wherein displaying the file comprises displaying at least a portion of the video file; wherein providing the file for display comprises providing the video file as a stream of packets; and generating an identifier of the video file using the user-submitted information about the video file and saving the identifier in a storage device. 7. The method of claim 5 , wherein displaying the file further comprises displaying information about an item, wherein the item is at least one of a product, service, and website that is associated with the video file. | 0.756696 |
9,037,472 | 5 | 6 | 5. The method of claim 1 wherein determining the goal transaction of the user includes determining pending action items requiring user input. | 5. The method of claim 1 wherein determining the goal transaction of the user includes determining pending action items requiring user input. 6. The method of claim 5 wherein the pending action items include at least one of the following: payment of a bill, address change, and service modification. | 0.960051 |
7,752,193 | 26 | 27 | 26. A system for processing a search query for a query word, the system comprising: at least one storage device storing a word table storing a plurality of normalized words associated with a file, and a word record for each normalized word stored in the word table, each word record including a flag for indicating whether one or more variations exist in the file for the normalized word; a processor; and a memory operably coupled to the processor and storing program instructions therein, the processor being operable to execute the program instructions, the program instructions including: receiving an input query word; normalizing the input query word; searching the word table for the normalized input query word; and retrieving from the word table information on the word record for the normalized word matching the normalized input query word, wherein the one or more variations indicated in the retrieved word record are considered for a match against the query word responsive to a command to consider the one or more variations, wherein in response to a command to consider diacritic symbols, information on a diacritic symbol corresponding to the matched normalized word is retrieved from a first data store and compared against information of a diacritic symbol in the input query word for determining a match, wherein the information on the diacritic symbol stored in the first data structure includes a numeric value indicative of a position of the diacritic symbol in the word prior to normalizing, and a representation of the diacritic symbol, the diacritic symbol being a mark added to a character. | 26. A system for processing a search query for a query word, the system comprising: at least one storage device storing a word table storing a plurality of normalized words associated with a file, and a word record for each normalized word stored in the word table, each word record including a flag for indicating whether one or more variations exist in the file for the normalized word; a processor; and a memory operably coupled to the processor and storing program instructions therein, the processor being operable to execute the program instructions, the program instructions including: receiving an input query word; normalizing the input query word; searching the word table for the normalized input query word; and retrieving from the word table information on the word record for the normalized word matching the normalized input query word, wherein the one or more variations indicated in the retrieved word record are considered for a match against the query word responsive to a command to consider the one or more variations, wherein in response to a command to consider diacritic symbols, information on a diacritic symbol corresponding to the matched normalized word is retrieved from a first data store and compared against information of a diacritic symbol in the input query word for determining a match, wherein the information on the diacritic symbol stored in the first data structure includes a numeric value indicative of a position of the diacritic symbol in the word prior to normalizing, and a representation of the diacritic symbol, the diacritic symbol being a mark added to a character. 27. The system of claim 26 , wherein the normalizing the query word includes stripping the word of a diacritic symbol. | 0.844737 |
7,649,877 | 7 | 11 | 7. A method comprising: receiving, at a server, an input from a mobile device, the input comprising a text message and one or more destination addresses; converting the text message into a voice message; transmitting the voice message along with an acknowledge message from the server to the one or more destination addresses, wherein the acknowledge message permits a destination device to accept delivery of the voice message or to decline delivery of the voice message; receiving, at the server, a reply voice message from the destination device in response to the destination device accepting delivery of the voice message; and automatically attempting one or more additional transmissions in response to the destination device not accepting or declining delivery of the voice message. | 7. A method comprising: receiving, at a server, an input from a mobile device, the input comprising a text message and one or more destination addresses; converting the text message into a voice message; transmitting the voice message along with an acknowledge message from the server to the one or more destination addresses, wherein the acknowledge message permits a destination device to accept delivery of the voice message or to decline delivery of the voice message; receiving, at the server, a reply voice message from the destination device in response to the destination device accepting delivery of the voice message; and automatically attempting one or more additional transmissions in response to the destination device not accepting or declining delivery of the voice message. 11. The method of claim 7 , further comprising transmitting an email message from the server to a device, wherein the email message includes the reply voice message. | 0.890146 |
7,805,391 | 3 | 7 | 3. The computer implemented method of claim 2 , further comprising: receiving a second fact at the database, wherein the second fact is related to the anomalous behavior; and responsive to receiving the second fact, executing the action trigger. | 3. The computer implemented method of claim 2 , further comprising: receiving a second fact at the database, wherein the second fact is related to the anomalous behavior; and responsive to receiving the second fact, executing the action trigger. 7. The computer implemented method of claim 3 , wherein the action trigger is executed in response to at least one of the probability of the first inference exceeding a first pre-selected value, a significance of the inference exceeding a second pre-selected value, a rate of change in the probability of the first inference exceeding a third pre-selected value, and an amount of change in the probability of the first inference exceeding a fourth pre-selected value. | 0.927664 |
4,460,975 | 30 | 32 | 30. The process of claim 29 wherein the user may respond to presentation of the fifth stimulus by directing to change the data base designation and wherein the fourth stimulus again is presented. | 30. The process of claim 29 wherein the user may respond to presentation of the fifth stimulus by directing to change the data base designation and wherein the fourth stimulus again is presented. 32. The process of claim 30 wherein the user responds to the presentation of the fourth stimulus by directing that no further lines of text in the body are designated and further comprising a sixth prompting stimulus indicating that a choice of format feature is to be made, the sixth prompting stimulus is presented in combination with a menu of command choices, including page format feature, body feature, and line-totals feature. | 0.792625 |
8,884,885 | 3 | 4 | 3. The touch pad according to claim 2 , wherein the processing unit further comprises: a second processing unit configured to determine whether the touch pad can be used as an input device by determining whether the trace graph is matched with the graphical password on the basis of the second comparison value. | 3. The touch pad according to claim 2 , wherein the processing unit further comprises: a second processing unit configured to determine whether the touch pad can be used as an input device by determining whether the trace graph is matched with the graphical password on the basis of the second comparison value. 4. The touch pad according to claim 3 , wherein the first comparing unit and the second comparing unit are the same or different comparing units, and/or the first processing unit and the second processing unit are the same or different processing units. | 0.946737 |
8,941,589 | 29 | 30 | 29. The system of claim 1 , wherein each sensor corresponds to a sensing volume in the SOE. | 29. The system of claim 1 , wherein each sensor corresponds to a sensing volume in the SOE. 30. The system of claim 29 , wherein each sensor estimates a pose of each tag within the sensing volume. | 0.956485 |
9,538,343 | 12 | 19 | 12. A device, comprising: a transceiver; and a processor to implement a voice engine, wherein the processor is to receive an incoming call from a caller's device using the transceiver, determine a locale preference associated with the caller's device, dynamically configure the voice engine using locale settings associated with the determined locale preference, send a query message to the caller's device using the transceiver, parse a voice response from the caller to the query message using the voice engine, and process the incoming call in the called device based on the voice response. | 12. A device, comprising: a transceiver; and a processor to implement a voice engine, wherein the processor is to receive an incoming call from a caller's device using the transceiver, determine a locale preference associated with the caller's device, dynamically configure the voice engine using locale settings associated with the determined locale preference, send a query message to the caller's device using the transceiver, parse a voice response from the caller to the query message using the voice engine, and process the incoming call in the called device based on the voice response. 19. The device of claim 12 , wherein the processor is to receive the locale preference from the caller's device. | 0.783784 |
8,032,517 | 4 | 5 | 4. The method according to claim 1 , wherein to each association is assigned a numerical value as measure for the similarity of their associated components. | 4. The method according to claim 1 , wherein to each association is assigned a numerical value as measure for the similarity of their associated components. 5. The method according to claim 4 , wherein the associations are weighted according to their importance for the similarity of character strings. | 0.954288 |
7,747,651 | 14 | 18 | 14. A computer readable storage medium comprising instructions that cause a computing device to: provide a metadata model including model objects representing the data source, the metadata model having a query layer and a package layer, the query layer providing a business view of the data in the data source, the query layer including query subjects, wherein the query subjects directly describe actual physical data within an underlying database, are used in creating reports, and are abstracted and separate from the underlying database that includes physical data from one or more data sources, and wherein the package layer includes packages having direct references to the query subjects; generate a query specification based on a user input using the client application, the query specification is not in a form applicable to the data source directly; translate the generated query specification by the computer into a query applicable to the data source based on the query subjects referred to by the packages in the package layer in the metadata model, wherein the query is executed using a data source specification language of the data source, and wherein the query includes data query language statements that are embedded within the query subjects in the metadata model; and provide the query to the data source for execution. | 14. A computer readable storage medium comprising instructions that cause a computing device to: provide a metadata model including model objects representing the data source, the metadata model having a query layer and a package layer, the query layer providing a business view of the data in the data source, the query layer including query subjects, wherein the query subjects directly describe actual physical data within an underlying database, are used in creating reports, and are abstracted and separate from the underlying database that includes physical data from one or more data sources, and wherein the package layer includes packages having direct references to the query subjects; generate a query specification based on a user input using the client application, the query specification is not in a form applicable to the data source directly; translate the generated query specification by the computer into a query applicable to the data source based on the query subjects referred to by the packages in the package layer in the metadata model, wherein the query is executed using a data source specification language of the data source, and wherein the query includes data query language statements that are embedded within the query subjects in the metadata model; and provide the query to the data source for execution. 18. The computer readable storage medium of claim 14 , wherein the query layer includes query items that are attributes of the physical data. | 0.83012 |
9,837,070 | 13 | 14 | 13. The method of claim 12 , further comprising using the identified mapping in the automated speech recognition system in response to determining that the mapping likely represents a valid pronunciation. | 13. The method of claim 12 , further comprising using the identified mapping in the automated speech recognition system in response to determining that the mapping likely represents a valid pronunciation. 14. The method of claim 13 , wherein using the identified mapping in the automated speech recognition system comprises using the identified mapping to transcribe utterances received from multiple users. | 0.972176 |
9,789,605 | 14 | 21 | 14. A non-transitory computer-readable storage medium having a plurality of instructions stored thereon, the instructions being executable by a processing apparatus to operate a robot, the instructions configured to, when executed by the processing apparatus, cause the processing apparatus to: define a policy comprising a plurality of parameters configured to determine robot actions based at least in part on sensory-data inputs, wherein the policy maps the sensory-data inputs to robot actions; receive a first sensory-data input; perform a first robot action at a first action time, wherein the first action is determined based at least in part on the first sensory-data input and application of the policy; determine that a user input was received at an input time corresponding to the first action time, wherein a corrective command at least partially derived from the user input specifies a corrective robot action for physical performance, the user input being indicative of at least partial dissatisfaction with the first robot action; and modify the policy based on the corrective command and the first sensory-data input. | 14. A non-transitory computer-readable storage medium having a plurality of instructions stored thereon, the instructions being executable by a processing apparatus to operate a robot, the instructions configured to, when executed by the processing apparatus, cause the processing apparatus to: define a policy comprising a plurality of parameters configured to determine robot actions based at least in part on sensory-data inputs, wherein the policy maps the sensory-data inputs to robot actions; receive a first sensory-data input; perform a first robot action at a first action time, wherein the first action is determined based at least in part on the first sensory-data input and application of the policy; determine that a user input was received at an input time corresponding to the first action time, wherein a corrective command at least partially derived from the user input specifies a corrective robot action for physical performance, the user input being indicative of at least partial dissatisfaction with the first robot action; and modify the policy based on the corrective command and the first sensory-data input. 21. The non-transitory computer-readable storage medium of claim 14 , wherein the at least partial dissatisfaction includes a discrepancy between a target robot action and the first robot action. | 0.758663 |
8,918,417 | 10 | 17 | 10. A system comprising one or more computers programmed to perform operations comprising: obtaining a group of query pairs, each query pair including a first query and a second query; determining, using one or more computers, a quality score for each query pair in the group of query pairs; determining a diversity score for each query pair in the group of query pairs having a quality score satisfying a quality threshold; and associating, for each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair with the first query of the query pair as a candidate refinement for the first query; selecting a group of candidate refinements associated with a candidate query, the group of candidate refinements ordered according to an order; processing one or more of the candidate refinements according to the order and determining, for at least one additional candidate refinement in the one or more processed candidate refinements, that the additional candidate refinement has an intra-suggestion diversity score satisfying an intra-suggestion diversity threshold, the intra-suggestion diversity score estimating diversity between a first group of top documents responsive to the additional candidate refinement and a group of seen documents; associating the additional candidate refinement with the candidate query as a confirmed refinement; and adding the first group of top documents to the group of seen documents. | 10. A system comprising one or more computers programmed to perform operations comprising: obtaining a group of query pairs, each query pair including a first query and a second query; determining, using one or more computers, a quality score for each query pair in the group of query pairs; determining a diversity score for each query pair in the group of query pairs having a quality score satisfying a quality threshold; and associating, for each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair with the first query of the query pair as a candidate refinement for the first query; selecting a group of candidate refinements associated with a candidate query, the group of candidate refinements ordered according to an order; processing one or more of the candidate refinements according to the order and determining, for at least one additional candidate refinement in the one or more processed candidate refinements, that the additional candidate refinement has an intra-suggestion diversity score satisfying an intra-suggestion diversity threshold, the intra-suggestion diversity score estimating diversity between a first group of top documents responsive to the additional candidate refinement and a group of seen documents; associating the additional candidate refinement with the candidate query as a confirmed refinement; and adding the first group of top documents to the group of seen documents. 17. The system of claim 10 , wherein the quality threshold has a first value when the second query in a query pair is a query superstring of a first query in the query pair and a different second value when the second query is not a super string of the first query. | 0.742718 |
8,947,355 | 1 | 2 | 1. A computer-implemented method of enabling a user to provide input to an electronic device, comprising: under control of one or more computing systems configured with executable instructions, determining a default relative orientation of the electronic device using at least in part at least one imaging element of the electronic device, wherein the default relative orientation of the electronic device comprises a relative orientation of the electronic device with respect to an aspect of a user of the electronic device; detecting a change in the relative orientation of the electronic device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the electronic device is detected using at least in part the at least one imaging element, and wherein the electronic device displays a plurality of selectable elements in a graphical user interface; if the change in relative orientation meets or exceeds a coarse threshold, moving a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a first rate; if the change in relative orientation meets or exceeds a fine threshold, but is less than the coarse threshold, moving the selection element in a direction corresponding to a direction of the change in relative orientation at a second rate less than the first rate; if the change in relative orientation is less than the fine threshold but the detected relative orientation is different from the default relative orientation, maintaining a position of the selection element with respect to one of the selectable elements currently associated with the selection element; and in response to receiving a selection action, providing the selectable element currently associated with the selection element as input to the electronic device. | 1. A computer-implemented method of enabling a user to provide input to an electronic device, comprising: under control of one or more computing systems configured with executable instructions, determining a default relative orientation of the electronic device using at least in part at least one imaging element of the electronic device, wherein the default relative orientation of the electronic device comprises a relative orientation of the electronic device with respect to an aspect of a user of the electronic device; detecting a change in the relative orientation of the electronic device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the electronic device is detected using at least in part the at least one imaging element, and wherein the electronic device displays a plurality of selectable elements in a graphical user interface; if the change in relative orientation meets or exceeds a coarse threshold, moving a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a first rate; if the change in relative orientation meets or exceeds a fine threshold, but is less than the coarse threshold, moving the selection element in a direction corresponding to a direction of the change in relative orientation at a second rate less than the first rate; if the change in relative orientation is less than the fine threshold but the detected relative orientation is different from the default relative orientation, maintaining a position of the selection element with respect to one of the selectable elements currently associated with the selection element; and in response to receiving a selection action, providing the selectable element currently associated with the selection element as input to the electronic device. 2. The computer-implemented method of claim 1 , wherein the plurality of selectable characters comprise alphanumeric characters arranged in a substantially circular, substantially linear, or QWERTY keyboard layout. | 0.682493 |
9,288,156 | 1 | 2 | 1. A method for maintaining a plurality of dialog sessions of a multi-modal dialog application in a server, the method comprising: storing session state information for at least one suspended dialog session of a plurality of dialog sessions with the multi-modal dialog application in the server, the session state information including a unique identifier; reducing an amount of the session state information stored; releasing resources associated with at least the amount reduced; and automatically resuming the at least one suspended dialog session with the reduced session state information stored based on the unique identifier and a detected interaction with the multi-modal dialog application. | 1. A method for maintaining a plurality of dialog sessions of a multi-modal dialog application in a server, the method comprising: storing session state information for at least one suspended dialog session of a plurality of dialog sessions with the multi-modal dialog application in the server, the session state information including a unique identifier; reducing an amount of the session state information stored; releasing resources associated with at least the amount reduced; and automatically resuming the at least one suspended dialog session with the reduced session state information stored based on the unique identifier and a detected interaction with the multi-modal dialog application. 2. The method of claim 1 wherein the at least one suspended dialog session was suspended automatically based on a configurable setting of the at least one suspended dialog session and optionally wherein the session state information includes a session attribute for disambiguation. | 0.869545 |
8,745,091 | 1 | 13 | 1. In a computing system, a method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one of one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories; receiving a user feedback regarding prioritization of the one of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising: associating one or more concepts with the one of the one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. | 1. In a computing system, a method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one of one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories; receiving a user feedback regarding prioritization of the one of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising: associating one or more concepts with the one of the one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. 13. The method of claim 1 , further comprising assigning a retention level to the electronic document based on the classification of the electronic document. | 0.872977 |
7,966,174 | 3 | 4 | 3. The system of claim 2 , wherein the second module configured to control the processor to cluster is further configured to control the processor to cluster the non-context tokens into a cluster tree. | 3. The system of claim 2 , wherein the second module configured to control the processor to cluster is further configured to control the processor to cluster the non-context tokens into a cluster tree. 4. The system of claim 3 , wherein the cluster tree represents a grammatical relationship among the non-context tokens. | 0.909299 |
9,305,307 | 18 | 19 | 18. The system of claim 17 wherein the first collection of entities is named, and wherein the instructions further include instructions that cause the one or more processors to provide to the content sponsor an interface for enabling a selection of the first collection of entities from a plurality of available collection of entities, and receive from content sponsor an explicit designation of the first collection of entities by name to be used as the selection criteria for delivery of the first content item. | 18. The system of claim 17 wherein the first collection of entities is named, and wherein the instructions further include instructions that cause the one or more processors to provide to the content sponsor an interface for enabling a selection of the first collection of entities from a plurality of available collection of entities, and receive from content sponsor an explicit designation of the first collection of entities by name to be used as the selection criteria for delivery of the first content item. 19. The system of claim 18 wherein the explicit designation includes a designation of the first collection of entities and an amount of a bid to be used when evaluating the first content item with other eligible content items in an auction or reservation selection system. | 0.943001 |
9,727,608 | 7 | 8 | 7. The system of claim 4 , wherein identifying one or more predefined constraints pertaining to executing the database workload comprises identifying a plurality of distinct constraints including at least two of a first constraint, a second constraint, a third constraint, a fourth constraint, and a fifth constraint, wherein programmatically refining the statistical view candidates based on the identified one or more predefined constraints comprises programmatically refining the statistical view candidates based on the plurality of distinct constraints, wherein at least one generated statistical view includes a column sub-expression or specifies to generate statistics pertaining to a column group having a plurality of columns. | 7. The system of claim 4 , wherein identifying one or more predefined constraints pertaining to executing the database workload comprises identifying a plurality of distinct constraints including at least two of a first constraint, a second constraint, a third constraint, a fourth constraint, and a fifth constraint, wherein programmatically refining the statistical view candidates based on the identified one or more predefined constraints comprises programmatically refining the statistical view candidates based on the plurality of distinct constraints, wherein at least one generated statistical view includes a column sub-expression or specifies to generate statistics pertaining to a column group having a plurality of columns. 8. The system of claim 7 , wherein the first constraint refines a first specified statistical view candidate by imposing a limit on a total count of columns in the first specified statistical view candidate, wherein the second constraint refines the plurality of statistical view candidates by imposing a limit on a total count of statistical views generated from the plurality of statistical view candidates, wherein the operation further comprises identifying, for the database workload, a set of criteria one or more one or more fact tables, one or more dimension tables, one or more express joins, and one or more implied joins, the set of criteria further including the respective arity for each of the plurality of joins and the respective skew for each of the plurality of joins, wherein the plurality of statistical view candidates is generated based on the identified set of criteria, wherein the third constraint refines the plurality of statistical view candidates by imposing a limit on a total count of statistical views generated from the plurality of statistical view candidates, for a specified database table. | 0.815772 |
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