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9,916,300 | 9 | 14 | 9. A method comprising: receiving, by use of a processor, a handwritten sub-character, the handwritten sub-character comprising one or more character strokes; determining a hint list based on the handwritten sub-character, the hint list comprising at least one entry, each entry being a character that comprises the handwritten sub-character; identifying a number of post-character strokes corresponding to each entry in the hint list, a post-character stroke being a stroke added to the sub-character to form the entry; receiving the at least one indication of an additional stroke relating to the handwritten sub-character, wherein the at least one indication of an additional stroke is a different input than a character stroke, said indication selected from the group consisting of: a tap that represents an additional character stroke and does not indicate a specific character stroke at a location of the touch-sensitive input panel adjacent to a location of the handwritten sub-character, a button press that represents an additional character stroke and does not indicate a specific character stroke; and updating the hint list based on a number of additional strokes determined using the at least one indication of an additional stroke, wherein updating the hint list based on the number of additional strokes comprises removing each entry in the hint list whose number of post-character strokes is less than the number of additional strokes. | 9. A method comprising: receiving, by use of a processor, a handwritten sub-character, the handwritten sub-character comprising one or more character strokes; determining a hint list based on the handwritten sub-character, the hint list comprising at least one entry, each entry being a character that comprises the handwritten sub-character; identifying a number of post-character strokes corresponding to each entry in the hint list, a post-character stroke being a stroke added to the sub-character to form the entry; receiving the at least one indication of an additional stroke relating to the handwritten sub-character, wherein the at least one indication of an additional stroke is a different input than a character stroke, said indication selected from the group consisting of: a tap that represents an additional character stroke and does not indicate a specific character stroke at a location of the touch-sensitive input panel adjacent to a location of the handwritten sub-character, a button press that represents an additional character stroke and does not indicate a specific character stroke; and updating the hint list based on a number of additional strokes determined using the at least one indication of an additional stroke, wherein updating the hint list based on the number of additional strokes comprises removing each entry in the hint list whose number of post-character strokes is less than the number of additional strokes. 14. The method of claim 9 , wherein receiving a handwritten sub-character comprises: receiving handwriting input; determining whether the handwriting input forms a handwritten sub-character; identifying a character radical corresponding to the handwritten sub-character in response to the handwriting input forming a handwritten sub-character; and monitoring for another stroke of handwriting input in response to handwriting input not forming a handwritten sub-character. | 0.615008 |
8,751,217 | 4 | 6 | 4. The process of claim 1 , further comprising: providing a context indicator to the server such that the speech recognition system can select a language model from a plurality of language models based on the context indicator, where the context indicator specifies the context in which the user input is received. | 4. The process of claim 1 , further comprising: providing a context indicator to the server such that the speech recognition system can select a language model from a plurality of language models based on the context indicator, where the context indicator specifies the context in which the user input is received. 6. The process of claim 4 , wherein the context indicator specifies an application in which the user input is received. | 0.967451 |
8,527,508 | 13 | 17 | 13. A non-transitory storage medium storing an input assistance program, the input assistance program causing the computer to execute: referring to stored plurality of input candidates for an input item, and historical values that indicate an input history of information of each of the plurality of input candidates for the input item; determining a first display order of the plurality of input candidates based on the historical values to change the first display order of the plurality of input candidates for the input item into a second display order by replacing a first input candidate from among the plurality of input candidates for the input item in a first range from a top percentile priority with a second input candidate in a second range from another percentile priority that is outside of the first range in the top percentile priority; and outputting the plurality of input candidates for the input item to a display according to the second display order. | 13. A non-transitory storage medium storing an input assistance program, the input assistance program causing the computer to execute: referring to stored plurality of input candidates for an input item, and historical values that indicate an input history of information of each of the plurality of input candidates for the input item; determining a first display order of the plurality of input candidates based on the historical values to change the first display order of the plurality of input candidates for the input item into a second display order by replacing a first input candidate from among the plurality of input candidates for the input item in a first range from a top percentile priority with a second input candidate in a second range from another percentile priority that is outside of the first range in the top percentile priority; and outputting the plurality of input candidates for the input item to a display according to the second display order. 17. The non-transitory storage medium storing the input assistance program according to claim 13 further causing the computer to execute: referring to stored number of times a user selects an input candidate having a specified priority in a display order; and notifying a number of times an input candidate having the specified priority is selected is equal to or more than a threshold. | 0.501292 |
7,743,079 | 15 | 18 | 15. A computer-readable storage medium which stores a set of instructions which when executed performs a method for managing data across a semantic data view and a presentation data view, the method executed by the set of instructions comprising: maintaining a semantic model corresponding to the semantic data view, the semantic model having at least one node; maintaining a presentation model corresponding to the presentation data view, the presentation model corresponding to a graphical representation of the semantic model, the presentation model including at least two shapes corresponding to the at least one node, the presentation model configured to select the at least two shapes when the at least one node is selected in the semantic data view; operating on the semantic model and the presentation model according to a received command, wherein operating on the semantic model and the presentation model comprises performing operations on both the presentation data view and the semantic data view in response to the received command being directed to one of the presentation data view and the semantic data view, wherein performing operation on both the presentation data view and the semantic data view comprises: displaying an unfocused representation of the at least one node of the semantic data view in response to the received command comprising a selection of at least one of the at least two shapes in the presentation data view, and selecting text corresponding to the at least one node of the plurality of nodes in the semantic data view in response to the received command comprising a command to switch focus to the semantic data view from the presentation data view, wherein the text corresponding to the at least one node of the plurality of nodes in the semantic data view is associated with the selected at least one shape of the plurality of shapes in the presentation data view; and displaying an insertion point at a default node of the semantic data view in response to a transition shape being selected in the presentation data view, wherein the transition shape does not correspond to the at least one node in the semantic data view. | 15. A computer-readable storage medium which stores a set of instructions which when executed performs a method for managing data across a semantic data view and a presentation data view, the method executed by the set of instructions comprising: maintaining a semantic model corresponding to the semantic data view, the semantic model having at least one node; maintaining a presentation model corresponding to the presentation data view, the presentation model corresponding to a graphical representation of the semantic model, the presentation model including at least two shapes corresponding to the at least one node, the presentation model configured to select the at least two shapes when the at least one node is selected in the semantic data view; operating on the semantic model and the presentation model according to a received command, wherein operating on the semantic model and the presentation model comprises performing operations on both the presentation data view and the semantic data view in response to the received command being directed to one of the presentation data view and the semantic data view, wherein performing operation on both the presentation data view and the semantic data view comprises: displaying an unfocused representation of the at least one node of the semantic data view in response to the received command comprising a selection of at least one of the at least two shapes in the presentation data view, and selecting text corresponding to the at least one node of the plurality of nodes in the semantic data view in response to the received command comprising a command to switch focus to the semantic data view from the presentation data view, wherein the text corresponding to the at least one node of the plurality of nodes in the semantic data view is associated with the selected at least one shape of the plurality of shapes in the presentation data view; and displaying an insertion point at a default node of the semantic data view in response to a transition shape being selected in the presentation data view, wherein the transition shape does not correspond to the at least one node in the semantic data view. 18. The computer-readable storage medium of claim 15 , wherein maintaining the semantic model and maintaining the presentation model comprises simultaneously maintaining the semantic model and the presentation model in a volatile memory in a computer. | 0.750992 |
8,219,976 | 8 | 10 | 8. A non-transitory computer-readable storage medium encoded with a computer program comprising instructions that, when executed, operate to cause a computer to perform operations comprising: providing a plurality of items, each item of the plurality of items being uniquely identified by an identifier and comprising at least one core attribute, the at least one core attribute being of a variable data type; defining a first context that describes a first set of items from the plurality of items, and that can describe a first other context, the first context including at least one of a first default context attribute and a first overriding context attribute, the first other context comprising one or more items of the first set of items; defining a second context that describes a second set of items from the plurality of items, and that can describe a second other context, the second context including at least one of a second default context attribute and a second overriding context attribute, the second other context comprising one or more items of the second set of items; generating a description language based on the first and second contexts; evaluating the description language based on the first context; generating a first list as a sub-set of items of the plurality of items based on the first context, wherein the first default context attribute is assigned to at least one item of the first list if the at least one item does not include a corresponding attribute, and wherein the first overriding context attribute replaces a corresponding core attribute of at least one item of the first list if the corresponding core attribute conflicts with the first overriding core attribute, the first list being associated with a first version of a software product; and displaying the first list. | 8. A non-transitory computer-readable storage medium encoded with a computer program comprising instructions that, when executed, operate to cause a computer to perform operations comprising: providing a plurality of items, each item of the plurality of items being uniquely identified by an identifier and comprising at least one core attribute, the at least one core attribute being of a variable data type; defining a first context that describes a first set of items from the plurality of items, and that can describe a first other context, the first context including at least one of a first default context attribute and a first overriding context attribute, the first other context comprising one or more items of the first set of items; defining a second context that describes a second set of items from the plurality of items, and that can describe a second other context, the second context including at least one of a second default context attribute and a second overriding context attribute, the second other context comprising one or more items of the second set of items; generating a description language based on the first and second contexts; evaluating the description language based on the first context; generating a first list as a sub-set of items of the plurality of items based on the first context, wherein the first default context attribute is assigned to at least one item of the first list if the at least one item does not include a corresponding attribute, and wherein the first overriding context attribute replaces a corresponding core attribute of at least one item of the first list if the corresponding core attribute conflicts with the first overriding core attribute, the first list being associated with a first version of a software product; and displaying the first list. 10. The non-transitory computer-readable storage medium of claim 8 , wherein the first and second contexts each explicitly exclude certain items from the plurality of items. | 0.89321 |
9,177,554 | 7 | 11 | 7. A system for reporting sentiment of a product, comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a program, wherein the processor is configured to execute instructions of the program to perform operations, and wherein the operations comprise: performing a text analysis on communications; determining at least one feature for the product based on the text analysis; generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength; determining a date associated with each of the sentiment values by extracting the date from the communications; for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules; and reporting how the sentiment values changed over time based on each date. | 7. A system for reporting sentiment of a product, comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a program, wherein the processor is configured to execute instructions of the program to perform operations, and wherein the operations comprise: performing a text analysis on communications; determining at least one feature for the product based on the text analysis; generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength; determining a date associated with each of the sentiment values by extracting the date from the communications; for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules; and reporting how the sentiment values changed over time based on each date. 11. The system of claim 7 , wherein each date is selected from: purchase date; and a communication date. | 0.801527 |
9,769,545 | 1 | 9 | 1. A method for delivering a media source, the method comprising: determining, by a processor, a first plurality of keywords from a portion of the media source, wherein the first plurality of keywords is generated from a language analysis process on words collected from the portion of the media source; selecting, by the processor, a second keyword from the first plurality of keywords, wherein the selecting the second keyword comprises scoring each of the first plurality of keywords based on a source of each of the first plurality of keywords, wherein the second keyword is determined based upon one or more of the first plurality of keywords that have a score above a threshold; searching, by the processor, a memory to identify a reference item related to the media source based upon the second keyword, wherein the reference item is external to the media source; filtering, by the processor, the reference item to generate a filtered reference item; embedding, by the processor, the filtered reference item into the media source; and delivering, by the processor, the media source embedded with the filtered reference item to a customer premises. | 1. A method for delivering a media source, the method comprising: determining, by a processor, a first plurality of keywords from a portion of the media source, wherein the first plurality of keywords is generated from a language analysis process on words collected from the portion of the media source; selecting, by the processor, a second keyword from the first plurality of keywords, wherein the selecting the second keyword comprises scoring each of the first plurality of keywords based on a source of each of the first plurality of keywords, wherein the second keyword is determined based upon one or more of the first plurality of keywords that have a score above a threshold; searching, by the processor, a memory to identify a reference item related to the media source based upon the second keyword, wherein the reference item is external to the media source; filtering, by the processor, the reference item to generate a filtered reference item; embedding, by the processor, the filtered reference item into the media source; and delivering, by the processor, the media source embedded with the filtered reference item to a customer premises. 9. The method of claim 1 , wherein the searching the memory is performed for the second keyword. | 0.904382 |
9,740,928 | 2 | 3 | 2. The method of claim 1 , further comprising: selecting a representative word image in the word cluster; selecting digitized text for the representative word image; and assigning the selected digitized text to each of the word images in the word cluster. | 2. The method of claim 1 , further comprising: selecting a representative word image in the word cluster; selecting digitized text for the representative word image; and assigning the selected digitized text to each of the word images in the word cluster. 3. The method of claim 2 , wherein the step of selecting a representative word image comprises: determining a mean of the values assigned to the word features in order to create feature vectors for the two of the word images that are assigned to the word cluster; and selecting, as the representative word image, the one of the two word images having values in its associated feature vector closest to the mean. | 0.830725 |
8,280,101 | 10 | 13 | 10. A method of authenticating an identification document, the identification document comprising: an image including steganographically encoded first machine-readable information including a first plural-bit message, a background including steganographically encoded second machine-readable information including a second plural-bit message, and semantic information including authentication information carried on or in the identification document, the method comprising: determining, using a processor, the first plural-bit message based on the first machine-readable information; determining the second plural-bit message based on the second machine-readable information; determining the authentication information from the semantic information carried on or in the identification document; decrypting the first plural-bit message or the authentication information; and determining whether the identification document is authentic based at least in part on the first plural-bit message, the second plural-bit message, and the authentication information, wherein the second plural-bit message comprises information from the first plural-bit message and the authentication information. | 10. A method of authenticating an identification document, the identification document comprising: an image including steganographically encoded first machine-readable information including a first plural-bit message, a background including steganographically encoded second machine-readable information including a second plural-bit message, and semantic information including authentication information carried on or in the identification document, the method comprising: determining, using a processor, the first plural-bit message based on the first machine-readable information; determining the second plural-bit message based on the second machine-readable information; determining the authentication information from the semantic information carried on or in the identification document; decrypting the first plural-bit message or the authentication information; and determining whether the identification document is authentic based at least in part on the first plural-bit message, the second plural-bit message, and the authentication information, wherein the second plural-bit message comprises information from the first plural-bit message and the authentication information. 13. The method of claim 10 , wherein the semantic information comprises data representing a photograph and the first machine-readable information comprises a digital watermark. | 0.780549 |
7,522,046 | 23 | 24 | 23. A method by which a physical-document monitoring device facilitates management of a physical document, the method comprising: sensing a state of the physical document, with a sensor coupled to a document coupling device; generating a signal representing the document state with the sensor; determining the document state based on the signal with a computer coupled to the sensor and the document coupling device; and generating a wireless signal to send a representation of the document state to a remote device. | 23. A method by which a physical-document monitoring device facilitates management of a physical document, the method comprising: sensing a state of the physical document, with a sensor coupled to a document coupling device; generating a signal representing the document state with the sensor; determining the document state based on the signal with a computer coupled to the sensor and the document coupling device; and generating a wireless signal to send a representation of the document state to a remote device. 24. The method of claim 23 , further comprising coupling the physical-document monitoring device to the document. | 0.781008 |
8,051,071 | 28 | 29 | 28. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount that a rank of a document changes over time; determining or adjusting, by one or more processors of the one or more devices, a score for the document based on the amount that the rank of the document changes over time; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. | 28. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount that a rank of a document changes over time; determining or adjusting, by one or more processors of the one or more devices, a score for the document based on the amount that the rank of the document changes over time; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. 29. The method of claim 28 , further comprising: employing measures to prevent the rank of the document from changing at more than a predetermined rate. | 0.898667 |
9,245,032 | 10 | 12 | 10. A system comprising: a communications interface that receives requests for web pages from client devices; and a hardware processor; and a memory storing a set of one or more locale-specific modules that each enable an interface of the client devices to perform one or more locale-specific formatting operations using the web pages when the interfaces render the web pages using one or more scripts associated with the web pages, the memory further storing a set of instructions that when executed by the processor cause the processor to: receive a request for a web page created in a specific language from an interface associated with a client device, the web page comprising content in the specific language, one or more elements in a first markup language used by an interface of the client device to display the content, and one or elements in a second markup language, the second markup language being an intermediate non-scripting language different from the first language; extract a locale-specific preference from a header in the request, the locale-specific preference in the header further including one or more entries that each indicate a preference level for document languages; select a locale-specific module corresponding to the locale-specific preference from the set of locale-specific modules, the selected locale-specific module built in a language supported by a script associated with the requested web page using one or more user-supplied definitions associating an element of the webpage in the second markup language with one or more locale-specific formattings; send the locale-specific module to the client device via the communications interface for storage at the client device; and send the requested web page to the client device via the communications interface for storage at the client device, wherein, when the client device encounters the element of the web page in the second markup language when executing the script, the client device uses the locale-specific module to determine the one or more locale-specific formattings. | 10. A system comprising: a communications interface that receives requests for web pages from client devices; and a hardware processor; and a memory storing a set of one or more locale-specific modules that each enable an interface of the client devices to perform one or more locale-specific formatting operations using the web pages when the interfaces render the web pages using one or more scripts associated with the web pages, the memory further storing a set of instructions that when executed by the processor cause the processor to: receive a request for a web page created in a specific language from an interface associated with a client device, the web page comprising content in the specific language, one or more elements in a first markup language used by an interface of the client device to display the content, and one or elements in a second markup language, the second markup language being an intermediate non-scripting language different from the first language; extract a locale-specific preference from a header in the request, the locale-specific preference in the header further including one or more entries that each indicate a preference level for document languages; select a locale-specific module corresponding to the locale-specific preference from the set of locale-specific modules, the selected locale-specific module built in a language supported by a script associated with the requested web page using one or more user-supplied definitions associating an element of the webpage in the second markup language with one or more locale-specific formattings; send the locale-specific module to the client device via the communications interface for storage at the client device; and send the requested web page to the client device via the communications interface for storage at the client device, wherein, when the client device encounters the element of the web page in the second markup language when executing the script, the client device uses the locale-specific module to determine the one or more locale-specific formattings. 12. The system of claim 10 , wherein the locale-specific preference comprises a locale-specific preference setting of the interface. | 0.825858 |
9,965,508 | 16 | 17 | 16. A device comprising: a set of processing units; and a non-transitory machine readable medium storing a program which when executed by the set of processing units determines the identity of an entity, the program comprising sets of instructions for: identifying a particular name that occurs more often than other names in a set of documents; identifying a plurality of candidate identity attribute sets by analyzing the particular name and at least one document in the set of documents using a plurality of different processes that each identifies (i) a set of candidate identities corresponding to the particular name and (ii) a candidate identity attribute set for each identified candidate identity, wherein at least one of the different processes analyzes a stored plurality of identities to identify candidate identities having the particular name and that are related to an entity to which the at least one document is also related; for each candidate identity attribute set of the plurality of candidate identity attribute sets, calculating a relevance score for each candidate identity attribute in the set that measures a level of correspondence between the particular name and the candidate identity attribute; and identifying, based on the relevance scores calculated for the candidate identity attributes of the different candidate identity attribute sets, a particular candidate identity attribute set for a particular identity that corresponds to the particular name. | 16. A device comprising: a set of processing units; and a non-transitory machine readable medium storing a program which when executed by the set of processing units determines the identity of an entity, the program comprising sets of instructions for: identifying a particular name that occurs more often than other names in a set of documents; identifying a plurality of candidate identity attribute sets by analyzing the particular name and at least one document in the set of documents using a plurality of different processes that each identifies (i) a set of candidate identities corresponding to the particular name and (ii) a candidate identity attribute set for each identified candidate identity, wherein at least one of the different processes analyzes a stored plurality of identities to identify candidate identities having the particular name and that are related to an entity to which the at least one document is also related; for each candidate identity attribute set of the plurality of candidate identity attribute sets, calculating a relevance score for each candidate identity attribute in the set that measures a level of correspondence between the particular name and the candidate identity attribute; and identifying, based on the relevance scores calculated for the candidate identity attributes of the different candidate identity attribute sets, a particular candidate identity attribute set for a particular identity that corresponds to the particular name. 17. The device of claim 16 , wherein the set of instructions for identifying the plurality of candidate identity attribute sets comprises a set of instructions for querying a set of databases to identify candidate identities and corresponding candidate identity attribute sets based on the particular name. | 0.565341 |
8,701,000 | 1 | 4 | 1. A computer-implemented method, comprising: outputting, for display, a plurality of open document representations in a carousel view, wherein each of the plurality of representations includes content from a corresponding open document and a document viewport portion is displayed in the carousel view, the document viewport portion corresponding to content from the corresponding open document that would be output for display in a full view of the corresponding open document; upon receiving an indication of a first gesture associated with a selected representation of the plurality of representations, outputting, for display, the full view of the document viewport portion of the open document corresponding to the selected representation; adjusting content of the open document included in the document viewport portion based upon a user navigation to a next position in the open document; and upon receiving an indication of a second gesture: closing the full view of the document viewport portion; and outputting, for display, the plurality of open document representations in the carousel view, wherein the document viewport portion for the selected representation is displayed in the carousel view corresponding to the adjusted content of the corresponding open document, and a remaining portion of the content from the corresponding open document is displayed outside of the document viewport portion for the selected representation. | 1. A computer-implemented method, comprising: outputting, for display, a plurality of open document representations in a carousel view, wherein each of the plurality of representations includes content from a corresponding open document and a document viewport portion is displayed in the carousel view, the document viewport portion corresponding to content from the corresponding open document that would be output for display in a full view of the corresponding open document; upon receiving an indication of a first gesture associated with a selected representation of the plurality of representations, outputting, for display, the full view of the document viewport portion of the open document corresponding to the selected representation; adjusting content of the open document included in the document viewport portion based upon a user navigation to a next position in the open document; and upon receiving an indication of a second gesture: closing the full view of the document viewport portion; and outputting, for display, the plurality of open document representations in the carousel view, wherein the document viewport portion for the selected representation is displayed in the carousel view corresponding to the adjusted content of the corresponding open document, and a remaining portion of the content from the corresponding open document is displayed outside of the document viewport portion for the selected representation. 4. The method of claim 1 , wherein outputting, for display, the plurality of open document representations includes outputting, for display, dynamic content of one or more of the plurality of representations. | 0.769912 |
8,819,006 | 13 | 16 | 13. The system of claim 12 , wherein selecting rich content items from one or more of the first rich content items and the second rich content items to be provided as one or more answer rich content items comprises: demoting the second images in the order in the first set relative to the first images in the first set wherein the images in the first set are ranked according to a revised order; selecting, from among the images in the first set, one or more images as one or more answer images, the selection based at least in part on the revised order; providing the one or more answer images with the answer to a user device from which the question query was received, the selection based at least in part on the revised order. | 13. The system of claim 12 , wherein selecting rich content items from one or more of the first rich content items and the second rich content items to be provided as one or more answer rich content items comprises: demoting the second images in the order in the first set relative to the first images in the first set wherein the images in the first set are ranked according to a revised order; selecting, from among the images in the first set, one or more images as one or more answer images, the selection based at least in part on the revised order; providing the one or more answer images with the answer to a user device from which the question query was received, the selection based at least in part on the revised order. 16. The system of claim 13 , wherein demoting the second images in the order in the first set relative to the first images in the first set comprises: for each second image included in only one of the second set or third set, demoting the second image in the first set in proportion to its ordinal position in the order in the other of the second set or third of images in which it is included, wherein the lower the ordinal position the higher the relevance of the image to the query. | 0.906695 |
9,373,048 | 5 | 6 | 5. A recognition system comprising: an image sensor; a processor coupled with the image sensor; a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to: receive, from the image sensor, an input image comprising one or more characters; pre-process the input image before extracting one or more nodes and edges of each character from the input image, the pre-processing comprising the steps of: detecting a boundary of the input image; identifying a location of each character based on the boundary of the input image; segmenting image of each character into one or more image segments from the location; and skeletonizing the one or more image segments of each character to generate one or more features representing the general form of the character; extract the one or more nodes and edges of each character from the input image; and generate a graphical representation of each character based on the one or more edges, wherein generating the graphical representation of each character comprises the steps of: generating the graphical representation using the edges of each skeletonized character; and determining the graphical wave ending position angle of each skeletonized character from the respective graphical representation thus generated; a comparison unit coupled with the processor and configured to compare the graphical representation of each character with a predetermined graphical representation of each reference character stored in a reference repository; and a validation unit coupled with the comparison unit and configured to recognize the reference character as one of the characters in the input image based on the comparing. | 5. A recognition system comprising: an image sensor; a processor coupled with the image sensor; a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to: receive, from the image sensor, an input image comprising one or more characters; pre-process the input image before extracting one or more nodes and edges of each character from the input image, the pre-processing comprising the steps of: detecting a boundary of the input image; identifying a location of each character based on the boundary of the input image; segmenting image of each character into one or more image segments from the location; and skeletonizing the one or more image segments of each character to generate one or more features representing the general form of the character; extract the one or more nodes and edges of each character from the input image; and generate a graphical representation of each character based on the one or more edges, wherein generating the graphical representation of each character comprises the steps of: generating the graphical representation using the edges of each skeletonized character; and determining the graphical wave ending position angle of each skeletonized character from the respective graphical representation thus generated; a comparison unit coupled with the processor and configured to compare the graphical representation of each character with a predetermined graphical representation of each reference character stored in a reference repository; and a validation unit coupled with the comparison unit and configured to recognize the reference character as one of the characters in the input image based on the comparing. 6. The system as claimed in claim 5 , wherein the instructions, on execution, further cause the processor to create the reference character repository by: pre-processing an image of one or more characters including at least alphabets, numbers and special characters; extracting one or more nodes and edges of each skeletonized character; generating the graphical representation and adjacency matrix for each skeletonized character using the one or more extracted nodes and edges; and storing the graphical representation and the adjacency matrix in the memory. | 0.67555 |
9,374,087 | 17 | 20 | 17. A virtual world processing method comprising: encoding information relating to sensor capability into first metadata based on predetermined representation syntax, wherein the predetermined representation syntax defines attributes and flags corresponding to the attributes, and wherein the first metadata includes the flags corresponding to the attributes, and at least one attribute corresponding to at least one flag having a predefined logic value; encoding information relating to a virtual world into second metadata, wherein the information relating to the virtual world comprises a virtual world object characteristic; generating information that is applied to the virtual world, based on the first metadata and the second metadata; and encoding the generated information into third metadata. | 17. A virtual world processing method comprising: encoding information relating to sensor capability into first metadata based on predetermined representation syntax, wherein the predetermined representation syntax defines attributes and flags corresponding to the attributes, and wherein the first metadata includes the flags corresponding to the attributes, and at least one attribute corresponding to at least one flag having a predefined logic value; encoding information relating to a virtual world into second metadata, wherein the information relating to the virtual world comprises a virtual world object characteristic; generating information that is applied to the virtual world, based on the first metadata and the second metadata; and encoding the generated information into third metadata. 20. The virtual world processing method of claim 17 , wherein the encoding of the information on sensor capability into the first metadata comprises generating the first metadata by encoding the information relating to sensor capability into an XML format. | 0.6 |
8,909,573 | 1 | 3 | 1. A computer-implemented method, comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more query-dependent feature scores that are based on dependencies to multiple query terms from each of one or more of the alteration terms; computing one or more intra-candidate-dependent feature scores that are based on dependencies between different terms in the alteration candidate; and computing a candidate score for the candidate using the one or more query-dependent feature scores and the one or more intra-candidate-dependent feature scores; and determining whether to select the candidate to expand the query, the determination using the candidate score. | 1. A computer-implemented method, comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more query-dependent feature scores that are based on dependencies to multiple query terms from each of one or more of the alteration terms; computing one or more intra-candidate-dependent feature scores that are based on dependencies between different terms in the alteration candidate; and computing a candidate score for the candidate using the one or more query-dependent feature scores and the one or more intra-candidate-dependent feature scores; and determining whether to select the candidate to expand the query, the determination using the candidate score. 3. The method of claim 1 , wherein the one or more query-dependent feature scores comprise one or more bigram scores that are based on dependencies between a pair of the alteration terms and multiple terms in the query. | 0.742958 |
9,390,195 | 13 | 14 | 13. The apparatus of claim 12 , wherein the first entity corresponds to a market research project, the second entity corresponds to a panelist, the fact vertices correspond to profile parameter vertices representing profile parameter values identified for the panelist, and the criteria vertices represent quota cells of market research projects. | 13. The apparatus of claim 12 , wherein the first entity corresponds to a market research project, the second entity corresponds to a panelist, the fact vertices correspond to profile parameter vertices representing profile parameter values identified for the panelist, and the criteria vertices represent quota cells of market research projects. 14. The apparatus of claim 13 , wherein a means for identifying a set of quota cells includes means for traversing edges of the graph database from a panelist vertex to all profile parameter value vertices of the graph database representing profile parameter values that have been identified for a panelist represented by the panelist vertex. | 0.903499 |
7,725,481 | 14 | 15 | 14. A computer-readable storage medium storing instructions that, when executed by a processor, perform operation comprising: receiving a first request for information corresponding to a word appearing in electronic content being rendered to a party submitting the first request when the first request is submitted, deriving context information for the word based on the electronic content being rendered to the party when the first request is submitted; storing the context information in association with the word; receiving a second request, at a time subsequent to the first request, for information corresponding to the word; in response to receiving the second request, accessing, from electronic storage, the context information stored in association with the word and derived based on the electronic content rendered during the first request; and enabling presentation, to a party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with information corresponding to the word. | 14. A computer-readable storage medium storing instructions that, when executed by a processor, perform operation comprising: receiving a first request for information corresponding to a word appearing in electronic content being rendered to a party submitting the first request when the first request is submitted, deriving context information for the word based on the electronic content being rendered to the party when the first request is submitted; storing the context information in association with the word; receiving a second request, at a time subsequent to the first request, for information corresponding to the word; in response to receiving the second request, accessing, from electronic storage, the context information stored in association with the word and derived based on the electronic content rendered during the first request; and enabling presentation, to a party submitting the second request, of the accessed context information derived based on the electronic content rendered during the first request along with information corresponding to the word. 15. The computer-readable storage medium of claim 14 wherein: receiving the first request and receiving the second request includes receiving the first request and the second request from a single party; and storing the context information includes storing the context information in association with an identifier for the single party. | 0.765035 |
8,370,126 | 18 | 23 | 18. The computer program product of claim 17 , wherein combining the text phrase of the abstract phrase and the text value comprises: combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; and wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the method further comprises: creating an integrated phrase, comprising removing delimiters from the delimited phrase. | 18. The computer program product of claim 17 , wherein combining the text phrase of the abstract phrase and the text value comprises: combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; and wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the method further comprises: creating an integrated phrase, comprising removing delimiters from the delimited phrase. 23. The computer program product of claim 18 , wherein the integration rule prevents one or more further rules from being applied to a portion of the delimited phrase. | 0.908141 |
7,739,280 | 1 | 2 | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on inferring preferences of a given user from a plurality of users of an input device, the preferences of the plurality of users of the input device being learned based on content items selected by the plurality of users, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental inputs from a shared input device; in response to said incremental input, presenting a corresponding subset of content items; receiving from the shared input device selection actions of content items; analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the shared input device, wherein the shared input device used by the plurality of users is a solitary input device used by each user of the plurality of users so that the composite set of preferred descriptive terms collectively describes the descriptive terms associated with content items selected by each of the users of the plurality; inferring preferences of individual users of the plurality of users of the shared input device from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms, said decomposition act utilizing prespecified statistical models of preferences of a population according to demographic information; subsequent to learning the composite set of preferred descriptive terms of the plurality of users, receiving at least one content item selection action from one of the individual users and selecting an individual set of preferred descriptive terms for use in subsequent content item selections based on comparing said at least one selected content item to the individual sets of preferred descriptive terms; in response to receiving subsequent incremental input from the shared input device, selecting and ordering a collection of content items based on the individual set of preferred descriptive terms selected for use in subsequent content item selections; and presenting the ordered collection of content items on a display device. | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on inferring preferences of a given user from a plurality of users of an input device, the preferences of the plurality of users of the input device being learned based on content items selected by the plurality of users, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving incremental inputs from a shared input device; in response to said incremental input, presenting a corresponding subset of content items; receiving from the shared input device selection actions of content items; analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the shared input device, wherein the shared input device used by the plurality of users is a solitary input device used by each user of the plurality of users so that the composite set of preferred descriptive terms collectively describes the descriptive terms associated with content items selected by each of the users of the plurality; inferring preferences of individual users of the plurality of users of the shared input device from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms, said decomposition act utilizing prespecified statistical models of preferences of a population according to demographic information; subsequent to learning the composite set of preferred descriptive terms of the plurality of users, receiving at least one content item selection action from one of the individual users and selecting an individual set of preferred descriptive terms for use in subsequent content item selections based on comparing said at least one selected content item to the individual sets of preferred descriptive terms; in response to receiving subsequent incremental input from the shared input device, selecting and ordering a collection of content items based on the individual set of preferred descriptive terms selected for use in subsequent content item selections; and presenting the ordered collection of content items on a display device. 2. The method of claim 1 , wherein the demographic information is at least one of age and gender. | 0.941847 |
9,704,486 | 12 | 14 | 12. The computer-implemented method of claim 5 , wherein the operation further comprising receiving speech recognition results from the second computing device. | 12. The computer-implemented method of claim 5 , wherein the operation further comprising receiving speech recognition results from the second computing device. 14. The computer-implemented method of claim 12 further comprising: activating a second module of the first computing device based at least in part on the one or more values, wherein the second module is configured to implement a speech recognition application; and processing the speech recognition results with the speech recognition application. | 0.89977 |
9,372,674 | 1 | 2 | 1. On a computing device, a method for presenting a user interface, the method comprising: receiving a request to display a list of items, each item of the list of items comprising a plurality of parts each having an appearance defined by a corresponding portion of a full version template; for an item in the list of items, populating the full version template with data for each of the plurality of parts to render a full version of a representation of the item; generating via the full version template a preview placeholder template defining an appearance of a thin version of a list item representation comprising a subset of the plurality of parts, the preview placeholder template comprising a subset of items of the full version template tagged for inclusion in the preview placeholder template, the subset of items comprising fewer items than the full version template; storing the preview placeholder template; and in response to a later request for scrolling the list of items, retrieving the preview placeholder template from storage and populating the preview placeholder template with data for the subset of the plurality of parts to render a thin version of one or more items in the list of items initially during scrolling, and then at a later time replacing the thin version of the one or more items in the list of items with the full version of the one or more items in the list of items. | 1. On a computing device, a method for presenting a user interface, the method comprising: receiving a request to display a list of items, each item of the list of items comprising a plurality of parts each having an appearance defined by a corresponding portion of a full version template; for an item in the list of items, populating the full version template with data for each of the plurality of parts to render a full version of a representation of the item; generating via the full version template a preview placeholder template defining an appearance of a thin version of a list item representation comprising a subset of the plurality of parts, the preview placeholder template comprising a subset of items of the full version template tagged for inclusion in the preview placeholder template, the subset of items comprising fewer items than the full version template; storing the preview placeholder template; and in response to a later request for scrolling the list of items, retrieving the preview placeholder template from storage and populating the preview placeholder template with data for the subset of the plurality of parts to render a thin version of one or more items in the list of items initially during scrolling, and then at a later time replacing the thin version of the one or more items in the list of items with the full version of the one or more items in the list of items. 2. The method of claim 1 , wherein storing the preview placeholder template further comprises storing the preview placeholder template in a cache memory of the computing device. | 0.858173 |
8,949,122 | 12 | 13 | 12. At least one non-transitory computer-readable storage medium encoded with computer-executable code that, when executed by at least one processor, causes the at least one processor to carry out a method of evaluating a plurality of stored audio phrases and at least one finite state grammar, wherein the at least one finite state grammar defines at least a first plurality of text phrases and wherein the plurality of stored audio phrases correspond to a second plurality of text phrases, the method comprising: determining, for each one text phrase of the first plurality of text phrases and based at least in part on phrase characteristics associated with the plurality of stored audio phrases, whether there is an audio phrase of the plurality of stored audio phrases that corresponds to the one text phrase; and identifying a phrase coverage for the at least one finite state grammar based at least in part on the determining, the phrase coverage indicating whether there are one or more text phrases of the first plurality of text phrases defined by the at least one finite state grammar to which none of the plurality of stored audio phrases corresponds. | 12. At least one non-transitory computer-readable storage medium encoded with computer-executable code that, when executed by at least one processor, causes the at least one processor to carry out a method of evaluating a plurality of stored audio phrases and at least one finite state grammar, wherein the at least one finite state grammar defines at least a first plurality of text phrases and wherein the plurality of stored audio phrases correspond to a second plurality of text phrases, the method comprising: determining, for each one text phrase of the first plurality of text phrases and based at least in part on phrase characteristics associated with the plurality of stored audio phrases, whether there is an audio phrase of the plurality of stored audio phrases that corresponds to the one text phrase; and identifying a phrase coverage for the at least one finite state grammar based at least in part on the determining, the phrase coverage indicating whether there are one or more text phrases of the first plurality of text phrases defined by the at least one finite state grammar to which none of the plurality of stored audio phrases corresponds. 13. The at least one non-transitory computer-readable storage medium of claim 12 , wherein the method further comprises: generating a test run package for the at least one finite state grammar including at least one stored audio phrase, of the plurality of stored audio phrases, that was determined in the determining to correspond to at least one text phrase of the first plurality of text phrases; and testing a speech recognition performance of the at least one finite state grammar using the test run package. | 0.703125 |
8,762,312 | 1 | 6 | 1. A computer implemented method for using sentiment-based analysis in content access, the method comprising the steps of: receiving a filtering policy by a computer, the received filtering policy specifying to filter a protected party's access to content based on fact-based categorization of content and subjective factors concerning content, wherein granularity of said filtering policy is variable by use of one or more of a plurality of combinations of fact-based categorization and subjective factors, wherein the protected party is being administered by a third party; detecting, by a computer, an attempt by the protected party to access specific content, the specific content being remotely located; categorizing, by a computer, the specific content based on occurrence of predefined words responsive to the access attempt; performing, by a computer, a sentiment-based analysis of the specific content responsive to the access attempt; responsive to results of the categorization in light of the sentiment-based analysis of the specific content, determining, by a computer, whether the filtering policy permits the protected party to access the specific content; responsive to results of the determining step, managing, by a computer, the attempted access of the specific content by the protected party. | 1. A computer implemented method for using sentiment-based analysis in content access, the method comprising the steps of: receiving a filtering policy by a computer, the received filtering policy specifying to filter a protected party's access to content based on fact-based categorization of content and subjective factors concerning content, wherein granularity of said filtering policy is variable by use of one or more of a plurality of combinations of fact-based categorization and subjective factors, wherein the protected party is being administered by a third party; detecting, by a computer, an attempt by the protected party to access specific content, the specific content being remotely located; categorizing, by a computer, the specific content based on occurrence of predefined words responsive to the access attempt; performing, by a computer, a sentiment-based analysis of the specific content responsive to the access attempt; responsive to results of the categorization in light of the sentiment-based analysis of the specific content, determining, by a computer, whether the filtering policy permits the protected party to access the specific content; responsive to results of the determining step, managing, by a computer, the attempted access of the specific content by the protected party. 6. The method of claim 1 wherein the subjective factors concerning content comprise an amount of subjectivity expressed by the content. | 0.890422 |
7,574,044 | 1 | 4 | 1. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that divides the text part extracted by the extracting unit according to colors of text contained in the extracted text part, wherein the colors of text are expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a keyword and a color of text as a search condition of text; and a text searching unit that searches the divided text part using the specified keyword and the specified color of text. | 1. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that divides the text part extracted by the extracting unit according to colors of text contained in the extracted text part, wherein the colors of text are expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a keyword and a color of text as a search condition of text; and a text searching unit that searches the divided text part using the specified keyword and the specified color of text. 4. The image processing apparatus according to claim 1 , further comprising: a compression unit that binarizes segment parts obtained by dividing the text part by the dividing unit and compresses the binarized segment parts. | 0.504425 |
6,144,958 | 11 | 12 | 11. The method of claim 1, wherein step (e) comprises using a spelling comparison function to compare the non-matching term to the additional terms, the spelling comparison function adapted to compare first and second character strings by sorting the first and second strings and comparing the sorted first and second strings on a character-by-character basis. | 11. The method of claim 1, wherein step (e) comprises using a spelling comparison function to compare the non-matching term to the additional terms, the spelling comparison function adapted to compare first and second character strings by sorting the first and second strings and comparing the sorted first and second strings on a character-by-character basis. 12. The method of claim 11, wherein the spelling comparison function generates a score which indicates a degree of similarity between the first and second character strings, and wherein step (e) further comprises comparing a score generated by the scoring function to a threshold value to determine whether a corresponding additional term is a candidate replacement, the threshold value dependent upon a number of characters in the non-matching term. | 0.837075 |
9,747,460 | 2 | 5 | 2. The method of claim 1 , further comprising: the at least one computer processor verifying that transmission of the electronic document is authorized; the at least one computer processor verifying that a device that provided the identification of the electronic document to be sent, the identification of a sender, and the identification of a receiver to the electronic document management system is authorized to request that the electronic document be sent; and the at least one computer processor verifying that the receiving device is authorized to receive the electronic document. | 2. The method of claim 1 , further comprising: the at least one computer processor verifying that transmission of the electronic document is authorized; the at least one computer processor verifying that a device that provided the identification of the electronic document to be sent, the identification of a sender, and the identification of a receiver to the electronic document management system is authorized to request that the electronic document be sent; and the at least one computer processor verifying that the receiving device is authorized to receive the electronic document. 5. The method of claim 2 , wherein the step of verifying that the sending device is authorized to send the electronic document comprises: the at least one computer processor verifying that the sending device is associated with the sender. | 0.932155 |
9,002,702 | 6 | 11 | 6. A system for assigning a confidence level to an axiom extracted from a text of a transcription of a voice recording, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and an audio transcription tool coupled to the bus that when executing the instructions causes the system to: receive the text of the transcription; compare every word from the text to a customer specific dictionary and a dictionary of common language words; determine a number of inaccurately spelled words in the transcription based on the comparing; assign, using a Gaussian distribution, a confidence level to the text of the transcription based on the determining; estimate an accuracy of the text based on the assigned confidence level; gather external information related to words in the text by retrieving a set of axioms that further define the words in the text of the transcription from a set of sources, each axiom in the set of axioms comprising a proposition that is regarded as being at least one of established, accepted, and self-evidently true; determine a confidence level of each source of the set of sources; and assign a confidence level to each axiom of the set of axioms based on a combination of the confidence level of the set of sources and the accuracy of the text estimated based on the assigned confidence level. | 6. A system for assigning a confidence level to an axiom extracted from a text of a transcription of a voice recording, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and an audio transcription tool coupled to the bus that when executing the instructions causes the system to: receive the text of the transcription; compare every word from the text to a customer specific dictionary and a dictionary of common language words; determine a number of inaccurately spelled words in the transcription based on the comparing; assign, using a Gaussian distribution, a confidence level to the text of the transcription based on the determining; estimate an accuracy of the text based on the assigned confidence level; gather external information related to words in the text by retrieving a set of axioms that further define the words in the text of the transcription from a set of sources, each axiom in the set of axioms comprising a proposition that is regarded as being at least one of established, accepted, and self-evidently true; determine a confidence level of each source of the set of sources; and assign a confidence level to each axiom of the set of axioms based on a combination of the confidence level of the set of sources and the accuracy of the text estimated based on the assigned confidence level. 11. The system of claim 6 , the memory medium further comprising instructions for causing the system to estimate an accuracy of the text of the transcription based on the confidence level of the source. | 0.582645 |
9,092,409 | 1 | 4 | 1. A method of modifying a map, comprising: searching, using a processor, a data element for user generated text that includes one or more apparent textual geo-annotations associated with the data element and input by a user indicating a location of interest; searching, by the processor, the data element for geocode information specifying a geographic location of the data element; determining, by the processor, a location proximity of (i) a geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element; calculating, using the processor, a level-of-detail score for the data element based on the apparent geo-annotations in the user generated text and the location proximity of (i) the geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element, wherein the level-of-detail score is a score corresponding to a geographic level of detail associated with the data element; determining that the score exceeds a threshold level-of-detail score, and in response, modifying the map to include a reference to the data element, wherein the reference is placed on a the map at a location corresponding to the data element; and storing the modified map including the reference to the data element in a memory device for subsequent presentation. | 1. A method of modifying a map, comprising: searching, using a processor, a data element for user generated text that includes one or more apparent textual geo-annotations associated with the data element and input by a user indicating a location of interest; searching, by the processor, the data element for geocode information specifying a geographic location of the data element; determining, by the processor, a location proximity of (i) a geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element; calculating, using the processor, a level-of-detail score for the data element based on the apparent geo-annotations in the user generated text and the location proximity of (i) the geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element, wherein the level-of-detail score is a score corresponding to a geographic level of detail associated with the data element; determining that the score exceeds a threshold level-of-detail score, and in response, modifying the map to include a reference to the data element, wherein the reference is placed on a the map at a location corresponding to the data element; and storing the modified map including the reference to the data element in a memory device for subsequent presentation. 4. The method of claim 1 , wherein the method further comprises: searching, using the processor, for metadata in the data element, wherein the calculating of the level-of-detail score is further based on the metadata. | 0.774428 |
7,984,071 | 1 | 2 | 1. A data processing system comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes a set of instructions; a set of hierarchical business objects; a plurality of templated business graphs; an instruction execution unit; and a processing unit connected to the bus system, wherein the processing unit executes the set of instructions to load a selected set of hierarchical business objects based on user input, wherein the set of hierarchical business objects is created by a user using a hierarchical business object design tool; present a plurality of templated business graphs that are unified modeling language models for a business graph to the user; receive a selection of a templated business graph that most suitably defines the set of hierarchical business objects from the plurality of templated business graphs; wrap the set of hierarchical business objects with the templated business graph such that the set of hierarchical business objects is combined with the templated business graph to define and enhance the set of hierarchical business objects with value added services to the user to form a templated business object, wherein a set of header objects in the templated business graph provide the value added services, and wherein the set of header objects is added to a top level of the set of hierarchical business objects; and save the templated business object as an Extensible Markup Language schema. | 1. A data processing system comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes a set of instructions; a set of hierarchical business objects; a plurality of templated business graphs; an instruction execution unit; and a processing unit connected to the bus system, wherein the processing unit executes the set of instructions to load a selected set of hierarchical business objects based on user input, wherein the set of hierarchical business objects is created by a user using a hierarchical business object design tool; present a plurality of templated business graphs that are unified modeling language models for a business graph to the user; receive a selection of a templated business graph that most suitably defines the set of hierarchical business objects from the plurality of templated business graphs; wrap the set of hierarchical business objects with the templated business graph such that the set of hierarchical business objects is combined with the templated business graph to define and enhance the set of hierarchical business objects with value added services to the user to form a templated business object, wherein a set of header objects in the templated business graph provide the value added services, and wherein the set of header objects is added to a top level of the set of hierarchical business objects; and save the templated business object as an Extensible Markup Language schema. 2. The data processing system of claim 1 , wherein the plurality of templated business graphs is stored in a data structure. | 0.504 |
9,384,263 | 1 | 8 | 1. A method comprising: receiving, by an enterprise content management (ECM) computing system comprising a computer processor, data associated with a subscriber; connecting, by said computer processor, devices belonging to said subscriber to said ECM computing system via an Intranet, wherein said devices comprise computing devices and storage devices; connecting, by said computer processor, end user systems associated with said subscriber to said ECM computing system via said Intranet, wherein said end user systems comprise service tools, documentation systems, and storage systems; connecting, by said computer processor, database and repository systems associated with said subscriber to said ECM computing system via said Intranet, wherein said database and repository systems comprise a database, an enterprise content management metadata system, and past search results; retrieving, by said computer processor from said devices, said end user systems, and said database and repository systems, metadata associated with content retrieved by said subscriber via said devices and said end user systems; analyzing, by said computer processor, said metadata, wherein said analyzing comprises: executing a text analytics process with respect to said metadata; executing a Web analytics process with respect to said metadata; and performing an analysis of said metadata with respect to dates of creation and modification of said content, a frequency of said modification being performed with respect to time periods, and numbers of shares of said content via emails; classifying, by said computer processor based on said analyzing said metadata, said content into formal content and informal content, wherein said formal content comprises content that has been uploaded to a primary repository of said ECM computing system, and wherein said informal content comprises content that has not been uploaded to said primary repository of said ECM computing system; generating, by said computer processor for said subscriber based on monitoring multiple searches for additional content initiated by said subscriber and results of said classifying, multifaceted search results associated with said formal content and said informal content; and presenting, by said computer processor to said subscriber, said multifaceted search results. | 1. A method comprising: receiving, by an enterprise content management (ECM) computing system comprising a computer processor, data associated with a subscriber; connecting, by said computer processor, devices belonging to said subscriber to said ECM computing system via an Intranet, wherein said devices comprise computing devices and storage devices; connecting, by said computer processor, end user systems associated with said subscriber to said ECM computing system via said Intranet, wherein said end user systems comprise service tools, documentation systems, and storage systems; connecting, by said computer processor, database and repository systems associated with said subscriber to said ECM computing system via said Intranet, wherein said database and repository systems comprise a database, an enterprise content management metadata system, and past search results; retrieving, by said computer processor from said devices, said end user systems, and said database and repository systems, metadata associated with content retrieved by said subscriber via said devices and said end user systems; analyzing, by said computer processor, said metadata, wherein said analyzing comprises: executing a text analytics process with respect to said metadata; executing a Web analytics process with respect to said metadata; and performing an analysis of said metadata with respect to dates of creation and modification of said content, a frequency of said modification being performed with respect to time periods, and numbers of shares of said content via emails; classifying, by said computer processor based on said analyzing said metadata, said content into formal content and informal content, wherein said formal content comprises content that has been uploaded to a primary repository of said ECM computing system, and wherein said informal content comprises content that has not been uploaded to said primary repository of said ECM computing system; generating, by said computer processor for said subscriber based on monitoring multiple searches for additional content initiated by said subscriber and results of said classifying, multifaceted search results associated with said formal content and said informal content; and presenting, by said computer processor to said subscriber, said multifaceted search results. 8. The method of claim 1 , further comprising: providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the computing system, said code being executed by the computer processor to implement: said receiving, said connecting said devices, said connecting said end user systems, said connecting said database, said retrieving, said analyzing, said classifying, said generating, and said presenting. | 0.675202 |
9,852,729 | 1 | 3 | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a sequence of feature vectors, wherein the sequence of feature vectors represents at least a portion of a stream of audio data; generate a keyword score based at least partly on a likelihood that a particular feature vector of the sequence of feature vectors represents audio data corresponding to a keyword; generate a background score based at least partly on a likelihood that the particular feature vector represents audio data corresponding to background audio; determine that a difference between the keyword score and the background score is greater than differences associated with feature vectors preceding the particular feature vector in a subset of the sequence of feature vectors, wherein the particular feature vector is in a center of the subset; determine that the difference is greater than differences associated with feature vectors subsequent to the particular feature vector in the subset; and generate data indicating the particular feature vector corresponds to an end of the keyword. | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a sequence of feature vectors, wherein the sequence of feature vectors represents at least a portion of a stream of audio data; generate a keyword score based at least partly on a likelihood that a particular feature vector of the sequence of feature vectors represents audio data corresponding to a keyword; generate a background score based at least partly on a likelihood that the particular feature vector represents audio data corresponding to background audio; determine that a difference between the keyword score and the background score is greater than differences associated with feature vectors preceding the particular feature vector in a subset of the sequence of feature vectors, wherein the particular feature vector is in a center of the subset; determine that the difference is greater than differences associated with feature vectors subsequent to the particular feature vector in the subset; and generate data indicating the particular feature vector corresponds to an end of the keyword. 3. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to at least determine a size of the subset based at least partly on an expected length of time for the keyword to be uttered. | 0.720418 |
9,665,650 | 15 | 18 | 15. A non-transitory computer-readable medium having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations comprising: identifying, by a browser assistant, a set of one or more context uniform resource identifiers; receiving, by the browser assistant, a set of one or more referenced uniform resource identifiers that are referenced by a search results page provided by a search engine; for each referenced uniform resource identifier, determining, by the browser assistant, a relatedness score based on an extent to which the referenced uniform resource identifier is related to one or more of the context uniform resource identifiers; selecting, by the browser assistant, a subset of the referenced uniform resource identifiers for presentation based on the relatedness scores; and providing, by the browser assistant, the subset of the referenced uniform resource identifiers for presentation as a web page in a browser window. | 15. A non-transitory computer-readable medium having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations comprising: identifying, by a browser assistant, a set of one or more context uniform resource identifiers; receiving, by the browser assistant, a set of one or more referenced uniform resource identifiers that are referenced by a search results page provided by a search engine; for each referenced uniform resource identifier, determining, by the browser assistant, a relatedness score based on an extent to which the referenced uniform resource identifier is related to one or more of the context uniform resource identifiers; selecting, by the browser assistant, a subset of the referenced uniform resource identifiers for presentation based on the relatedness scores; and providing, by the browser assistant, the subset of the referenced uniform resource identifiers for presentation as a web page in a browser window. 18. The computer-readable medium of claim 15 , wherein the extent to which the reference uniform resource identifier is related to one or more of the context uniform resource identifiers is based on a combination of two or more factors. | 0.796552 |
7,475,060 | 5 | 6 | 5. The graphics user interface of claim 1 wherein the display panels show the results a database query that is jointly specified by one or more constraint panels. | 5. The graphics user interface of claim 1 wherein the display panels show the results a database query that is jointly specified by one or more constraint panels. 6. The graphics user interface of claim 5 wherein a float mode can be invoked that allows a user to navigate a constraint panel without eliciting a database query. | 0.93954 |
9,773,043 | 1 | 5 | 1. An automated method for creating an implicit profile for use by at least one of a recommendation engine or a question router, comprising: tracking user behavior on one or more electronic devices of a user and an electronic communications network used to access the recommendation engine or question router; analyzing user-related information relating to the user behavior to extract and derive key words therefrom which are used to characterize user interests, expertise, and skills; assigning key word weightings to each of the key words; storing the key words and the key word weightings in a profiles database as the implicit profile; wherein: the key word weightings are assigned based on at least relevancy calculations of the user-related information and recency of the user-related information; the relevancy calculations are based on at least a relation of the user-related information to current key words in the implicit profile; at least the implicit profile is used by the recommendation engine or question router to provide expert recommendations or expert information to the user in response to a recommendation request or information request from the user; access to the recommendation engine or question router is restricted and requires user login; and the tracking is enabled via a crawling or searching application running on the one or more electronic devices of the user for searching various computer applications or storage locations on the one or more electronic devices for obtaining the user-related information. | 1. An automated method for creating an implicit profile for use by at least one of a recommendation engine or a question router, comprising: tracking user behavior on one or more electronic devices of a user and an electronic communications network used to access the recommendation engine or question router; analyzing user-related information relating to the user behavior to extract and derive key words therefrom which are used to characterize user interests, expertise, and skills; assigning key word weightings to each of the key words; storing the key words and the key word weightings in a profiles database as the implicit profile; wherein: the key word weightings are assigned based on at least relevancy calculations of the user-related information and recency of the user-related information; the relevancy calculations are based on at least a relation of the user-related information to current key words in the implicit profile; at least the implicit profile is used by the recommendation engine or question router to provide expert recommendations or expert information to the user in response to a recommendation request or information request from the user; access to the recommendation engine or question router is restricted and requires user login; and the tracking is enabled via a crawling or searching application running on the one or more electronic devices of the user for searching various computer applications or storage locations on the one or more electronic devices for obtaining the user-related information. 5. The method in accordance with claim 1 , wherein the user-related information comprises user requests submitted to the recommendation engine or the question router via online forms, emails, or computer applications that are recorded in a request database to find at least one of experts, analysts, or peers, or to receive requested information or materials. | 0.855475 |
9,934,221 | 7 | 13 | 7. A system, comprising: one or more processors; and one or more memories having stored therein instructions that, upon execution by the one or more processors, cause the one or more processors to perform operations comprising: identifying a plurality of user devices associated with a user of a document management and collaboration system on which the user has had a user session; determining that one or more documents associated with the user that were downloaded to the plurality of user devices from the document management and collaboration system should be deleted from the plurality of user devices; causing a targeted deletion of the one or more documents from the plurality of user devices; and receiving, from the plurality of user devices, indications of successful deletion of the one or more documents. | 7. A system, comprising: one or more processors; and one or more memories having stored therein instructions that, upon execution by the one or more processors, cause the one or more processors to perform operations comprising: identifying a plurality of user devices associated with a user of a document management and collaboration system on which the user has had a user session; determining that one or more documents associated with the user that were downloaded to the plurality of user devices from the document management and collaboration system should be deleted from the plurality of user devices; causing a targeted deletion of the one or more documents from the plurality of user devices; and receiving, from the plurality of user devices, indications of successful deletion of the one or more documents. 13. The system of claim 7 , wherein the causing the targeted deletion comprises: deleting documents associated with the user that are located on the plurality of user devices and that are on persistent disk storage and a metadata store; and terminating active user sessions. | 0.76007 |
8,762,827 | 15 | 19 | 15. A system for creating documentation, comprising: a memory storage device operable to store in a data store a plurality of document schemas, each document schema corresponding to a topic of a writing pattern provided by an authoring tool as a guide for a writer to author at least a portion of a document, each of the document schemas comprising a plurality of elements corresponding to a plurality of components of the writing pattern, each writing pattern corresponding to each of the document schemas is associated with several of distinct topic types, the topic types including at least one of questions for answering business-use and system-constraint questions about a task or function, conceptual information, examples of how to achieve a specific result, or definitions of at least one of application-specific words, phrases, or common business terms that have specific meaning, each component of the plurality of components corresponds to at least a portion of a document; at least one input device; and at least one processor operable to: for each of a plurality of documents: receive user selection of a component of a particular writing pattern corresponding to a visual element of a visual representation of a corresponding document schema, the visual representation including a plurality of graphic pairs each having an opening graphic and a closing graphic; receive user input representative of content for the selected visual component corresponding to the selected element; and add information corresponding to the user input to the document according to the corresponding document schema; and associate the added information from the plurality of documents together in a document collection. | 15. A system for creating documentation, comprising: a memory storage device operable to store in a data store a plurality of document schemas, each document schema corresponding to a topic of a writing pattern provided by an authoring tool as a guide for a writer to author at least a portion of a document, each of the document schemas comprising a plurality of elements corresponding to a plurality of components of the writing pattern, each writing pattern corresponding to each of the document schemas is associated with several of distinct topic types, the topic types including at least one of questions for answering business-use and system-constraint questions about a task or function, conceptual information, examples of how to achieve a specific result, or definitions of at least one of application-specific words, phrases, or common business terms that have specific meaning, each component of the plurality of components corresponds to at least a portion of a document; at least one input device; and at least one processor operable to: for each of a plurality of documents: receive user selection of a component of a particular writing pattern corresponding to a visual element of a visual representation of a corresponding document schema, the visual representation including a plurality of graphic pairs each having an opening graphic and a closing graphic; receive user input representative of content for the selected visual component corresponding to the selected element; and add information corresponding to the user input to the document according to the corresponding document schema; and associate the added information from the plurality of documents together in a document collection. 19. The system of claim 15 , wherein at least two of the schemas share a common element. | 0.931677 |
7,970,944 | 23 | 24 | 23. The method recited in claim 9 , wherein the interface definition mark-up language (IDML) comprises a primitive list tag for parameterizing iterative collections. | 23. The method recited in claim 9 , wherein the interface definition mark-up language (IDML) comprises a primitive list tag for parameterizing iterative collections. 24. The method recited in claim 23 , wherein the primitive list tag comprises a nested item tag. | 0.964072 |
9,412,367 | 78 | 80 | 78. Computerized information apparatus of a transport device, the computerized information apparatus configured to enable transport-device agnostic delivery of data to a plurality of personal electronic devices of a plurality of respective individual users, the computerized information apparatus comprising: data processing apparatus comprising at least a central processor and a digital signal processor (DSP); a first wireless interface in data communication with at least a portion of the data processing apparatus; a mass storage device in data communication with at least a portion of the data processing apparatus; a data interface in data communication with at least a portion of the data processing apparatus; a capacitive touch screen input and display device in data communication with at least a portion of the data processing apparatus and both viewable and accessible by the user; and computerized logic in data communication with at least a portion of the data processing annaratus and configured to: generate and present a plurality of iconic soft function keys having respective ones of predetermined topical functions associated therewith, on the capacitive touch screen input and display device, the topical functions each selectable by a user via touch of the touch screen input and display device in an appropriate region thereof, the plurality of iconic soft function keys facilitating rapid access by the user to data relating to the respective topical functions thereof; receive user input via at least one of the soft function keys, the user input designating one or more information elements; based at least on the user input, access a server via the first wireless interface in order to obtain at least a portion of the one or more information elements; establish a communication link with a portable electronic device of the user via the data interface; and utilize the established communication link to transfer at least a portion of the at least portion of information elements to the personal electronic device for storage thereon; wherein the computerized information apparatus further comprises second computerized logic configured to cause at least a portion of the user input to be stored on a server, the storage of the at least portion of the user input enabling the common configuration of subsequent information element accesses for delivery to the user's portable electronic device irrespective of whether the user utilizes the computerized information apparatus of the transport device or another information apparatus associated with another transport device, the second computerized logic also configured to store corresponding at least portions of user inputs from other users on the server, the storage of the corresponding at least portions facilitating the computerized information apparatus to configure subsequent information element accesses for delivery to portable devices of respective ones of those other users which are particular to those respective users; and wherein the computerized information apparatus further comprises radio frequency apparatus in data communication with at least a portion of the data processing apparatus, the radio frequency apparatus configured to receive data uniquely identifying a portable radio frequency device associated with the user and, based at least on the data uniquely identifying the portable radio frequency device, cause substantially automated configuration of and transfer of the at least portion of the information elements to the user's portable electronic device. | 78. Computerized information apparatus of a transport device, the computerized information apparatus configured to enable transport-device agnostic delivery of data to a plurality of personal electronic devices of a plurality of respective individual users, the computerized information apparatus comprising: data processing apparatus comprising at least a central processor and a digital signal processor (DSP); a first wireless interface in data communication with at least a portion of the data processing apparatus; a mass storage device in data communication with at least a portion of the data processing apparatus; a data interface in data communication with at least a portion of the data processing apparatus; a capacitive touch screen input and display device in data communication with at least a portion of the data processing apparatus and both viewable and accessible by the user; and computerized logic in data communication with at least a portion of the data processing annaratus and configured to: generate and present a plurality of iconic soft function keys having respective ones of predetermined topical functions associated therewith, on the capacitive touch screen input and display device, the topical functions each selectable by a user via touch of the touch screen input and display device in an appropriate region thereof, the plurality of iconic soft function keys facilitating rapid access by the user to data relating to the respective topical functions thereof; receive user input via at least one of the soft function keys, the user input designating one or more information elements; based at least on the user input, access a server via the first wireless interface in order to obtain at least a portion of the one or more information elements; establish a communication link with a portable electronic device of the user via the data interface; and utilize the established communication link to transfer at least a portion of the at least portion of information elements to the personal electronic device for storage thereon; wherein the computerized information apparatus further comprises second computerized logic configured to cause at least a portion of the user input to be stored on a server, the storage of the at least portion of the user input enabling the common configuration of subsequent information element accesses for delivery to the user's portable electronic device irrespective of whether the user utilizes the computerized information apparatus of the transport device or another information apparatus associated with another transport device, the second computerized logic also configured to store corresponding at least portions of user inputs from other users on the server, the storage of the corresponding at least portions facilitating the computerized information apparatus to configure subsequent information element accesses for delivery to portable devices of respective ones of those other users which are particular to those respective users; and wherein the computerized information apparatus further comprises radio frequency apparatus in data communication with at least a portion of the data processing apparatus, the radio frequency apparatus configured to receive data uniquely identifying a portable radio frequency device associated with the user and, based at least on the data uniquely identifying the portable radio frequency device, cause substantially automated configuration of and transfer of the at least portion of the information elements to the user's portable electronic device. 80. The computerized information apparatus of claim 78 , wherein the computerized information apparatus is further configured such that the data transfer can be initiated by the user's tactile selection of at least one display element displayed on the capacitive touch screen and display device. | 0.919399 |
10,050,918 | 9 | 13 | 9. A computer system for creating at least one new thread associated with an online conversation, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: determining if a predetermined time period has elapsed; in response to determining the predetermined time period has elapsed, monitoring the online conversation to detect a new or updated element of the online conversation; extracting the detected new or updated element; analyzing the online conversation and the extracted detected new or updated element to determine if a new online conversation has started; extracting a plurality of members associated with the online conversation based on the determination that a new online conversation has started; extracting a plurality of content associated with the extracted detected new or updated element based on the determination that a new online conversation has started; prompting a user to determine if a new online conversation should be created wherein the user created the extracted detected new or updated element; creating the new online conversation based on the user determining that the new conversation should be created; in response to creating the new online conversation and in response to the user triggering an interface gesture to start the new online conversation, creating a user profile for the user; notifying the plurality of extracted members about the created new online conversation; suggesting a plurality of new participants to the user; prompting the user to select a plurality of required and optional members from the notified plurality of extracted members and the suggested plurality of new participants to participate in the created new online conversation; and enabling the added plurality of required and optional members to participate in the created new online conversation. | 9. A computer system for creating at least one new thread associated with an online conversation, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: determining if a predetermined time period has elapsed; in response to determining the predetermined time period has elapsed, monitoring the online conversation to detect a new or updated element of the online conversation; extracting the detected new or updated element; analyzing the online conversation and the extracted detected new or updated element to determine if a new online conversation has started; extracting a plurality of members associated with the online conversation based on the determination that a new online conversation has started; extracting a plurality of content associated with the extracted detected new or updated element based on the determination that a new online conversation has started; prompting a user to determine if a new online conversation should be created wherein the user created the extracted detected new or updated element; creating the new online conversation based on the user determining that the new conversation should be created; in response to creating the new online conversation and in response to the user triggering an interface gesture to start the new online conversation, creating a user profile for the user; notifying the plurality of extracted members about the created new online conversation; suggesting a plurality of new participants to the user; prompting the user to select a plurality of required and optional members from the notified plurality of extracted members and the suggested plurality of new participants to participate in the created new online conversation; and enabling the added plurality of required and optional members to participate in the created new online conversation. 13. The computer system of claim 9 , wherein creating the new online conversation comprises adding at least one link to the online conversation at a point which the online conversation diverged. | 0.797071 |
8,423,978 | 1 | 5 | 1. A method in a data processing system for processing a JavaServer page, the method comprising: translating the JavaServer page into a document object model object; configuring a set of visitor classes for invocation in a selected sequence; and processing the document object model using the set of visitor classes in the selected sequence to perform a desired set of custom functions on the document object model. | 1. A method in a data processing system for processing a JavaServer page, the method comprising: translating the JavaServer page into a document object model object; configuring a set of visitor classes for invocation in a selected sequence; and processing the document object model using the set of visitor classes in the selected sequence to perform a desired set of custom functions on the document object model. 5. The method of claim 1 , wherein the set of visitor classes for invocation in the selected sequence is defined in a configuration file. | 0.872913 |
9,836,293 | 11 | 15 | 11. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a component log integration method comprising: executing, by at least one of the one or more computer processors, a software application; retrieving, by at least one of the one or more computer processors, from said software application, high level log identification values representing transactions executed by said software application; retrieving, by at least one of the one or more computer processors, from an agent within a hardware device, compiled machine language identification values representing compiled code associated with said software application and said hardware device; identifying, by at least one of the one or more computer processors, at least one high level log identification value of said high level log identification values, wherein said at least one high level log identification value is associated with at least one instruction set received from at least one of the one or more computer processors and processed by at least one central processing unit (CPU), wherein said at least one CPU comprises a first CPU and a second CPU executing parallel processing with respect to a first instruction set of said at least one instruction set and a second instruction set of said at least one instruction set; correlating, by at least one of the one or more computer processors, at least one instruction set identification value of said at least one instruction set with said high level log identification values and said compiled machine language identification values; converting, by at least one of the one or more computer processors, within a mediation layer of said at least one CPU, said compiled machine language identification values into decompiled machine language identification values; generating, by at least one of the one or more computer processors, a chip level generated log associated with hardware functions of said at least one CPU; additionally correlating, by at least one of the one or more computer processors, said decompiled machine language identification values with log levels associated with said high level log identification values and said chip level generated log; generating, by at least one of the one or more computer processors, based on results of said additionally correlating, a trend analysis associated with a machine cycle response of said at least one CPU; and determining, by at least one of the one or more computer processors, based on said machine cycle response of said at least one CPU, hardware related outages and malfunctions related to said at least one CPU. | 11. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a component log integration method comprising: executing, by at least one of the one or more computer processors, a software application; retrieving, by at least one of the one or more computer processors, from said software application, high level log identification values representing transactions executed by said software application; retrieving, by at least one of the one or more computer processors, from an agent within a hardware device, compiled machine language identification values representing compiled code associated with said software application and said hardware device; identifying, by at least one of the one or more computer processors, at least one high level log identification value of said high level log identification values, wherein said at least one high level log identification value is associated with at least one instruction set received from at least one of the one or more computer processors and processed by at least one central processing unit (CPU), wherein said at least one CPU comprises a first CPU and a second CPU executing parallel processing with respect to a first instruction set of said at least one instruction set and a second instruction set of said at least one instruction set; correlating, by at least one of the one or more computer processors, at least one instruction set identification value of said at least one instruction set with said high level log identification values and said compiled machine language identification values; converting, by at least one of the one or more computer processors, within a mediation layer of said at least one CPU, said compiled machine language identification values into decompiled machine language identification values; generating, by at least one of the one or more computer processors, a chip level generated log associated with hardware functions of said at least one CPU; additionally correlating, by at least one of the one or more computer processors, said decompiled machine language identification values with log levels associated with said high level log identification values and said chip level generated log; generating, by at least one of the one or more computer processors, based on results of said additionally correlating, a trend analysis associated with a machine cycle response of said at least one CPU; and determining, by at least one of the one or more computer processors, based on said machine cycle response of said at least one CPU, hardware related outages and malfunctions related to said at least one CPU. 15. The computing system of claim 11 , wherein said method further comprises: retrieving, by at least one of the one or more computer processors, directly from said at least one CPU, said high level log identification values. | 0.728261 |
9,083,731 | 1 | 2 | 1. A non-transitory computer readable medium storing software instructions which, when executed by a processor, cause the processor to perform a method for estimating a worst-case time complexity of a regular expression comprising one or more back-references (backref-regex), the method comprising: constructing a non-deterministic finite automaton (NFA) corresponding to the backref-regex (backref-NFA), wherein the backref-NFA comprises a plurality of NFA-states and a respectively labeled edge for each of the one or more back-references of the backref-regex; performing liveness analysis on the backref-NFA to determine for each NFA-state of the backref-NFA a set of back-references alive at the NFA-state; and determining a maximum number of alive back-references over the plurality of NFA-states, wherein the determined maximum number is indicative of the worst-case time complexity of the backref-regex. | 1. A non-transitory computer readable medium storing software instructions which, when executed by a processor, cause the processor to perform a method for estimating a worst-case time complexity of a regular expression comprising one or more back-references (backref-regex), the method comprising: constructing a non-deterministic finite automaton (NFA) corresponding to the backref-regex (backref-NFA), wherein the backref-NFA comprises a plurality of NFA-states and a respectively labeled edge for each of the one or more back-references of the backref-regex; performing liveness analysis on the backref-NFA to determine for each NFA-state of the backref-NFA a set of back-references alive at the NFA-state; and determining a maximum number of alive back-references over the plurality of NFA-states, wherein the determined maximum number is indicative of the worst-case time complexity of the backref-regex. 2. The medium of claim 1 , wherein the method further comprises: determining a value of the worst-case time complexity of the backref-regex based on the determined maximum number; and providing the determined worst-case time complexity value. | 0.885957 |
9,331,965 | 1 | 10 | 1. A system for automatic generation of subject lines for electronic mail (email), comprising: a memory, and at least one processor operatively coupled to the memory; an extraction module executed via the at least one processor and capable of extracting topics from an email message; a prioritization module executed via the at least one processor and capable of computing a sender relevance score for each topic, and ranking the topics based on the sender relevance scores; a sorting module executed via the at least one processor and capable of ranking a plurality of syntactic units from the email message based on the topic ranking; and an assignment module executed via the at least one processor and capable of assigning one or more subject lines to the email message based on the ranking of the syntactic units; wherein the assignment module is further capable of: assigning different subject lines to the email message for each respective intended recipient of a plurality of intended recipients of the email message so that each respective intended recipient is sent the same email message with a different subject line from that of other intended recipients, wherein the different subject line corresponding to an intended recipient is determined based on one or more characteristics of the intended recipient; and assigning an identifying subject line different from the one or more of the subject lines assigned to the email message, the identifying subject line indicating one or more preferences of a sender of the email message and being visible to the sender and not visible to a recipient of the email message; wherein, when the sender receives a reply to the email message from the recipient, the reply email message includes the identifying subject line instead of the one or more of the subject lines assigned to the email message, or a combination of the identifying subject line and the one or more of the subject lines assigned to the email message. | 1. A system for automatic generation of subject lines for electronic mail (email), comprising: a memory, and at least one processor operatively coupled to the memory; an extraction module executed via the at least one processor and capable of extracting topics from an email message; a prioritization module executed via the at least one processor and capable of computing a sender relevance score for each topic, and ranking the topics based on the sender relevance scores; a sorting module executed via the at least one processor and capable of ranking a plurality of syntactic units from the email message based on the topic ranking; and an assignment module executed via the at least one processor and capable of assigning one or more subject lines to the email message based on the ranking of the syntactic units; wherein the assignment module is further capable of: assigning different subject lines to the email message for each respective intended recipient of a plurality of intended recipients of the email message so that each respective intended recipient is sent the same email message with a different subject line from that of other intended recipients, wherein the different subject line corresponding to an intended recipient is determined based on one or more characteristics of the intended recipient; and assigning an identifying subject line different from the one or more of the subject lines assigned to the email message, the identifying subject line indicating one or more preferences of a sender of the email message and being visible to the sender and not visible to a recipient of the email message; wherein, when the sender receives a reply to the email message from the recipient, the reply email message includes the identifying subject line instead of the one or more of the subject lines assigned to the email message, or a combination of the identifying subject line and the one or more of the subject lines assigned to the email message. 10. The system according to claim 1 , wherein the assignment module is further capable of assigning a plurality of the subject lines to the email message to be visible to an intended recipient in a configuration for displaying the plurality of the subject lines. | 0.65974 |
7,885,987 | 34 | 38 | 34. A system, implemented on at least one computer, for managing a plurality of attributes in association with a plurality of electronic documents and a plurality of attribute types, said system comprising: (A) means, in the at least one computer, for providing a first data storage having a group of a plurality of documents including at least one document; (B) means, in the at least one computer, for accepting, from an input device, a user's selection of a plurality of attributes to be associated with a single pre-determined attribute type for the at least one document, the attribute type having parent and child attribute types, the selected attributes being predetermined and having different parent attributes, attribute types being predetermined and ordered in a predetermined tree-structure hierarchy; and (C) means, in the at least one computer, responsive to the selection of the attributes, for automatically tagging, in the first data storage, the documents in the group including the at least one document, with the selected attributes, and with all attributes of all ancestors but not descendants or siblings according to the hierarchy of the selected attributes; and storing, in a second data storage, respective references in association with the selected attributes and the ancestor attributes, for later retrieval of individual documents in the group by searching the ancestor attributes instead of the selected attributes, the respective references uniquely indicating respective individual documents in the first data storage; (D) wherein the at least one document and the at least one other document are representative of at least one of: an invention disclosure document, a patent document, a trademark document, a copyright document, a product description document, a contract document, a license document, a sui generis protection document, a design registration document, a trade secret document, and an opinion document, wherein a document is a data record including a plurality of fields, wherein the attribute and the attribute type are different from the fields in the document and contents of the fields. | 34. A system, implemented on at least one computer, for managing a plurality of attributes in association with a plurality of electronic documents and a plurality of attribute types, said system comprising: (A) means, in the at least one computer, for providing a first data storage having a group of a plurality of documents including at least one document; (B) means, in the at least one computer, for accepting, from an input device, a user's selection of a plurality of attributes to be associated with a single pre-determined attribute type for the at least one document, the attribute type having parent and child attribute types, the selected attributes being predetermined and having different parent attributes, attribute types being predetermined and ordered in a predetermined tree-structure hierarchy; and (C) means, in the at least one computer, responsive to the selection of the attributes, for automatically tagging, in the first data storage, the documents in the group including the at least one document, with the selected attributes, and with all attributes of all ancestors but not descendants or siblings according to the hierarchy of the selected attributes; and storing, in a second data storage, respective references in association with the selected attributes and the ancestor attributes, for later retrieval of individual documents in the group by searching the ancestor attributes instead of the selected attributes, the respective references uniquely indicating respective individual documents in the first data storage; (D) wherein the at least one document and the at least one other document are representative of at least one of: an invention disclosure document, a patent document, a trademark document, a copyright document, a product description document, a contract document, a license document, a sui generis protection document, a design registration document, a trade secret document, and an opinion document, wherein a document is a data record including a plurality of fields, wherein the attribute and the attribute type are different from the fields in the document and contents of the fields. 38. The system of claim 34 , further comprising utilizing the attributes as criteria for at least one of searching, retrieving, reporting, and viewing the at least one document. | 0.861068 |
9,305,226 | 5 | 6 | 5. A method, comprising: obtaining an image including text; processing the image with a text recognition algorithm to produce text string data, the text string data including a first option for a first portion of the text string and a second option for the first portion, the first option having a first confidence value and the second option having a second confidence value; processing the text string data using a rule decision tree that has a plurality of hierarchical nodes, including a first hierarchical node corresponding to a semantic boosting rule, wherein processing the text string using the rule decision tree includes, for at least the first hierarchical node: determining that a pre-condition is satisfied for the semantic boosting rule with respect to the text string; applying the semantic boosting rule to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing at least one of the first confidence value or the second confidence value to generate a refined text string; and providing the refined text string as recognized text for the image. | 5. A method, comprising: obtaining an image including text; processing the image with a text recognition algorithm to produce text string data, the text string data including a first option for a first portion of the text string and a second option for the first portion, the first option having a first confidence value and the second option having a second confidence value; processing the text string data using a rule decision tree that has a plurality of hierarchical nodes, including a first hierarchical node corresponding to a semantic boosting rule, wherein processing the text string using the rule decision tree includes, for at least the first hierarchical node: determining that a pre-condition is satisfied for the semantic boosting rule with respect to the text string; applying the semantic boosting rule to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing at least one of the first confidence value or the second confidence value to generate a refined text string; and providing the refined text string as recognized text for the image. 6. The method of claim 5 , further comprising: determining that the text string is the refined text string in response to at least one of an overall confidence value for the text string data being equal to, or greater than, a minimum confidence value or each applicable rule of the decision tree being applied to the text string data. | 0.728455 |
9,786,199 | 14 | 17 | 14. A method comprising: providing text, via one or more networks, to a computing device, the text configured to be output as a guide to a user to speak one or more words of a language as part of a language learning session; receiving, from the computing device, recorded speech data representative of a recognition of the one or more words spoken by the user; generating, based at least in part on the recorded speech data, one or more confidence values, wherein an individual confidence value indicates a likelihood that a correspondence between at least one word spoken by the user and at least part of the text was correctly recognized; and analyzing the one or more confidence values to calculate a performance evaluation for the language learning session. | 14. A method comprising: providing text, via one or more networks, to a computing device, the text configured to be output as a guide to a user to speak one or more words of a language as part of a language learning session; receiving, from the computing device, recorded speech data representative of a recognition of the one or more words spoken by the user; generating, based at least in part on the recorded speech data, one or more confidence values, wherein an individual confidence value indicates a likelihood that a correspondence between at least one word spoken by the user and at least part of the text was correctly recognized; and analyzing the one or more confidence values to calculate a performance evaluation for the language learning session. 17. The method of claim 14 , wherein the correspondence between the at least one word spoken by the user and the at least part of the text comprises a temporal correspondence based at least in part on a time when the at least one word was spoken and a time when the at least part of the text was output. | 0.719963 |
7,680,773 | 7 | 8 | 7. The method of claim 6 , wherein the significance analysis of a respective URL parameter further includes: removing the respective URL parameter from each document identifier associated with the cluster, each document identifier having a document identifier remainder; grouping the document identifiers into multiple sets, each set having a distinct document identifier remainder; and summing up the number of distinct document contents within each set that has at least two different document contents as the URL parameter's significance index. | 7. The method of claim 6 , wherein the significance analysis of a respective URL parameter further includes: removing the respective URL parameter from each document identifier associated with the cluster, each document identifier having a document identifier remainder; grouping the document identifiers into multiple sets, each set having a distinct document identifier remainder; and summing up the number of distinct document contents within each set that has at least two different document contents as the URL parameter's significance index. 8. The method of claim 7 , further including a numeric significance threshold, wherein the respective URL parameter is classified as content-irrelevant if its significance index is less than the significance threshold. | 0.930083 |
8,731,919 | 12 | 17 | 12. A computer-implemented method for capturing voice files and rendering them searchable, comprising the steps of: (a) recording audio speech data for a conversation between two or more participants, said audio speech data obtained from at least one audio-capable device; (b) storing the audio speech data in a database system; (c) selecting and loading into a speech recognition engine a grammar selected from a plurality of stored grammars, wherein said grammar is selected prior to the transcribing step and is selected on the basis of information pertaining to the subject matter or purpose of the conversation, and the identity of one or more of the participants; (d) transcribing the audio speech data into machine-readable text data using the speech recognition engine employing said grammar; (e) creating at least one data element associating the machine-readable text data with the corresponding audio speech data; (f) storing the machine-readable text data and the associated data element in a searchable database; and (f) revising the machine-readable text data by performing a subsequent transcription pass on the audio speech data using another grammar which is different than the previously selected grammar. | 12. A computer-implemented method for capturing voice files and rendering them searchable, comprising the steps of: (a) recording audio speech data for a conversation between two or more participants, said audio speech data obtained from at least one audio-capable device; (b) storing the audio speech data in a database system; (c) selecting and loading into a speech recognition engine a grammar selected from a plurality of stored grammars, wherein said grammar is selected prior to the transcribing step and is selected on the basis of information pertaining to the subject matter or purpose of the conversation, and the identity of one or more of the participants; (d) transcribing the audio speech data into machine-readable text data using the speech recognition engine employing said grammar; (e) creating at least one data element associating the machine-readable text data with the corresponding audio speech data; (f) storing the machine-readable text data and the associated data element in a searchable database; and (f) revising the machine-readable text data by performing a subsequent transcription pass on the audio speech data using another grammar which is different than the previously selected grammar. 17. The method of claim 12 , wherein said audio speech data is stored in the database system as a plurality of files, with each file associated with a different participant. | 0.876956 |
8,312,057 | 23 | 27 | 23. A machine accessible medium having instructions stored thereon that, when executed, cause a machine to: receive a voice input from a source during a first encounter; determine an identity of the source; perform a speech-to-text conversion on the voice input to generate a text string representing the voice input; associate the text string with the identity of the source; automatically identify and select one or more keywords from the text string, wherein the one or more keywords are associated with one or more data fields; and automatically populate the one or more data fields with the identified keywords according to values associated with the identified keywords and the identity of the source, the populated one or more data fields to be different than the text string. | 23. A machine accessible medium having instructions stored thereon that, when executed, cause a machine to: receive a voice input from a source during a first encounter; determine an identity of the source; perform a speech-to-text conversion on the voice input to generate a text string representing the voice input; associate the text string with the identity of the source; automatically identify and select one or more keywords from the text string, wherein the one or more keywords are associated with one or more data fields; and automatically populate the one or more data fields with the identified keywords according to values associated with the identified keywords and the identity of the source, the populated one or more data fields to be different than the text string. 27. The machine accessible medium as defined in claim 23 having instructions stored there on that, when executed, cause the machine to visually represent that the text string is associated with the identity of the source. | 0.732446 |
7,904,445 | 9 | 10 | 9. The system of claim 8 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms. | 9. The system of claim 8 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms. 10. The system of claim 9 wherein the one or more relationships are established using a cluster analysis. | 0.974988 |
8,005,823 | 11 | 12 | 11. The method of claim 10 , further comprising receiving user feedback regarding the modified results from the community member, wherein the feedback specifies a level of correctness for at least one of the results, and wherein the feedback comprises feedback explicitly indicated by the community member selecting a positive or negative indication from among a plurality of indications. | 11. The method of claim 10 , further comprising receiving user feedback regarding the modified results from the community member, wherein the feedback specifies a level of correctness for at least one of the results, and wherein the feedback comprises feedback explicitly indicated by the community member selecting a positive or negative indication from among a plurality of indications. 12. The method of claim 11 , further comprising modifying the results according to the received user feedback. | 0.972826 |
9,098,808 | 15 | 18 | 15. The system of claim 10 wherein the operations further comprise: associating one or more topics with the user by analyzing text associated with the user and with others in a social affinity group of the user; and determining a probability distribution for the topics based on expertise in the topics of the user and the others. | 15. The system of claim 10 wherein the operations further comprise: associating one or more topics with the user by analyzing text associated with the user and with others in a social affinity group of the user; and determining a probability distribution for the topics based on expertise in the topics of the user and the others. 18. The system of claim 15 wherein the operations further comprise disassociating a topic in the one or more topics with the user if one or more of the following conditions holds true: the user mutes the topic, the user declines to answer a question about the topic, and the user receives negative feedback on an answer about the topic from another user. | 0.886027 |
7,689,033 | 49 | 50 | 49. The computer-readable medium as recited in claim 48 , wherein the SVM filter process is configured to reduce redundancy in a feature space associated with at least one intermediate candidate portion, and performs wavelet transformation of the at least one intermediate candidate portion to produce a plurality of sub-bands portions. | 49. The computer-readable medium as recited in claim 48 , wherein the SVM filter process is configured to reduce redundancy in a feature space associated with at least one intermediate candidate portion, and performs wavelet transformation of the at least one intermediate candidate portion to produce a plurality of sub-bands portions. 50. The computer-readable medium as recited in claim 49 , further comprising selectively cropping at least one of the plurality of sub-band portions. | 0.937025 |
8,666,727 | 11 | 16 | 11. A method for the voice-controlled selection of a media file stored on a data storage unit, the data storage unit including a plurality of media files, the media files including respective file identification data, the method comprising: receiving voice data indicative of selection of the media file from among the media files, and supplying the voice data to a speech recognition unit; extracting, by a processor, a first language identification tag included in the respective file identification data of each of the media files, the first language identification tag indicating a first language associated with a first data field of the respective file identification data, where the respective file identification data is in a header section of each of the respective media files; extracting, by the processor, a second language identification tag included in the respective file identification data of each of the media file, the second language identification tag indicating a second language associated with a second data field of the respective file identification data in the header section of each of the respective media files; generating, by the processor, phonetic data corresponding to the file identification data for each of the media files, the generated phonetic data comprising phonetic representations of the first data field and the second data field that are generated based on the first language identification tag and the second language identification tag, respectively; comparing, by the processor, the generated phonetic data to the received voice data by the speech recognition unit and generating a corresponding speech control command; and selecting, by the processor, the media file from the data storage unit in accordance with the generated speech control command. | 11. A method for the voice-controlled selection of a media file stored on a data storage unit, the data storage unit including a plurality of media files, the media files including respective file identification data, the method comprising: receiving voice data indicative of selection of the media file from among the media files, and supplying the voice data to a speech recognition unit; extracting, by a processor, a first language identification tag included in the respective file identification data of each of the media files, the first language identification tag indicating a first language associated with a first data field of the respective file identification data, where the respective file identification data is in a header section of each of the respective media files; extracting, by the processor, a second language identification tag included in the respective file identification data of each of the media file, the second language identification tag indicating a second language associated with a second data field of the respective file identification data in the header section of each of the respective media files; generating, by the processor, phonetic data corresponding to the file identification data for each of the media files, the generated phonetic data comprising phonetic representations of the first data field and the second data field that are generated based on the first language identification tag and the second language identification tag, respectively; comparing, by the processor, the generated phonetic data to the received voice data by the speech recognition unit and generating a corresponding speech control command; and selecting, by the processor, the media file from the data storage unit in accordance with the generated speech control command. 16. The method of claim 11 , further comprising transferring the selected media file to a media file player where the selected media file is reproducible. | 0.772189 |
8,521,739 | 11 | 17 | 11. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: determining prefixes, infixes and postfixes of unique queries in a log of past queries submitted to one or more search engines, wherein an infix of a particular unique query is a sequence of one or more terms occurring between a prefix at a beginning of the particular unique query and a postfix at an end of the particular query; identifying a plurality of groups of queries, wherein the queries in each group have matching prefixes, matching postfixes and different infixes; forming for each group of queries a respective query template by selecting the matched prefix and the matched postfix of the queries in the group; reformulating the query templates into corresponding canonical representations using canonicalization rules; identifying a first group of queries in the plurality of groups of queries that has a query template canonical representation matching that of a second group of queries in the plurality of groups of queries; identifying candidate phrases based at least in part on similarity scores between the infixes of the queries in the second group and the candidate phrases; selecting infixes of one or more queries in the first group of queries, wherein selecting the infixes of queries in the first group includes creating a list of the candidate phrases based on the similarity scores between the infixes of the queries in the second group and the candidate phrases, and selecting only infixes of queries in the first group which appear in the list of candidate phrases; creating one or more inferred queries by adding the selected infixes to the query template of the second group of queries; and storing the inferred queries for use as query suggestions. | 11. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: determining prefixes, infixes and postfixes of unique queries in a log of past queries submitted to one or more search engines, wherein an infix of a particular unique query is a sequence of one or more terms occurring between a prefix at a beginning of the particular unique query and a postfix at an end of the particular query; identifying a plurality of groups of queries, wherein the queries in each group have matching prefixes, matching postfixes and different infixes; forming for each group of queries a respective query template by selecting the matched prefix and the matched postfix of the queries in the group; reformulating the query templates into corresponding canonical representations using canonicalization rules; identifying a first group of queries in the plurality of groups of queries that has a query template canonical representation matching that of a second group of queries in the plurality of groups of queries; identifying candidate phrases based at least in part on similarity scores between the infixes of the queries in the second group and the candidate phrases; selecting infixes of one or more queries in the first group of queries, wherein selecting the infixes of queries in the first group includes creating a list of the candidate phrases based on the similarity scores between the infixes of the queries in the second group and the candidate phrases, and selecting only infixes of queries in the first group which appear in the list of candidate phrases; creating one or more inferred queries by adding the selected infixes to the query template of the second group of queries; and storing the inferred queries for use as query suggestions. 17. The non-transitory computer readable storage medium of claim 11 , wherein the canonicalization rules include stemming of terms in the query templates. | 0.818824 |
8,619,316 | 11 | 12 | 11. The apparatus according to claim 7 , further comprising: a storage unit to store the generated key index in an image file format separately from the scanned document, or in a header area of the scanned document in an image file format. | 11. The apparatus according to claim 7 , further comprising: a storage unit to store the generated key index in an image file format separately from the scanned document, or in a header area of the scanned document in an image file format. 12. The apparatus according to claim 11 , further comprising: a user interface (UI) unit to enlarge and display at least one of the stored key index and an image area of the scanned document if an event to search for the scanned document occurs. | 0.856725 |
8,266,594 | 1 | 5 | 1. A method for correcting semantic errors in code in an integrated development environment, said method comprising: inputting, using a code editor, code being developed in an integrated development environment; identifying, in a syntax tree constructed for said code inputted, one or more nodes containing semantic errors pertaining to use of a third-party library; choosing a node of said one or more nodes identified in said syntax tree constructed containing said semantic errors; displaying multiple suggestions for correcting said semantic errors identified for said node chosen, wherein each of said multiple suggestions include one or more executable code snippets associated with one or more collaboration records located for said node chosen, and wherein said one or more executable code snippets are submitted by peer developers to correct said semantic errors identified for said node chosen; displaying an executable code snippet configuration interface for configuring said one or more executable code snippets, wherein the executable code snippet configuration interface comprises: an input parameter active field for identifying input parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an output parameter active field for identifying output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an input/output parameter active field for identifying input/output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; and a return value active field for identifying a return value that is required, by said node chosen, to be returned by said one or more executable code snippets; selecting at least one executable code snippet from said one or more executable code snippets displayed for correcting said semantic errors identified for said node chosen; and executing said code inputted in said integrated development environment, wherein said at least one executable code snippet has been previously collected by said integrated development environment, and wherein said at least one executable code snippet selected is automatically invoked to correct said semantic errors identified for said node chosen. | 1. A method for correcting semantic errors in code in an integrated development environment, said method comprising: inputting, using a code editor, code being developed in an integrated development environment; identifying, in a syntax tree constructed for said code inputted, one or more nodes containing semantic errors pertaining to use of a third-party library; choosing a node of said one or more nodes identified in said syntax tree constructed containing said semantic errors; displaying multiple suggestions for correcting said semantic errors identified for said node chosen, wherein each of said multiple suggestions include one or more executable code snippets associated with one or more collaboration records located for said node chosen, and wherein said one or more executable code snippets are submitted by peer developers to correct said semantic errors identified for said node chosen; displaying an executable code snippet configuration interface for configuring said one or more executable code snippets, wherein the executable code snippet configuration interface comprises: an input parameter active field for identifying input parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an output parameter active field for identifying output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; an input/output parameter active field for identifying input/output parameters that are required, by said node chosen, to be used with said one or more executable code snippets; and a return value active field for identifying a return value that is required, by said node chosen, to be returned by said one or more executable code snippets; selecting at least one executable code snippet from said one or more executable code snippets displayed for correcting said semantic errors identified for said node chosen; and executing said code inputted in said integrated development environment, wherein said at least one executable code snippet has been previously collected by said integrated development environment, and wherein said at least one executable code snippet selected is automatically invoked to correct said semantic errors identified for said node chosen. 5. The method according to claim 1 , wherein said selecting further comprises: providing an executable code snippet processor for maintaining said one or more executable code snippets associated with said one or more collaboration records located for said node chosen; and configuring one or more parameters for said at least one executable code snippet selected for said node chosen, wherein said one or more parameters comprises at least one of: input parameters, output parameters, input-output parameters, return values and execution order values. | 0.737619 |
8,296,290 | 19 | 20 | 19. A system for propagating classification decisions, comprising: text marked within one or more unclassified documents that is responsive to a predetermined issue, wherein the one or more unclassified documents are selected from a corpus of unclassified documents; a query generator to generate a search query from the responsive text and to identify result documents, comprising: a same search module to identify same result documents by applying inclusive search parameters to the query, by applying the search query to the corpus, and by identifying the documents that satisfy the query as the same result documents; and a similar search module to identify similar result documents from the corpus by adjusting a breath of the query by applying less inclusive search parameters and by identifying documents from the corpus that satisfy the query as the similar result documents; a propagator to automatically assign a responsive classification code to the same result documents for classification as responsive documents; a document feeder to provide the similar documents to the user and to receive a responsive classification decision from the user for at least one of the similar documents for classification as the responsive documents; a validation module to provide a number of the unclassified documents remaining in the corpus for further review, wherein the number of remaining unclassified documents is determined in accordance with the equation: M = x b where b is an upper bound value representing a percentage of the unclassified documents remaining in the corpus that are responsive and x is an integer that is determined based on a desired confidence level that all the responsive documents are identified; and a processor to execute the modules, the query generator, the propagator, and the document feeder. | 19. A system for propagating classification decisions, comprising: text marked within one or more unclassified documents that is responsive to a predetermined issue, wherein the one or more unclassified documents are selected from a corpus of unclassified documents; a query generator to generate a search query from the responsive text and to identify result documents, comprising: a same search module to identify same result documents by applying inclusive search parameters to the query, by applying the search query to the corpus, and by identifying the documents that satisfy the query as the same result documents; and a similar search module to identify similar result documents from the corpus by adjusting a breath of the query by applying less inclusive search parameters and by identifying documents from the corpus that satisfy the query as the similar result documents; a propagator to automatically assign a responsive classification code to the same result documents for classification as responsive documents; a document feeder to provide the similar documents to the user and to receive a responsive classification decision from the user for at least one of the similar documents for classification as the responsive documents; a validation module to provide a number of the unclassified documents remaining in the corpus for further review, wherein the number of remaining unclassified documents is determined in accordance with the equation: M = x b where b is an upper bound value representing a percentage of the unclassified documents remaining in the corpus that are responsive and x is an integer that is determined based on a desired confidence level that all the responsive documents are identified; and a processor to execute the modules, the query generator, the propagator, and the document feeder. 20. A system according to claim 19 , further comprising: a document selection module to randomly select the M remaining unclassified documents for review. | 0.877583 |
9,747,264 | 1 | 6 | 1. A method comprising: receiving, by one or more processors, a pending update list including a first plurality of items, wherein each item of the first plurality of items describes an update to a hierarchically structured document; adding, by one or more processors, each of one or more items of the first plurality of items to a subsumed update list having a second plurality of items, wherein the subsumed update list is ordered based, at least in part, on a document order and on a target node of each of the second plurality of items; applying, by one or more processors, subsume logic to each of the one or more items based, at least in part, on the second plurality of items, wherein applying the subsume logic to each of the one or more items pre-processes the pending update list, thereby consolidating redundant updates and removing conflicting updates; comparing, by one or more processors, a first target node of a first item of the one or more items to a second target node of a second item of the second plurality of items, wherein the second item is a tail of the subsumed update list; responsive to determining, by one or more processors, that the first target node is the same as or is a descendant of the second target node, applying, by one or more processors, the subsume logic to the first item based, at least in part, on at least one subsume matrix; and responsive to determining, by one or more processors, that the subsume logic has been applied to each item of the first plurality of items, executing, by one or more processors, each of the second plurality of items of the subsumed update list. | 1. A method comprising: receiving, by one or more processors, a pending update list including a first plurality of items, wherein each item of the first plurality of items describes an update to a hierarchically structured document; adding, by one or more processors, each of one or more items of the first plurality of items to a subsumed update list having a second plurality of items, wherein the subsumed update list is ordered based, at least in part, on a document order and on a target node of each of the second plurality of items; applying, by one or more processors, subsume logic to each of the one or more items based, at least in part, on the second plurality of items, wherein applying the subsume logic to each of the one or more items pre-processes the pending update list, thereby consolidating redundant updates and removing conflicting updates; comparing, by one or more processors, a first target node of a first item of the one or more items to a second target node of a second item of the second plurality of items, wherein the second item is a tail of the subsumed update list; responsive to determining, by one or more processors, that the first target node is the same as or is a descendant of the second target node, applying, by one or more processors, the subsume logic to the first item based, at least in part, on at least one subsume matrix; and responsive to determining, by one or more processors, that the subsume logic has been applied to each item of the first plurality of items, executing, by one or more processors, each of the second plurality of items of the subsumed update list. 6. The method of claim 1 , wherein the hierarchically structured document is an extended markup language document. | 0.947898 |
7,565,607 | 20 | 21 | 20. A computer readable storage medium storing instructions which, when read by a computer, cause the computer to perform a method of generating content indicating the progressive steps to be taken on a user interface to perform a task, the method comprising: detecting a user manipulation of an element on a user interface; and recording, in response to the user manipulation, an image from the user interface indicative of the element; recording separately a context image showing at least a portion of a context of the element with respect to the user interface; recording separately an image of a parent window of the element on the user interface; displaying the recorded image of the element, the context image, and the image of the parent window on an editor component configured to automatically receive and edit a pre-associated textual description of the user manipulation of the element for each image indicating a step to be taken on a user interface to perform a task; repeating the above steps for user manipulation of at least another element; generating content describing the progressive steps to be taken to perform a task on the user interface, with the image of the control, the contextual image, and the image of the parent window separately embedded in the corresponding pre-associated textual description. | 20. A computer readable storage medium storing instructions which, when read by a computer, cause the computer to perform a method of generating content indicating the progressive steps to be taken on a user interface to perform a task, the method comprising: detecting a user manipulation of an element on a user interface; and recording, in response to the user manipulation, an image from the user interface indicative of the element; recording separately a context image showing at least a portion of a context of the element with respect to the user interface; recording separately an image of a parent window of the element on the user interface; displaying the recorded image of the element, the context image, and the image of the parent window on an editor component configured to automatically receive and edit a pre-associated textual description of the user manipulation of the element for each image indicating a step to be taken on a user interface to perform a task; repeating the above steps for user manipulation of at least another element; generating content describing the progressive steps to be taken to perform a task on the user interface, with the image of the control, the contextual image, and the image of the parent window separately embedded in the corresponding pre-associated textual description. 21. The computer readable storage medium of claim 20 wherein detecting comprises: identifying a size and position of the element. | 0.656915 |
8,238,666 | 1 | 4 | 1. A method of creating a document comprising a modifiable shape, the method comprising the steps of: analysing an image to detect at least a graphical object; matching the detected graphical object with at least one of a plurality of predetermined modifiable closed-form non-textual template shapes, each said predetermined template shape comprising at least one control parameter for modifying the closed-form non-textual template shape in a non-affine manner, wherein the number of control parameters of the predetermined modifiable closed-form non-textual template shape is less than a number of sections making up the modifiable closed-form non-textual template shape; and creating a document comprising the at least one modifiable closed-form non-textual template shape. | 1. A method of creating a document comprising a modifiable shape, the method comprising the steps of: analysing an image to detect at least a graphical object; matching the detected graphical object with at least one of a plurality of predetermined modifiable closed-form non-textual template shapes, each said predetermined template shape comprising at least one control parameter for modifying the closed-form non-textual template shape in a non-affine manner, wherein the number of control parameters of the predetermined modifiable closed-form non-textual template shape is less than a number of sections making up the modifiable closed-form non-textual template shape; and creating a document comprising the at least one modifiable closed-form non-textual template shape. 4. The method according to claim 1 , the matching step comprises the sub-steps of: estimating an optimal set of control parameters; estimating an optimal set of affine parameters based on said graphical object and said estimated control parameters; and computing a match score between said graphical object and said template shape wherein said template shape uses said estimated affine parameters and said control parameters. | 0.501174 |
8,543,378 | 9 | 12 | 9. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a first and a last consonant in the misspelled entry with a first and a last consonant in a selected term. | 9. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a first and a last consonant in the misspelled entry with a first and a last consonant in a selected term. 12. The computer readable-media as recited in claim 9 , wherein the filtering process considers one or more consonants that are omittable from a start or end of the misspelled entry. | 0.910345 |
8,756,258 | 15 | 16 | 15. A system, comprising: a memory; a model generator executed in the memory to perform operations, the operations comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; processing the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; and generating a reference in the data structure schema to the reusable code. | 15. A system, comprising: a memory; a model generator executed in the memory to perform operations, the operations comprising: providing a program coded in a first programming language having data structures, wherein at least one of the data structures includes a reference to reusable code; generating a model file identifying the reusable code, elements and attributes in a second programming language for the reference to the reusable code in the program; processing the data structure coded in the first programming language to generate a data structure schema in a second programming language describing elements and attributes of the data structure coded in the first programming language; and generating a reference in the data structure schema to the reusable code. 16. The system of claim 15 , wherein the reference generated in the data structure schema includes the element and attribute information indicated in the model file. | 0.903958 |
8,156,062 | 3 | 4 | 3. The method as claimed in claim 1 , wherein the U-Health ontologies comprise: a disease ontology in which information on kinds of disease is defined, a symptom ontology in which information on symptoms caused by diseases is defined, an environment ontology in which information on environments of a person targeted for disease deduction is defined, and a treatment ontology in which treatment methods for diseases are defined. | 3. The method as claimed in claim 1 , wherein the U-Health ontologies comprise: a disease ontology in which information on kinds of disease is defined, a symptom ontology in which information on symptoms caused by diseases is defined, an environment ontology in which information on environments of a person targeted for disease deduction is defined, and a treatment ontology in which treatment methods for diseases are defined. 4. The method as claimed in claim 3 , wherein the U-Health ontologies further comprises: user information ontology, including age, sex, family disease history, and biological signals. | 0.92615 |
5,473,705 | 1 | 14 | 1. A sign language translation system, comprising: input means for inputting motion of hands as electric signals; sign language word generating means for recognizing words in accordance with said input electric signals and generating sign language words; storage means for storing conjugations or translations of said generated sign language words and postpositions or auxiliary verbs to be supplemented between said generated sign language words; dependence analyzing means for analyzing a dependence relationship between successive ones of said recognized words in accordance with said stored translations of said recognized words and outputting analyzed results; spoken language generating means for generating, in accordance with said analyzed results, an audibly communicated sentence by supplementing said stored postpositions or auxiliary verbs and providing said stored conjugations of conjugative words; and output means for outputting said generated spoken language. | 1. A sign language translation system, comprising: input means for inputting motion of hands as electric signals; sign language word generating means for recognizing words in accordance with said input electric signals and generating sign language words; storage means for storing conjugations or translations of said generated sign language words and postpositions or auxiliary verbs to be supplemented between said generated sign language words; dependence analyzing means for analyzing a dependence relationship between successive ones of said recognized words in accordance with said stored translations of said recognized words and outputting analyzed results; spoken language generating means for generating, in accordance with said analyzed results, an audibly communicated sentence by supplementing said stored postpositions or auxiliary verbs and providing said stored conjugations of conjugative words; and output means for outputting said generated spoken language. 14. A sign language translation system according to claim 1, wherein said output means outputs synthesized images of the hand motion corresponding to a sign language wherein the dependence between said recognized words is analyzed using said recognized results, and a predetermined process is executed using said analyzed results to generate said spoken language by supplementing omitted words and providing the conjugations of a conjugative word. | 0.671324 |
8,060,492 | 4 | 6 | 4. The method of claim 1 wherein the at least one query generation criteria comprises at least one seed value for query generation. | 4. The method of claim 1 wherein the at least one query generation criteria comprises at least one seed value for query generation. 6. The method of claim 4 wherein the at least one seed value for query generation comprises a result set of the context query, wherein the result set of the context query comprises at least one reference to a data object. | 0.957533 |
8,868,555 | 1 | 2 | 1. An apparatus for generating a recognizability score, the apparatus comprising: a vector calculator for determining a plurality of quality feature vectors from an input image to measure distortion of the input image including blurriness and coding artifacts and to determine whether the input image is stable to the distortion by applying different levels of the distortion to the input image, measuring distances between the input image and the distorted images and determining whether a combination of the distances is small, the vector calculator adapted for communication to receive the input image; a score generator for generating a recognition score for each of the quality feature vectors, the score generator adapted to receive the quality feature vectors from the vector calculator; and a scoring module for determining recognition results, generating the recognizability score from the recognition scores, generating a confidence score for each recognition result that reflects a confidence in the recognition result based on the recognizability score and merging and sorting the recognition results to produce one or more top results using the confidence scores, the scoring module adapted to communicate with the score generator to receive the recognition scores. | 1. An apparatus for generating a recognizability score, the apparatus comprising: a vector calculator for determining a plurality of quality feature vectors from an input image to measure distortion of the input image including blurriness and coding artifacts and to determine whether the input image is stable to the distortion by applying different levels of the distortion to the input image, measuring distances between the input image and the distorted images and determining whether a combination of the distances is small, the vector calculator adapted for communication to receive the input image; a score generator for generating a recognition score for each of the quality feature vectors, the score generator adapted to receive the quality feature vectors from the vector calculator; and a scoring module for determining recognition results, generating the recognizability score from the recognition scores, generating a confidence score for each recognition result that reflects a confidence in the recognition result based on the recognizability score and merging and sorting the recognition results to produce one or more top results using the confidence scores, the scoring module adapted to communicate with the score generator to receive the recognition scores. 2. The apparatus of claim 1 wherein the vector calculator includes one from the group of a blur feature module, a content amount feature module, a luminosity feature module, a bleed through feature module, a coding artifacts feature module, a perspective distortion feature module, a camera noise feature module, a text quality feature module, an object detection feature module, a recognition algorithm feature module and a robustness feature module. | 0.65361 |
7,689,546 | 18 | 19 | 18. The search system of claim 13 , wherein the means for generating a search request performs the further function of editing the text of the headnote to generate the search request. | 18. The search system of claim 13 , wherein the means for generating a search request performs the further function of editing the text of the headnote to generate the search request. 19. The search system of claim 18 , wherein the means for generating a search request performs the further function of subjecting the text of the headnote to a phrase recognition process and identifying keywords in the headnote text, and edits the headnote text by applying rules to remove terms from the search request if the number of keywords identified in the headnote text is greater than a set threshold. | 0.909292 |
8,667,007 | 8 | 12 | 8. A computer program product for providing recommendations to improve a query, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category Levels; and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the calculated keyword relevance indicators, wherein the query relevance indicator is calculated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. | 8. A computer program product for providing recommendations to improve a query, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category Levels; and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the calculated keyword relevance indicators, wherein the query relevance indicator is calculated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. 12. The computer program product of claim 8 , wherein the computer readable program code, when executed by the processor of the computer, is configured to perform: identifying query keywords having low keyword relevance indicator values for non-top-ranked selected categories and having high keyword relevance indicator values for top-ranked, but un-selected categories; from the identified query keywords, identifying the query keywords for which synonyms are not identified; and providing a recommendation that the query keywords for which synonyms were not identified be removed from the query. | 0.513844 |
9,015,139 | 9 | 16 | 9. A search system for performing an image-based search, the system comprising: processing circuitry configured to: receive a snapshot image captured from video of media content being displayed by user equipment; and receive supplemental data associated with the media content; and searching circuitry responsive to the processing circuitry and configured to: retrieve a plurality of images from a collection of searchable data by comparing the supplemental data to data associated with each image of the plurality of images; process visual attributes of each image of the plurality of retrieved images to determine whether at least one image of the plurality of images includes at least one recognizable feature of the snapshot image; provide at least one first search result based on determining at least one image of the plurality of retrieved images has the at least one recognizable feature; receive a user request to refine the image-based search; process at least one new image based at least in part on the user request; and provide at least one second search result based on the at least one new image. | 9. A search system for performing an image-based search, the system comprising: processing circuitry configured to: receive a snapshot image captured from video of media content being displayed by user equipment; and receive supplemental data associated with the media content; and searching circuitry responsive to the processing circuitry and configured to: retrieve a plurality of images from a collection of searchable data by comparing the supplemental data to data associated with each image of the plurality of images; process visual attributes of each image of the plurality of retrieved images to determine whether at least one image of the plurality of images includes at least one recognizable feature of the snapshot image; provide at least one first search result based on determining at least one image of the plurality of retrieved images has the at least one recognizable feature; receive a user request to refine the image-based search; process at least one new image based at least in part on the user request; and provide at least one second search result based on the at least one new image. 16. The system of claim 9 wherein: the processing circuitry is further configured to determine a user's location; and the searching circuitry is further configured to provide search results related to the user's location. | 0.601083 |
7,849,030 | 26 | 31 | 26. The computer process of claim 25 wherein each concept contained in a vector forms a pattern. | 26. The computer process of claim 25 wherein each concept contained in a vector forms a pattern. 31. The computer process of claim 26 further including the step of pointing through a trace to a claim in which the phrases occur and linking them to the concepts that are indicative of a collection claim. | 0.899706 |
8,180,800 | 1 | 9 | 1. A method, including: using a data processor to receive context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services offered to purchasers in the network-based marketplace; automatically discovering context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services; associating the context data and the context attributes with a user identifier corresponding to the user; and generating result data associated with the context, the result data being relevant to the user identified by the user identifier. | 1. A method, including: using a data processor to receive context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services offered to purchasers in the network-based marketplace; automatically discovering context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services; associating the context data and the context attributes with a user identifier corresponding to the user; and generating result data associated with the context, the result data being relevant to the user identified by the user identifier. 9. The method of claim 1 , further including: associating an advertisement from a third party pertaining to a context; and providing the advertisement to a user interface of the user. | 0.799781 |
9,063,974 | 1 | 7 | 1. A machine-implemented method for processing a query, comprising: determining, by a microprocessor, that execution of the query involves a scan operation; in response to determining that execution of the query involves a scan operation, generating, by the microprocessor, a scan operation command that includes, as parameters of the scan operation command, address data that is used to identify input data to be read by a coprocessor and one or more values that are used to compare against the input data; wherein the microprocessor is separate from the coprocessor; causing, by the microprocessor, the scan operation command to be stored in memory; processing, by the coprocessor, the scan operation command by: reading the scan operation command from the memory; causing the input data to be read from a location that is indicated by the address data; performing a comparison between the input data with the one or more values; generating a result data based on the comparison; causing the result data to be stored. | 1. A machine-implemented method for processing a query, comprising: determining, by a microprocessor, that execution of the query involves a scan operation; in response to determining that execution of the query involves a scan operation, generating, by the microprocessor, a scan operation command that includes, as parameters of the scan operation command, address data that is used to identify input data to be read by a coprocessor and one or more values that are used to compare against the input data; wherein the microprocessor is separate from the coprocessor; causing, by the microprocessor, the scan operation command to be stored in memory; processing, by the coprocessor, the scan operation command by: reading the scan operation command from the memory; causing the input data to be read from a location that is indicated by the address data; performing a comparison between the input data with the one or more values; generating a result data based on the comparison; causing the result data to be stored. 7. The method of claim 1 , wherein causing the result data to be stored further comprises causing, to be stored, a completion status that indicates that the scan operation command has been performed. | 0.841812 |
7,642,932 | 5 | 6 | 5. The method according to claim 1 further comprising the step of mapping the second group by position information compatibility. | 5. The method according to claim 1 further comprising the step of mapping the second group by position information compatibility. 6. The method according to claim 5 wherein the keypad has above and below keys and all above vowels and diacritics are mapped to the keys in the above keys of the keypad, all below vowels and diacritics are mapped to the below keys of the keypad, and leading vowels are placed in front of following vowels. | 0.89048 |
8,996,564 | 4 | 5 | 4. The one or more computer-readable storage devices of claim 3 , wherein the first logical result, the second logical result, and the other logical results are Boolean values. | 4. The one or more computer-readable storage devices of claim 3 , wherein the first logical result, the second logical result, and the other logical results are Boolean values. 5. The one or more computer-readable storage devices of claim 4 , the acts further comprising parsing the data file in the first instance to identify XML tags delimiting the multiple other logic expressions that are included in the logic expression. | 0.943203 |
10,157,179 | 18 | 19 | 18. A non-transitory computer readable data storage memory storing computer-executable instructions that, when executed, cause a computer system to perform a computer-implemented method, the computer-implemented method comprising: providing a developer interface to enable selection of a property expression of a specific edge in a flexible sentence syntax, the flexible sentence syntax controlling how an application of a social networking system expresses edges in a social graph; and receiving a selection, via the developer interface, corresponding to reordering and/or inserting an element in any of a plurality of flexible sentence configurations, wherein the received selection causes the social graph to express a new edge representing a user action according to the flexible sentence syntax. | 18. A non-transitory computer readable data storage memory storing computer-executable instructions that, when executed, cause a computer system to perform a computer-implemented method, the computer-implemented method comprising: providing a developer interface to enable selection of a property expression of a specific edge in a flexible sentence syntax, the flexible sentence syntax controlling how an application of a social networking system expresses edges in a social graph; and receiving a selection, via the developer interface, corresponding to reordering and/or inserting an element in any of a plurality of flexible sentence configurations, wherein the received selection causes the social graph to express a new edge representing a user action according to the flexible sentence syntax. 19. The non-transitory computer readable data storage memory of claim 18 , wherein computer-implemented method further comprises: arranging and/or inserting the element in any of the plurality of flexible sentence configurations; and generating a sentence expression by extracting an edge or an object from a social graph relevant to the sentence configuration. | 0.628601 |
9,842,162 | 14 | 21 | 14. A method, comprising: identifying, in at least one computing device, a plurality of categories in a taxonomy of a collection of items by matching at least one term in a user-provided unstructured search query with metadata associated with respective categories in the taxonomy; identifying, in the at least one computing device, a refinement in the user-provided unstructured search query that is associated with at least one of the plurality of categories by translating at least one keyword from the user-provided unstructured search query into at least one criterion for selecting items from the at least one of the plurality of categories, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; generating, in the at least one computing device, a confidence score for individual categories of the plurality of categories based at least in part on a matching of at least a portion of the user-provided unstructured search query with data associated with the individual categories of the plurality of categories, individual confidence scores being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the user-provided unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the user-provided unstructured search query that are associated with the respective category, and the data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that the at least a portion of the user-provided unstructured search query occurs within the description; selecting, in the at least one computing device, a first pool of items from the one of the plurality of categories when the respective confidence score meets a threshold; selecting, in the at least one computing device, a second pool of items from the collection of items when no confidence score meets the threshold; and generating, in the at least one computing device, a network page listing at least a portion of the first pool of items or the second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, and the disambiguation tool providing a user interface for selecting one category from the plurality of categories. | 14. A method, comprising: identifying, in at least one computing device, a plurality of categories in a taxonomy of a collection of items by matching at least one term in a user-provided unstructured search query with metadata associated with respective categories in the taxonomy; identifying, in the at least one computing device, a refinement in the user-provided unstructured search query that is associated with at least one of the plurality of categories by translating at least one keyword from the user-provided unstructured search query into at least one criterion for selecting items from the at least one of the plurality of categories, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; generating, in the at least one computing device, a confidence score for individual categories of the plurality of categories based at least in part on a matching of at least a portion of the user-provided unstructured search query with data associated with the individual categories of the plurality of categories, individual confidence scores being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the user-provided unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the user-provided unstructured search query that are associated with the respective category, and the data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that the at least a portion of the user-provided unstructured search query occurs within the description; selecting, in the at least one computing device, a first pool of items from the one of the plurality of categories when the respective confidence score meets a threshold; selecting, in the at least one computing device, a second pool of items from the collection of items when no confidence score meets the threshold; and generating, in the at least one computing device, a network page listing at least a portion of the first pool of items or the second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, and the disambiguation tool providing a user interface for selecting one category from the plurality of categories. 21. The method of claim 14 , further comprising: receiving, in the at least one computing device, the user-provided unstructured search query from a client device; and parsing, in the at least one computing device, the user-provided unstructured search query to identify the at least one term. | 0.683585 |
9,396,192 | 11 | 14 | 11. A system for tagging a media asset, the system comprising: control circuitry configured to: receive a plurality of communications from a plurality of users, wherein each of the plurality of communications includes words spoken by a respective one of the users while accessing the media asset, and wherein each of the communications is associated with a media asset play position during which the respective words were spoken; select a subset of the plurality of communications for which the associated media asset play position is within a range of play positions, the range of play positions being shorter than a duration of the media asset; identify a word that a threshold number of the selected communications have in common; retrieve from an attribute database an attribute associated with the word; and assign the retrieved attribute to the media asset within the range of play positions. | 11. A system for tagging a media asset, the system comprising: control circuitry configured to: receive a plurality of communications from a plurality of users, wherein each of the plurality of communications includes words spoken by a respective one of the users while accessing the media asset, and wherein each of the communications is associated with a media asset play position during which the respective words were spoken; select a subset of the plurality of communications for which the associated media asset play position is within a range of play positions, the range of play positions being shorter than a duration of the media asset; identify a word that a threshold number of the selected communications have in common; retrieve from an attribute database an attribute associated with the word; and assign the retrieved attribute to the media asset within the range of play positions. 14. The system of claim 11 , wherein the control circuitry is further configured to: retrieve closed-captioning information corresponding to the range of play positions; identify a subject based on the retrieved closed-captioning information; and associate the attribute with the identified subject. | 0.501667 |
8,117,208 | 20 | 25 | 20. A method comprising: searching for qualifying occurrences of a query q consisting of at least one entity and at least one keyword from a database of linked documents, identifying entity tuples from the qualifying occurrences of the entity and keyword; for each instance of entity tuple q(t) in one document d of the documents, assigning a local score p(q(t)|d) based on a context of the entity in that document and an uncertainty value associated with extraction of the entity from that document; for each distinct entity tuple q(t), aggregating all the local scores thereof into a global score across the documents, based on respective weight p(d) assigned to each respective document d, as follow, p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; normalizing the aggregated score by statistically validating the significance of said score over the database; and outputting a relatively ranked listing of the normalized scores of at least a subset of the distinct entity tuples, to a storage or display device. | 20. A method comprising: searching for qualifying occurrences of a query q consisting of at least one entity and at least one keyword from a database of linked documents, identifying entity tuples from the qualifying occurrences of the entity and keyword; for each instance of entity tuple q(t) in one document d of the documents, assigning a local score p(q(t)|d) based on a context of the entity in that document and an uncertainty value associated with extraction of the entity from that document; for each distinct entity tuple q(t), aggregating all the local scores thereof into a global score across the documents, based on respective weight p(d) assigned to each respective document d, as follow, p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; normalizing the aggregated score by statistically validating the significance of said score over the database; and outputting a relatively ranked listing of the normalized scores of at least a subset of the distinct entity tuples, to a storage or display device. 25. The method of claim 20 , wherein the quantitative indicator indicates one of the group consisting of popularity of the document where an entity tuple is matched or quality of the document where an entity tuple is matched. | 0.853896 |
8,595,010 | 11 | 16 | 11. A Hidden Markov Model generation system that generates Hidden Markov Models to be used for speech recognition with a given speech recognition system, the Hidden Markov Model generation system comprising: a scheduled-to-be used model group storage section that stores a scheduled-to-be-used model group including a plurality of Hidden Markov Models scheduled to be used by the given speech recognition system; and a filler model generation section that generates Hidden Markov Models to be used as filler models by the given speech recognition system based on all or at least a part of the Hidden Markov Model group in the scheduled-to-be-used model group; wherein the filler model generation section classifies a plurality of probability density functions composing all or at least a part of the Hidden Markov Model group in the scheduled-to-be-used model group into a plurality of clusters, obtains a given parameter for defining probability density functions composing Hidden Markov Models to be used as filler models. | 11. A Hidden Markov Model generation system that generates Hidden Markov Models to be used for speech recognition with a given speech recognition system, the Hidden Markov Model generation system comprising: a scheduled-to-be used model group storage section that stores a scheduled-to-be-used model group including a plurality of Hidden Markov Models scheduled to be used by the given speech recognition system; and a filler model generation section that generates Hidden Markov Models to be used as filler models by the given speech recognition system based on all or at least a part of the Hidden Markov Model group in the scheduled-to-be-used model group; wherein the filler model generation section classifies a plurality of probability density functions composing all or at least a part of the Hidden Markov Model group in the scheduled-to-be-used model group into a plurality of clusters, obtains a given parameter for defining probability density functions composing Hidden Markov Models to be used as filler models. 16. The Hidden Markov Model generation system according to claim 11 , wherein the filler model generation section obtains a cluster value of each of the clusters based on a mean for defining one or a plurality of probability density functions classified in each of the clusters, and obtains a mean for defining probability density functions composing the Hidden Markov Model to be used as the filler model or its state based on the obtained cluster value, and obtains a variance for defining probability density functions composing the Hidden Markov Model to be used as the filler model or its state based on a variance for defining one or a plurality of probability density functions classified into each of the clusters. | 0.647461 |
7,693,827 | 13 | 14 | 13. The system of claim 10 , further including a scaling factor associated with the similarity score. | 13. The system of claim 10 , further including a scaling factor associated with the similarity score. 14. The system of claim 13 , wherein the scaling factor is determined by normalizing the similarity score to a particular range. | 0.969868 |
8,819,051 | 1 | 4 | 1. One or more non-transitory computer-readable media storing instructions which, when processed by one or more processors, cause: an information service receiving, over one or more communications networks from a client device, one or more alphanumeric keywords, wherein both the one or more alphanumeric keywords and an information service indicator that uniquely identifies the information service are displayed to a user of the client device in visual content on a non-Web page medium; the information service identifying, at a first time, one or more first search-limiting criteria that both correspond to the one or more alphanumeric keywords and provide a first context for the one or more alphanumeric keywords, wherein the one or more first search-limiting criteria are not included in the visual content on the non-Web page medium; the information service providing both the one or more alphanumeric keywords and the one or more first search-limiting criteria to a search engine, wherein the search engine performs a first search using both the one or more alphanumeric keywords and the one or more first search-limiting criteria and generates first search results; the information service receiving the first search results from the search engine; the information service transmitting the first search results over the one or more communications networks to the client device; the information service identifying, at a second time that is different than the first time, one or more second search-limiting criteria that both correspond to the one or more alphanumeric keywords and provide, for the one or more alphanumeric keywords, a second context that is different than the first context; and the information service providing both the one or more alphanumeric keywords and the one or more second search-limiting criteria to the search engine, wherein the search engine performs a second search using both the one or more alphanumeric keywords and the one or more second search-limiting criteria and generates second search results. | 1. One or more non-transitory computer-readable media storing instructions which, when processed by one or more processors, cause: an information service receiving, over one or more communications networks from a client device, one or more alphanumeric keywords, wherein both the one or more alphanumeric keywords and an information service indicator that uniquely identifies the information service are displayed to a user of the client device in visual content on a non-Web page medium; the information service identifying, at a first time, one or more first search-limiting criteria that both correspond to the one or more alphanumeric keywords and provide a first context for the one or more alphanumeric keywords, wherein the one or more first search-limiting criteria are not included in the visual content on the non-Web page medium; the information service providing both the one or more alphanumeric keywords and the one or more first search-limiting criteria to a search engine, wherein the search engine performs a first search using both the one or more alphanumeric keywords and the one or more first search-limiting criteria and generates first search results; the information service receiving the first search results from the search engine; the information service transmitting the first search results over the one or more communications networks to the client device; the information service identifying, at a second time that is different than the first time, one or more second search-limiting criteria that both correspond to the one or more alphanumeric keywords and provide, for the one or more alphanumeric keywords, a second context that is different than the first context; and the information service providing both the one or more alphanumeric keywords and the one or more second search-limiting criteria to the search engine, wherein the search engine performs a second search using both the one or more alphanumeric keywords and the one or more second search-limiting criteria and generates second search results. 4. The one or more non-transitory computer-readable media of claim 1 , wherein: the one or more non-transitory media include additional instructions which, when processed by the one or more processors, cause the information service to generate one or more Web pages that include the first search results, wherein the first search results include references to one or more other Web pages that each includes at least one of the one or more alphanumeric keywords and the one or more first search-limiting criteria, and the information service transmitting the first search results over the one or more communications networks to the client device includes the information service transmitting the one or more Web pages to the client device. | 0.500677 |
9,483,768 | 1 | 5 | 1. A computer-implemented method, comprising: receiving, by a processor, interaction data corresponding to one or more interactions between a customer and a customer support representative and storing said interaction data in a memory; extracting the stored interaction data from the memory and detecting, by the processor, the presence of at least one language associated with the interaction data by comparing whole text strings or portions of text in the interaction data with available language detection models for different languages, and predicting a best matching language corresponding to the interaction data; generating, by the processor, textual content in a plurality of languages corresponding to the interaction data based at least in part on translating the interaction data using two or more languages different than the at least one language; determining, by the processor, at least one emotion score for text corresponding to each language from among the plurality of languages; determining, by the processor, an aggregate emotion score using the at least one emotion score for the text corresponding to the each language; modeling, by the processor, an interaction experience of the customer based at least in part on the aggregate emotion score; and providing at least one recommendation to the customer based on said modeled interaction experience. | 1. A computer-implemented method, comprising: receiving, by a processor, interaction data corresponding to one or more interactions between a customer and a customer support representative and storing said interaction data in a memory; extracting the stored interaction data from the memory and detecting, by the processor, the presence of at least one language associated with the interaction data by comparing whole text strings or portions of text in the interaction data with available language detection models for different languages, and predicting a best matching language corresponding to the interaction data; generating, by the processor, textual content in a plurality of languages corresponding to the interaction data based at least in part on translating the interaction data using two or more languages different than the at least one language; determining, by the processor, at least one emotion score for text corresponding to each language from among the plurality of languages; determining, by the processor, an aggregate emotion score using the at least one emotion score for the text corresponding to the each language; modeling, by the processor, an interaction experience of the customer based at least in part on the aggregate emotion score; and providing at least one recommendation to the customer based on said modeled interaction experience. 5. The method of claim 1 , wherein at least one interaction from among the one or more interactions comprises code-mixed content. | 0.919876 |
4,752,772 | 4 | 6 | 4. A Braille display keyboard which can be connected to a digital data processor arranged to store and process alphanumeric text, and having cursor control means, said processor responding to said cursor control means by identifying a location in said text and providing a Braille actuation signal corresponding to the character in the identified location in said text, said keyboard comprising a plurality of keys for generating input for the digital data processor, said plurality of keys including a Braille display key, said Braille display key being arranged to provide a Braille indicator of the character in the identified location in said text in response to said Braille actuation signal. | 4. A Braille display keyboard which can be connected to a digital data processor arranged to store and process alphanumeric text, and having cursor control means, said processor responding to said cursor control means by identifying a location in said text and providing a Braille actuation signal corresponding to the character in the identified location in said text, said keyboard comprising a plurality of keys for generating input for the digital data processor, said plurality of keys including a Braille display key, said Braille display key being arranged to provide a Braille indicator of the character in the identified location in said text in response to said Braille actuation signal. 6. A Braille display keyboard as defined in claim 4 wherein: A. said keys cause said input to generate when said keys are individually depressed, said input identifying the particular key which was depressed; and B. said Braille display key includes: 1. a holder having a plurality of first bearings and supporting a keycap which has a top surface, said top surface having a plurality of holes; 2. a keyguide on which said holder is slidably retained so that said holder can slide up and down on said keyguide; 3. a spring urging said holder upward on said guide; 4. a plurality of pins movably mounted on said holder, each of said pins being movable between a raised position in which said pin extends upwardly through one of said holes to project above said top surface and a lowered position in which the entire pin is below said top surface; 5. a plurality of double-crank rods having first crank arms and second crank arms separated by central shafts, said first crank arms being coupled to said pins, said center rods passing through and being supported by said first bearings so that rotation of said shafts moves said pins between said raised and lowered positions and said shafts move up and down with said holder without changing the vertical positions of said pins relative to said top surface; and 6. a plurality of solenoids responsive to said Braille actuation signal, said second crank arms being coupled to said solenoids so that said Braille actuation signal causes rotation of said shafts, thereby producing said Braille indicator. | 0.559943 |
9,258,136 | 2 | 3 | 2. The data processing system of claim 1 , further comprising an interface to one or more of local storage devices, a reader for a removable memory, a reader for removable storage devices, a home network comprising one or more home network storage devices, and a WAN network including at least one server comprising one or more WAN network storage devices. | 2. The data processing system of claim 1 , further comprising an interface to one or more of local storage devices, a reader for a removable memory, a reader for removable storage devices, a home network comprising one or more home network storage devices, and a WAN network including at least one server comprising one or more WAN network storage devices. 3. The data processing system of claim 2 , wherein the private resource is selected from at least one of the local storage devices, the removable memory, the removable storage devices, the home network storage devices, and the WAN network storage devices. | 0.90983 |
7,583,845 | 31 | 32 | 31. The system of claim 1 , wherein said search engine includes a query pool that contains a set of query vectors. | 31. The system of claim 1 , wherein said search engine includes a query pool that contains a set of query vectors. 32. The system of claim 31 , wherein the query vector pool is configured to allow an application to insert and maintain a set of active queries used by said search engine to search an input vector set. | 0.923806 |
9,996,626 | 18 | 19 | 18. A computing system, comprising: one or more processors; and a system that, when executed by at least one of the one or more processors, causes the computing system to: receive search results that are generated in response to a search request by a user and that indicate multiple items from multiple product categories, wherein the search results are provided by one or more online retailers; automatically determine one or more additional items to recommend to the user that are distinct from the multiple items indicated in the search results, by automatically determining one product category of the multiple product categories to associate with the search request from analyzing information about the multiple items in the search results, storing an association of the search request with the determined one product category, and selecting the one or more additional items from a plurality of items in the determined one product category; automatically send one or more electronic communications that have information about the one or more additional items, to cause the additional items to be included as part of a single search results Web page displayed to the user that also includes the search results; and update, after the sending and based at least in part on one or more interactions by the user with at least one of the displayed single search results Web page or one or more additional Web pages that are subsequently displayed to the user, the stored association of the search request from the determined one product category to a different product category, for use with later searches based at least in part on the search request. | 18. A computing system, comprising: one or more processors; and a system that, when executed by at least one of the one or more processors, causes the computing system to: receive search results that are generated in response to a search request by a user and that indicate multiple items from multiple product categories, wherein the search results are provided by one or more online retailers; automatically determine one or more additional items to recommend to the user that are distinct from the multiple items indicated in the search results, by automatically determining one product category of the multiple product categories to associate with the search request from analyzing information about the multiple items in the search results, storing an association of the search request with the determined one product category, and selecting the one or more additional items from a plurality of items in the determined one product category; automatically send one or more electronic communications that have information about the one or more additional items, to cause the additional items to be included as part of a single search results Web page displayed to the user that also includes the search results; and update, after the sending and based at least in part on one or more interactions by the user with at least one of the displayed single search results Web page or one or more additional Web pages that are subsequently displayed to the user, the stored association of the search request from the determined one product category to a different product category, for use with later searches based at least in part on the search request. 19. The computing system of claim 18 wherein the multiple items are each a product that is associated with one of the multiple product categories, and wherein the automatic determining of the one product category from the multiple product categories includes determining a most frequent product category of the multiple items. | 0.902395 |
10,120,862 | 1 | 6 | 1. A method for accessing documents, the method comprising: providing, by a processor of a computing system, a document comprising one or more original time references having corresponding meanings depending on one or more time bases; identifying, by the processor, at least one original time reference in the document; generating, by the processor, a corresponding time artifact for the at least one original time reference, the corresponding time artifact comprising corresponding time values being calculated from the corresponding original time references according to the one or more time bases and/or corresponding calculation instructions for calculating the corresponding time values from the corresponding original time references according to the one or more time bases; associating, by the processor, the corresponding time artifacts with the at least one original time reference for outputting the corresponding time values; generating, by the processor, the corresponding time artifacts to comprise corresponding translated time references, each translated time reference comprising the corresponding time values and a text corresponding to the meaning of the corresponding at least one original time reference, which changes the meaning of the at least one original time reference to a user accessing the document, independently of a time at which the document is accessed; generating, by the processor, a translated document from the document by replacing the at least one original time reference with the corresponding translated time references; and outputting, by the processor, the translated document in place of the document. | 1. A method for accessing documents, the method comprising: providing, by a processor of a computing system, a document comprising one or more original time references having corresponding meanings depending on one or more time bases; identifying, by the processor, at least one original time reference in the document; generating, by the processor, a corresponding time artifact for the at least one original time reference, the corresponding time artifact comprising corresponding time values being calculated from the corresponding original time references according to the one or more time bases and/or corresponding calculation instructions for calculating the corresponding time values from the corresponding original time references according to the one or more time bases; associating, by the processor, the corresponding time artifacts with the at least one original time reference for outputting the corresponding time values; generating, by the processor, the corresponding time artifacts to comprise corresponding translated time references, each translated time reference comprising the corresponding time values and a text corresponding to the meaning of the corresponding at least one original time reference, which changes the meaning of the at least one original time reference to a user accessing the document, independently of a time at which the document is accessed; generating, by the processor, a translated document from the document by replacing the at least one original time reference with the corresponding translated time references; and outputting, by the processor, the translated document in place of the document. 6. The method according to claim 1 , wherein for one or more variable original time references of the at least one original time reference depending on one or more variable time bases of the time bases, the method comprises: determining, by the processor, the variable time bases; and calculating, by the processor, the corresponding time values by applying the corresponding calculation instructions to the variable time bases. | 0.505774 |
8,745,025 | 14 | 17 | 14. A server comprising: at least one tangible memory that stores processor-executable instructions for facilitating a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive a first search query from a client device; identify at least one search engine to be queried; generate at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and send, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein the at least one hardware computer processor generates the at least one second search query by generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine. | 14. A server comprising: at least one tangible memory that stores processor-executable instructions for facilitating a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive a first search query from a client device; identify at least one search engine to be queried; generate at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and send, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein the at least one hardware computer processor generates the at least one second search query by generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine. 17. The server of claim 14 , wherein the at least one hardware computer processor, executes the processor-executable instructions to identify the at least one search engine to be queried from among a plurality of search engines, wherein the first language model is associated with at least one other of the plurality of search engines. | 0.501488 |
9,043,338 | 1 | 14 | 1. A computer-implemented method, comprising: identifying images that appear in a plurality of distinct book content items, the distinct book content items corresponding to published books and lacking explicit electronic links between each other; generating implicit links between two or more of the distinct book content items that each include a similar image, the links represented as weighted edges in a graph in which nodes represent corresponding book content items, each weighted edge representing one or more matches of image content in corresponding book content items as between different books for nodes that define a corresponding weighted edge; for particular distinct ones of the nodes, identifying images that match each other as between different book content items based on multiple descriptor points for each of the images, and assigning weightings to particular edges between the distinct ones of the nodes; and determining a rank score for each of the two or more distinct book content items based on the implicit links between the two or more distinct book content items, the rank score for each of the two or more distinct book content items being a value indicative of the importance of the distinct book content item relative to other distinct book content items. | 1. A computer-implemented method, comprising: identifying images that appear in a plurality of distinct book content items, the distinct book content items corresponding to published books and lacking explicit electronic links between each other; generating implicit links between two or more of the distinct book content items that each include a similar image, the links represented as weighted edges in a graph in which nodes represent corresponding book content items, each weighted edge representing one or more matches of image content in corresponding book content items as between different books for nodes that define a corresponding weighted edge; for particular distinct ones of the nodes, identifying images that match each other as between different book content items based on multiple descriptor points for each of the images, and assigning weightings to particular edges between the distinct ones of the nodes; and determining a rank score for each of the two or more distinct book content items based on the implicit links between the two or more distinct book content items, the rank score for each of the two or more distinct book content items being a value indicative of the importance of the distinct book content item relative to other distinct book content items. 14. The method of claim 1 , wherein identifying images comprises: identifying textual content in each of the plurality of distinct book content items; identifying blank space in each of the plurality of distinct book content items; and defining the images for each of the plurality of book content items as a portion of each distinct book content item that is not identified as textual content and is not identified as blank space. | 0.718301 |
7,660,793 | 21 | 22 | 21. The system of claim 20 wherein the structured data within the RDBMS comprises metadata about the unstructured data within the data store of unstructured data. | 21. The system of claim 20 wherein the structured data within the RDBMS comprises metadata about the unstructured data within the data store of unstructured data. 22. The system of claim 21 wherein the standardized database query comprises a SQL command. | 0.973361 |
9,076,347 | 11 | 15 | 11. A method for identifying a mispronounced word spoken by a user of a non-native language, comprising: presenting to the user a curriculum comprising a plurality of tracks, each track corresponding to a selected set of phrases; prompting the user to create an utterance corresponding to a phrase selected from among the plurality of tracks; analyzing, one or more electronic processors, the utterance using a speech recognition system, the speech recognition system returning a ranked list of two or more recognized phrases; comparing, the one or more electronic processors, each of the ranked list of two or more recognized phrases to a series of mispronunciations corresponding to the phrase; matching, using the one or more electronic processors, one of the ranked list of two or more recognized phrases to a mispronunciation; identifying, using the one or more electronic processors, guidance for the user to correct the matched mispronunciation based upon the match of the one of the ranked list of two or more recognized phrases to a mispronunciation; and displaying the guidance to the user. | 11. A method for identifying a mispronounced word spoken by a user of a non-native language, comprising: presenting to the user a curriculum comprising a plurality of tracks, each track corresponding to a selected set of phrases; prompting the user to create an utterance corresponding to a phrase selected from among the plurality of tracks; analyzing, one or more electronic processors, the utterance using a speech recognition system, the speech recognition system returning a ranked list of two or more recognized phrases; comparing, the one or more electronic processors, each of the ranked list of two or more recognized phrases to a series of mispronunciations corresponding to the phrase; matching, using the one or more electronic processors, one of the ranked list of two or more recognized phrases to a mispronunciation; identifying, using the one or more electronic processors, guidance for the user to correct the matched mispronunciation based upon the match of the one of the ranked list of two or more recognized phrases to a mispronunciation; and displaying the guidance to the user. 15. The method of claim 11 , further comprising accessing the speech recognition system via the Internet. | 0.873798 |
7,571,092 | 1 | 4 | 1. A method for localizing a software product, the method comprising: an automated localization mechanism implemented in a computer extracting localizable text strings, to be translated into a language for which the product is to be localized, from one or more localizable files of the software product; the localization mechanism searching a localization database for translations of the extracted localizable text strings, wherein the localization database comprises text strings and associated translations of the text strings in the language for which the product is to be localized; the localization mechanism writing translations for the localizable text strings found in the database into localized versions of the localizable files at locations from which the corresponding localizable text strings were extracted such that the localized versions match an original file structure of the localizable files; and the localization mechanism storing the localized versions of the localizable files in file system locations in accordance with a file organization scheme for the product, wherein the localized versions of the localizable files in the file system locations have the original file structure and are ready for a final build into a localized version of the software product such that all translations in the localized versions relative to the localizable files are obtained by the localization mechanism performing said extracting, said searching, said writing and said storing. | 1. A method for localizing a software product, the method comprising: an automated localization mechanism implemented in a computer extracting localizable text strings, to be translated into a language for which the product is to be localized, from one or more localizable files of the software product; the localization mechanism searching a localization database for translations of the extracted localizable text strings, wherein the localization database comprises text strings and associated translations of the text strings in the language for which the product is to be localized; the localization mechanism writing translations for the localizable text strings found in the database into localized versions of the localizable files at locations from which the corresponding localizable text strings were extracted such that the localized versions match an original file structure of the localizable files; and the localization mechanism storing the localized versions of the localizable files in file system locations in accordance with a file organization scheme for the product, wherein the localized versions of the localizable files in the file system locations have the original file structure and are ready for a final build into a localized version of the software product such that all translations in the localized versions relative to the localizable files are obtained by the localization mechanism performing said extracting, said searching, said writing and said storing. 4. The method as recited in claim 1 , further comprising: repeating: the localization mechanism searching the localization database for translations of the extracted localizable text strings; the localization mechanism writing translations for the localizable text strings found in the database into localized versions of the localizable files at locations from which the corresponding localizable text strings were extracted; in response to translations for one or more localizable text strings not being found in the localization database: the localization mechanism generating entries in a translation kit for the localizable text strings not found in the localization database, wherein the translation kit is formatted in accordance with a canonical translation kit format, wherein the same canonical format is used for the translation kit regardless of the format of the localizable files, and wherein the translation kit is separate from the localizable files, and wherein the translation kit is configured to be provided to a translator for translation of the localizable text strings for which entries were made in the translation kit; and providing the translation kit to a translator for translation of the localizable text strings in the translation kit; and importing translations of the localizable text strings from the translation kit into the translation database in accordance with the canonical translation kit format; wherein said repeating is performed until the translation kit includes no entries for localizable text strings to be translated. | 0.500319 |
8,914,357 | 6 | 7 | 6. The method of claim 1 , wherein: the selecting content further comprises using demographic data associated with the determined first one of the geographic features, and the corresponding keyword mapping for the determined first one of the geographic features is based on demographic data of the user. | 6. The method of claim 1 , wherein: the selecting content further comprises using demographic data associated with the determined first one of the geographic features, and the corresponding keyword mapping for the determined first one of the geographic features is based on demographic data of the user. 7. The method of claim 6 , wherein greater weight is assigned to location keywords in the corresponding keyword mapping that are associated with demographic data similar to the demographic data of the user. | 0.94393 |
8,538,970 | 8 | 25 | 8. A system, comprising: a computer-implemented interface to receive a search query from a client device associated with a user; and a computer-implemented processing unit to: initiate a search of information regarding a corpus of documents, based on the search query, to identify a ranked set of search result documents, identify a first set of documents, each document in the first set of documents being ranked higher than a threshold by a global document ranking algorithm, identify a second set of documents, associated with preferences of the user or a group of users that includes the user, from a query history or document browsing history associated with the user, generate an intersection set, documents in the intersection set being common to both the first set and the second set, identify at least one document in the intersection set that includes a link to a particular document in the ranked set of search result documents, re-rank, in the ranked set of search result documents, the particular document based on at least one weight assigned to the at least one document, to identify a re-ranked set of search result documents, and provide information associated with the re-ranked search result documents to the user. | 8. A system, comprising: a computer-implemented interface to receive a search query from a client device associated with a user; and a computer-implemented processing unit to: initiate a search of information regarding a corpus of documents, based on the search query, to identify a ranked set of search result documents, identify a first set of documents, each document in the first set of documents being ranked higher than a threshold by a global document ranking algorithm, identify a second set of documents, associated with preferences of the user or a group of users that includes the user, from a query history or document browsing history associated with the user, generate an intersection set, documents in the intersection set being common to both the first set and the second set, identify at least one document in the intersection set that includes a link to a particular document in the ranked set of search result documents, re-rank, in the ranked set of search result documents, the particular document based on at least one weight assigned to the at least one document, to identify a re-ranked set of search result documents, and provide information associated with the re-ranked search result documents to the user. 25. The system of claim 8 , where the computer-implemented processing unit, when identifying the second set of documents, is further to: identify, as the second set of documents, a substantial entirety of a corpus of aggregated documents. | 0.767123 |
7,886,264 | 20 | 22 | 20. A computing apparatus programmed to perform a method for use in a computing programming environment, the method comprising: a computing device; a bus system; a storage communicating with the computing device over the bus system; an application residing in the storage that, when invoked, is capable of: receiving a plurality of user inputs, each user input specifying an action in a workflow; automatically identifying a data type incompatibility between an output of a first one of the specified actions and an input of a second one of the specified actions; and automatically generating a background script, to run in the background, wherein the background script is adapted to execute the actions in the workflow responsive to the user inputs, the background script adapted to automatically convert data of at least one of the incompatible data types to a compatible data type, wherein automatically converting the data comprises converting data based at least upon a relevance hierarchy of compatible data types. | 20. A computing apparatus programmed to perform a method for use in a computing programming environment, the method comprising: a computing device; a bus system; a storage communicating with the computing device over the bus system; an application residing in the storage that, when invoked, is capable of: receiving a plurality of user inputs, each user input specifying an action in a workflow; automatically identifying a data type incompatibility between an output of a first one of the specified actions and an input of a second one of the specified actions; and automatically generating a background script, to run in the background, wherein the background script is adapted to execute the actions in the workflow responsive to the user inputs, the background script adapted to automatically convert data of at least one of the incompatible data types to a compatible data type, wherein automatically converting the data comprises converting data based at least upon a relevance hierarchy of compatible data types. 22. The computing apparatus of claim 20 , wherein the application is further capable of at least one of automatically storing the script, automatically invoking the script, and automatically executing the script. | 0.813051 |
7,849,108 | 1 | 2 | 1. A system for establishing a database for a pooled endowment fund system, comprising: an import template provided in a web browser program comprising a plurality of column headers, residing in a client computer and configured to accept pooled endowment data from a flat file source, wherein the pooled endowment data comprises an account header, an ID header, a fund name header, an investment pool header and a seed data header, and wherein seed data within the seed data header comprises unit shares or dollar balances; a server coupled to the client computer; an import utility configured to receive the pooled endowment data from the import template; a plurality of holding tables comprising names corresponding to the plurality of column headers; and a relational database; wherein the import utility reads the column header in the import template and parses the pooled endowment data received from the import template according the column header by placing the pooled endowment data corresponding to an individual column into an matching holding table, the import utility relates the pooled endowment data by assigning a key number to individual categories in the holding tables, eliminating duplicated categories in the holding tables and linking the key number to an endowment fund record within the relational database. | 1. A system for establishing a database for a pooled endowment fund system, comprising: an import template provided in a web browser program comprising a plurality of column headers, residing in a client computer and configured to accept pooled endowment data from a flat file source, wherein the pooled endowment data comprises an account header, an ID header, a fund name header, an investment pool header and a seed data header, and wherein seed data within the seed data header comprises unit shares or dollar balances; a server coupled to the client computer; an import utility configured to receive the pooled endowment data from the import template; a plurality of holding tables comprising names corresponding to the plurality of column headers; and a relational database; wherein the import utility reads the column header in the import template and parses the pooled endowment data received from the import template according the column header by placing the pooled endowment data corresponding to an individual column into an matching holding table, the import utility relates the pooled endowment data by assigning a key number to individual categories in the holding tables, eliminating duplicated categories in the holding tables and linking the key number to an endowment fund record within the relational database. 2. The system as claimed in claim 1 wherein the import template is located on the client computer and the import utility is located on the server. | 0.745645 |
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