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8,965,835 | 13 | 14 | 13. The method of claim 12 , wherein generating the plurality of term taxonomies comprises: crawling the one or more data sources by an agent operative on a computing device to collect textual content from the one or more data sources; performing phrase extraction using the textual content and generating phrases; identifying sentiment phrases and non-sentiment phrases from the phrases; and associating a sentiment phrase with at least a non-sentiment phrase, wherein an association between a non-sentiment phrase and at least one corresponding sentiment phrase is a term taxonomy. | 13. The method of claim 12 , wherein generating the plurality of term taxonomies comprises: crawling the one or more data sources by an agent operative on a computing device to collect textual content from the one or more data sources; performing phrase extraction using the textual content and generating phrases; identifying sentiment phrases and non-sentiment phrases from the phrases; and associating a sentiment phrase with at least a non-sentiment phrase, wherein an association between a non-sentiment phrase and at least one corresponding sentiment phrase is a term taxonomy. 14. The method of claim 13 , wherein identifying the sentiment phrases and non-sentiment phrases comprises: comparing the phrases to sentiment phrases and non-sentiment phrases stored in a phrases database; determining that a phrase is a sentiment phrase if a match is found between the phrase and at least one sentiment phrase in the phrase database; and determining a phrase is a non-sentiment phrase when a match is found between the phrase and at least one non-sentiment phrase in the phrase database. | 0.874503 |
8,442,309 | 14 | 15 | 14. A computer system for method for learning a random multinomial logit (RML) classifier for scene segmentation, the system comprising: an image textonization module configured to: receive an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; and generate a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; a feature selection module configured to select one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; and a RML classifier configured to: learn multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluate the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. | 14. A computer system for method for learning a random multinomial logit (RML) classifier for scene segmentation, the system comprising: an image textonization module configured to: receive an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; and generate a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; a feature selection module configured to select one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; and a RML classifier configured to: learn multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluate the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. 15. The system of claim 14 , wherein the image textonization module is further configured to: remove contrast and brightness variations among the images in the image training set; convolute the image training set with a filter bank to generate convoluted images; and cluster the convoluted images. | 0.718216 |
9,069,759 | 10 | 12 | 10. The system of claim 9 , wherein the request further comprises the administrator injecting instructions for the processors to identify and retrieve un-translated strings in an original language into a template on each webpage of the administrator's website. | 10. The system of claim 9 , wherein the request further comprises the administrator injecting instructions for the processors to identify and retrieve un-translated strings in an original language into a template on each webpage of the administrator's website. 12. The system of claim 10 , wherein injecting comprises manually copying and pasting of instructions for processors one time into a template on each webpage regardless of the number of supported languages the webpages are requested to be translated into. | 0.953603 |
8,948,789 | 1 | 5 | 1. A method for inferring a high-level context associated with a mobile device, the method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity to a location of the mobile device, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; comparing the aggregated low-level context information to a plurality of templates, each template being associated with a high-level context and including one or more histograms of context data; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. | 1. A method for inferring a high-level context associated with a mobile device, the method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity to a location of the mobile device, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; comparing the aggregated low-level context information to a plurality of templates, each template being associated with a high-level context and including one or more histograms of context data; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. 5. The method of claim 1 , further comprising: estimating a time context of the mobile device, wherein the mobile device is estimated to be in the time context and at the location simultaneously, and wherein each of the plurality of other devices is estimated to be at the respective proximity during another time context, the time context and the another time context being the same. | 0.633588 |
9,076,182 | 17 | 18 | 17. A system comprising one or more computers programmed to perform operations comprising: determining whether a site-specific script for extracting financial data from a particular financial institution website is available; in response to determining that a site-specific script for extracting financial data from the particular financial institution website is not available, generating a site map of web pages and web page segments in the financial institution website, wherein the site map is generated based at least in part on a statistical analysis of (i) web pages and (ii) web page segments that are not in the financial institution website; generating, based on the site map of the financial institution website, a site-specific script for extracting financial data from the financial institution website; and extracting, for one or more users, financial data from the particular financial institution website using the generated site-specific script. | 17. A system comprising one or more computers programmed to perform operations comprising: determining whether a site-specific script for extracting financial data from a particular financial institution website is available; in response to determining that a site-specific script for extracting financial data from the particular financial institution website is not available, generating a site map of web pages and web page segments in the financial institution website, wherein the site map is generated based at least in part on a statistical analysis of (i) web pages and (ii) web page segments that are not in the financial institution website; generating, based on the site map of the financial institution website, a site-specific script for extracting financial data from the financial institution website; and extracting, for one or more users, financial data from the particular financial institution website using the generated site-specific script. 18. The system of claim 17 , wherein generating a site map of web pages and web page segments in the financial institution website, wherein the site map is generated based at least in part on a statistical analysis of (i) web pages and (ii) web page segments that are not in the financial institution website comprises: crawling the financial institution website to identify one or more web pages in the financial institution website and one or more web page segments in the one or more web pages in the financial institution website; determining, based on the statistical analysis, respective categorizations for the one or more identified web pages; and determining, based on the statistical analysis, respective categorizations for the one or more web page segments in the identified one or more web pages. | 0.573762 |
7,562,343 | 1 | 8 | 1. A method of providing a code assist function which suggests candidates responsive to a parsing of a partial program instruction statement, said method comprising: parsing a partial program instruction statement into tokens, wherein the tokens are identified and divided into keywords and variables according to a computer language in which the partial program instruction statement is written; determining whether the tokens match syntax statement tokens in a syntax library for the computer language by comparing the keywords against keywords of the syntax statement tokens or comparing the variables against symbols of the syntax statement tokens; moving a cursor positioned on one of the tokens for which the match is determined to a following token in response to determining that the token matches one of the syntax statement tokens in the syntax library; in response to determining that the token on which the cursor is positioned does not match one of the syntax statement tokens generating proposals from the cursor position based on previous tokens in the partial program instruction that matched syntax statement tokens in the syntax library; providing proposals to append to the partial program instruction statement to a user responsive to the parsing of the partial program instruction statement. | 1. A method of providing a code assist function which suggests candidates responsive to a parsing of a partial program instruction statement, said method comprising: parsing a partial program instruction statement into tokens, wherein the tokens are identified and divided into keywords and variables according to a computer language in which the partial program instruction statement is written; determining whether the tokens match syntax statement tokens in a syntax library for the computer language by comparing the keywords against keywords of the syntax statement tokens or comparing the variables against symbols of the syntax statement tokens; moving a cursor positioned on one of the tokens for which the match is determined to a following token in response to determining that the token matches one of the syntax statement tokens in the syntax library; in response to determining that the token on which the cursor is positioned does not match one of the syntax statement tokens generating proposals from the cursor position based on previous tokens in the partial program instruction that matched syntax statement tokens in the syntax library; providing proposals to append to the partial program instruction statement to a user responsive to the parsing of the partial program instruction statement. 8. The method of claim 1 , further comprising: determining the computer language in which the partial program instruction statement is written; and selecting one of a plurality of syntax libraries to use to determine whether the tokens match one of the plurality of syntax statements in the syntax library specific to the determined computer language. | 0.699486 |
8,156,146 | 1 | 4 | 1. A method implemented in computer-executable instructions that, when executed by a computer processor, produces a document for transmission to a client computing device that describes a folder tree, the method comprising: in response to receiving a request from the client computing device to access a root folder, querying a folder database for information associated with the root folder describing a user's access rights with regard to the root folder; authenticating that the user has rights to access the root folder and creating the document that describes the folder tree; adding metadata associated with the root folder to the document that describes the folder tree; for each subfolder within the hierarchy of the root folder that has the same permissions with respect to the user as the root folder: obtaining metadata of the subfolder from the folder database; adding metadata associated with the subfolder to the document that describes the folder tree; and for at least one subfolder within the hierarchy of the root folder that has different permissions with respect to the user as the root folder, inserting an XLink corresponding to the subfolder into the document, the XLink allowing the user to access the subfolder once the user's right to access the subfolder is authenticated. | 1. A method implemented in computer-executable instructions that, when executed by a computer processor, produces a document for transmission to a client computing device that describes a folder tree, the method comprising: in response to receiving a request from the client computing device to access a root folder, querying a folder database for information associated with the root folder describing a user's access rights with regard to the root folder; authenticating that the user has rights to access the root folder and creating the document that describes the folder tree; adding metadata associated with the root folder to the document that describes the folder tree; for each subfolder within the hierarchy of the root folder that has the same permissions with respect to the user as the root folder: obtaining metadata of the subfolder from the folder database; adding metadata associated with the subfolder to the document that describes the folder tree; and for at least one subfolder within the hierarchy of the root folder that has different permissions with respect to the user as the root folder, inserting an XLink corresponding to the subfolder into the document, the XLink allowing the user to access the subfolder once the user's right to access the subfolder is authenticated. 4. The method as recited in claim 1 , wherein adding metadata associated with the root folder to the document that describes the folder tree, includes: obtaining an identifier of the root folder in the request from the client computing device to access the root folder; and querying an index server to retrieve a list of files associated with the root folder. | 0.596629 |
9,444,772 | 1 | 3 | 1. A method implemented by a data processing apparatus, the method comprising: receiving, by the data processing apparatus, a question from an asker in which the question is associated with one or more topics; selecting, by the data processing apparatus, a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining, by the data processing apparatus, a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting, by the data processing apparatus, a first candidate answerer based on a ranking of the plurality of candidate answerers; sending, by the data processing apparatus, the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining, by the data processing apparatus, that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving, by the data processing apparatus, a second answer to the question from the second candidate answerer; and sending, by the data processing apparatus, the second answer to the asker and information that identifies the second answerer. | 1. A method implemented by a data processing apparatus, the method comprising: receiving, by the data processing apparatus, a question from an asker in which the question is associated with one or more topics; selecting, by the data processing apparatus, a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining, by the data processing apparatus, a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting, by the data processing apparatus, a first candidate answerer based on a ranking of the plurality of candidate answerers; sending, by the data processing apparatus, the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining, by the data processing apparatus, that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving, by the data processing apparatus, a second answer to the question from the second candidate answerer; and sending, by the data processing apparatus, the second answer to the asker and information that identifies the second answerer. 3. The method of claim 1 , further comprising: determining that a quality of a social match between the asker and a candidate answerer in the plurality of candidate answerers satisfies a quality score; and determining the respective wait time of the candidate answerer based on the quality score. | 0.763955 |
4,849,732 | 19 | 22 | 19. The input device according to claim 16, wherein at least one of said input means is a four-directional momentary dip-switch. | 19. The input device according to claim 16, wherein at least one of said input means is a four-directional momentary dip-switch. 22. The input device according to claim 19, wherein said switch is located in said key array of a plurality of input means and mounted to be operably accessible to the thumb of the hand. | 0.96449 |
9,785,993 | 13 | 16 | 13. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: collect a geolocation, detected by a positioning device, of a user terminal of a first user; receive a calendrical time identifier comprising indicia indicating an instance in which the first user was at the detected geolocation; generate a non-empty set of candidate venues based at least in part on the detected geolocation of the first user and the calendrical time identifier in response to determining that the candidate venues are within a predetermined distance of the detected geolocation of the first user; determine a set of venue categories based at least in part on the calendrical time identifier, wherein the calendrical time identifier indicates a time of day; include in the non-empty set of candidate venues and/or exclude from the non-empty set of candidate venues, one or more candidate venues based at least in part on the determined set of venue categories so that the non-empty set of candidate venues are determined based in part on the time of day and the indicia indicating the instance in which the first user was at the detected geolocation indicated by the calendrical time identifier; rank the candidate venues based on applying, to the candidate venues, a hypothesis that is learned from locations, detected by the positioning device, of one or more venues visited by at least one of i) the first user and ii) one or more additional users; provide visible indicia denoting one or more of the ranked candidate venues to a display device of the user terminal; and generate an electronic map indicating a detected current geolocation of the user terminal of the first user in relation to a detected location of a highest ranked venue, denoted as a recommended venue to the first user, of the ranked candidate venues and provide the generated electronic map to the display device for display of the electronic map by the user terminal, the recommended venue is determined to be a venue previously visited by one of the one or more additional users, but which was not previously visited by the first user. | 13. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: collect a geolocation, detected by a positioning device, of a user terminal of a first user; receive a calendrical time identifier comprising indicia indicating an instance in which the first user was at the detected geolocation; generate a non-empty set of candidate venues based at least in part on the detected geolocation of the first user and the calendrical time identifier in response to determining that the candidate venues are within a predetermined distance of the detected geolocation of the first user; determine a set of venue categories based at least in part on the calendrical time identifier, wherein the calendrical time identifier indicates a time of day; include in the non-empty set of candidate venues and/or exclude from the non-empty set of candidate venues, one or more candidate venues based at least in part on the determined set of venue categories so that the non-empty set of candidate venues are determined based in part on the time of day and the indicia indicating the instance in which the first user was at the detected geolocation indicated by the calendrical time identifier; rank the candidate venues based on applying, to the candidate venues, a hypothesis that is learned from locations, detected by the positioning device, of one or more venues visited by at least one of i) the first user and ii) one or more additional users; provide visible indicia denoting one or more of the ranked candidate venues to a display device of the user terminal; and generate an electronic map indicating a detected current geolocation of the user terminal of the first user in relation to a detected location of a highest ranked venue, denoted as a recommended venue to the first user, of the ranked candidate venues and provide the generated electronic map to the display device for display of the electronic map by the user terminal, the recommended venue is determined to be a venue previously visited by one of the one or more additional users, but which was not previously visited by the first user. 16. The apparatus of claim 13 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to: perform the ranking to exclude all venues visited by the first user and the hypothesis is learned from the locations of the one or more venues visited by the one or more additional users. | 0.707679 |
9,244,900 | 10 | 18 | 10. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: obtain input of an entity identifier uniquely associated with an entity operating a website, the entity identifier selected by one other than the entity and designating an entity database record within a database maintained by one other than the entity; obtain entity data including data pertaining to the entity operating the web site from the entity database record within the database using the entity identifier; access a template for a web page, the template including a content container and a style element; generate the web page for the entity using the template by dynamically inserting the entity data into the content container, the entity data inserted as the web page loads and presented as directed by the style element; enable revision of the web page by customizing the style element separately from the entity data to thereby create a customized style element; receive a request to update the web page to include updated entity data from an updated entity database record within the database; obtain the updated entity data including new data pertaining to the entity from the updated entity database record within the database using the entity identifier; and regenerate the web page using the template and the customized style element by dynamically inserting the updated entity data into the content container as the web page loads and, the web page rendered so as to include the updated entity data presented as directed by the customized style element. | 10. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: obtain input of an entity identifier uniquely associated with an entity operating a website, the entity identifier selected by one other than the entity and designating an entity database record within a database maintained by one other than the entity; obtain entity data including data pertaining to the entity operating the web site from the entity database record within the database using the entity identifier; access a template for a web page, the template including a content container and a style element; generate the web page for the entity using the template by dynamically inserting the entity data into the content container, the entity data inserted as the web page loads and presented as directed by the style element; enable revision of the web page by customizing the style element separately from the entity data to thereby create a customized style element; receive a request to update the web page to include updated entity data from an updated entity database record within the database; obtain the updated entity data including new data pertaining to the entity from the updated entity database record within the database using the entity identifier; and regenerate the web page using the template and the customized style element by dynamically inserting the updated entity data into the content container as the web page loads and, the web page rendered so as to include the updated entity data presented as directed by the customized style element. 18. The apparatus of claim 10 further comprising: the processor; a memory; wherein the processor and the memory comprise circuits and software for performing the instructions on the storage medium. | 0.809846 |
7,707,201 | 1 | 7 | 1. A method for assisting a user with a search, the method comprising: providing one or more concept networks, each concept network including a plurality of units and relationships among the units, wherein the relationships among the units are selected from a group consisting of extensions, associations and alternatives; receiving a baseline query; executing, using a processing device, a baseline search using the baseline query; transmitting, using the processing device, a result of the baseline search to the user; and in response to a user request: modifying, using the processing device, the baseline query to generate a modified query based at least in part on relationship information from at least one of the concept networks, the relationship information pertaining to at least one baseline unit extracted from the baseline query; executing a modified search using the modified query; transmitting, using the processing device, to the user a result of the modified search; and prompting, via the processing device, the user to provide feedback on the result of the modified search, wherein the user feedback is usable to perform a further modification to at least one of the baseline query and the modified query. | 1. A method for assisting a user with a search, the method comprising: providing one or more concept networks, each concept network including a plurality of units and relationships among the units, wherein the relationships among the units are selected from a group consisting of extensions, associations and alternatives; receiving a baseline query; executing, using a processing device, a baseline search using the baseline query; transmitting, using the processing device, a result of the baseline search to the user; and in response to a user request: modifying, using the processing device, the baseline query to generate a modified query based at least in part on relationship information from at least one of the concept networks, the relationship information pertaining to at least one baseline unit extracted from the baseline query; executing a modified search using the modified query; transmitting, using the processing device, to the user a result of the modified search; and prompting, via the processing device, the user to provide feedback on the result of the modified search, wherein the user feedback is usable to perform a further modification to at least one of the baseline query and the modified query. 7. The method of claim 1 , wherein modifying the baseline query comprises: determining a category of the baseline query according to a predefined taxonomy; and modifying the in the taxonomy. | 0.672414 |
7,818,378 | 1 | 13 | 1. A computer-implemented method of processing messages, comprising: at a client computer: receiving a plurality of messages directed to a user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier, wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; associating with each conversation a set of senders of messages included in the conversation; and displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the list of conversations comprises a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. | 1. A computer-implemented method of processing messages, comprising: at a client computer: receiving a plurality of messages directed to a user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation, each conversation having a respective conversation identifier, wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria and the respective conversation identifier is distinct from a subject reference of the one or more messages in the respective conversation; associating with each conversation a set of senders of messages included in the conversation; and displaying a list of conversations in an order determined in accordance with second predefined criteria, each conversation being represented as a single item in the list, wherein a plurality of conversations in the list of conversations each include a plurality of messages that share a common set of characteristics that meet the first predefined criteria; wherein the list of conversations comprises a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, wherein the sender list of a row in the list of conversations includes identifiers of one or more senders of at least one message in the corresponding conversation, including identifiers of a plurality of the senders in the set of senders, but less than all of the senders in the set of senders, when the set of senders exceeds a predefined limit. 13. The method of claim 1 , wherein a sender's identifier is assigned a priority, for determining which sender identifiers to include in the sender list, wherein the priority is determined in accordance with date/time information and status information associated with the messages in the conversation. | 0.855502 |
8,688,673 | 2 | 65 | 2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. | 2. A method for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, implemented using the computer system of claim 1 , the method comprising the steps of: identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users, performed using the means for identifying; copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, performed using the means for copying, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; aggregating the stored annotations based on a correlation between users, items and keywords, the correlation associated with the emergent self organization characteristics to form the collaborative content relevance between the plurality of items and the plurality of users, performed using the means for aggregating the stored annotations; and associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance, performed using the means for associating. 65. The method according to claim 2 , wherein at least one keyword for the annotations is obtained from text included in one of emails, documents, mail messages, and subject lines. | 0.964623 |
9,613,149 | 1 | 6 | 1. A method performed by a computer system having a processor of automatically mapping a pattern related to a location identifier of an object having content in the Web to a semantic type using metadata associated with the object, the method, comprising: collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself, wherein each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier; creating, by a processor, the pattern from the location identifier of the object in the Web, wherein the pattern is not identical to the location identifier and is used to search for other location identifiers of objects in the Web, wherein the metadata corresponds to the semantic type with which the content of the object has a semantic relationship, the metadata having an associated weighting; and storing, by the processor, the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; receiving via a user interface a search query associated with the semantic type; mapping the search query into the pattern stored in the database based on the semantic type; and performing a search for the other location identifiers matching the pattern for locating other objects or other objects including content embodied therein, that have the semantic relationship to the semantic type. | 1. A method performed by a computer system having a processor of automatically mapping a pattern related to a location identifier of an object having content in the Web to a semantic type using metadata associated with the object, the method, comprising: collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself, wherein each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier; creating, by a processor, the pattern from the location identifier of the object in the Web, wherein the pattern is not identical to the location identifier and is used to search for other location identifiers of objects in the Web, wherein the metadata corresponds to the semantic type with which the content of the object has a semantic relationship, the metadata having an associated weighting; and storing, by the processor, the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; receiving via a user interface a search query associated with the semantic type; mapping the search query into the pattern stored in the database based on the semantic type; and performing a search for the other location identifiers matching the pattern for locating other objects or other objects including content embodied therein, that have the semantic relationship to the semantic type. 6. The method of claim 1 , wherein, the metadata includes user-generated or user-identified metadata. | 0.82646 |
8,352,839 | 17 | 22 | 17. A computer implemented method for transmitting data, the method comprising: receiving data to be encoded into a word for transmission across a transmission medium; receiving constraints on symbol values associated with the word; encoding the data into the word, the encoding comprising: representing the data and the constraints as a first linear system in a first field of a first size; embedding the first linear system into a second linear system in a second field of a second size, the second size larger than the first size; solving the second linear system in the second field resulting in a solution; and collapsing the solution into the first field resulting in the word, the word satisfying the constraints on symbol values associated with the word; and outputting the word on the transmission medium. | 17. A computer implemented method for transmitting data, the method comprising: receiving data to be encoded into a word for transmission across a transmission medium; receiving constraints on symbol values associated with the word; encoding the data into the word, the encoding comprising: representing the data and the constraints as a first linear system in a first field of a first size; embedding the first linear system into a second linear system in a second field of a second size, the second size larger than the first size; solving the second linear system in the second field resulting in a solution; and collapsing the solution into the first field resulting in the word, the word satisfying the constraints on symbol values associated with the word; and outputting the word on the transmission medium. 22. The method of claim 17 , wherein the collapsing includes multiplying a matrix times the solution. | 0.75 |
9,342,495 | 2 | 3 | 2. The method of claim 1 , wherein said electronic representation is stored in the form of one or more electronic documents. | 2. The method of claim 1 , wherein said electronic representation is stored in the form of one or more electronic documents. 3. The method of claim 2 , wherein at least one of said electronic documents is a Portable Document Format (PDF) document. | 0.974445 |
9,195,654 | 1 | 6 | 1. A method comprising: receiving, by one or more processors of a device, a translation query, the translation query requesting a translation of one or more terms from a source language to a target language; determining, by the one or more processors, one or more translation features associated with the translation query; assigning, by the one or more processors, a feature value to each of the one or more translation features to form one or more feature values; applying, by the one or more processors, a feature weight to each of the one or more feature values, in a linear or non-linear manner, to generate a final value; determining, by the one or more processors, whether to provide a dialog translation user interface or a non-dialog translation user interface based on whether the final value satisfies a threshold, the dialog translation user interface facilitating translation of a conversation, the non-dialog translation user interface providing: one or more translation search results, and one or more links to one or more documents that provide a translation from the source language to the target language, and the non-dialog translation user interface being different than the dialog translation user interface; and providing, by the one or more processors, the dialog translation user interface for display when the final value satisfies the threshold. | 1. A method comprising: receiving, by one or more processors of a device, a translation query, the translation query requesting a translation of one or more terms from a source language to a target language; determining, by the one or more processors, one or more translation features associated with the translation query; assigning, by the one or more processors, a feature value to each of the one or more translation features to form one or more feature values; applying, by the one or more processors, a feature weight to each of the one or more feature values, in a linear or non-linear manner, to generate a final value; determining, by the one or more processors, whether to provide a dialog translation user interface or a non-dialog translation user interface based on whether the final value satisfies a threshold, the dialog translation user interface facilitating translation of a conversation, the non-dialog translation user interface providing: one or more translation search results, and one or more links to one or more documents that provide a translation from the source language to the target language, and the non-dialog translation user interface being different than the dialog translation user interface; and providing, by the one or more processors, the dialog translation user interface for display when the final value satisfies the threshold. 6. The method of claim 1 , further comprising: receiving a request to export information from the dialog translation user interface to a messaging application; and exporting the information from the dialog translation user interface to the messaging application based on the request. | 0.830742 |
9,311,402 | 24 | 31 | 24. A method for obtaining a plurality of contextually related instances, comprising: performing the following by a system which comprises at least one server: identifying at least one object of interest of a first instance type in a data resource; providing a query defining a contextual linkage between said first instance type and a second instance type; identifying a match between said contextual linkage and a sub-graph of a graph comprising a plurality of contextual relations among a plurality of instance types; selecting a group of a plurality of functionality modules, each said functionality module being configured for providing at least one instance of one of said plurality of instance types; dividing said received query to a number of single step queries; and iteratively executing at least some of said number of single step queries, wherein one of said number of single step queries includes a first member of said group and used for acquiring at least one intermediate instance wherein another of said number of single step queries includes a second member of said group with said at least one intermediate instance and used for acquiring at least one instance of said second instance type; wherein each of said plurality of functionality modules implements at least one of a web service and a code script; wherein members of said group are executed in an order matching dependencies in said sub graph. | 24. A method for obtaining a plurality of contextually related instances, comprising: performing the following by a system which comprises at least one server: identifying at least one object of interest of a first instance type in a data resource; providing a query defining a contextual linkage between said first instance type and a second instance type; identifying a match between said contextual linkage and a sub-graph of a graph comprising a plurality of contextual relations among a plurality of instance types; selecting a group of a plurality of functionality modules, each said functionality module being configured for providing at least one instance of one of said plurality of instance types; dividing said received query to a number of single step queries; and iteratively executing at least some of said number of single step queries, wherein one of said number of single step queries includes a first member of said group and used for acquiring at least one intermediate instance wherein another of said number of single step queries includes a second member of said group with said at least one intermediate instance and used for acquiring at least one instance of said second instance type; wherein each of said plurality of functionality modules implements at least one of a web service and a code script; wherein members of said group are executed in an order matching dependencies in said sub graph. 31. The method of claim 24 , wherein said data resource is a website, further comprising enhancing a display of said website with said at least one acquired instance. | 0.897022 |
8,365,138 | 50 | 51 | 50. The process of claim 49 wherein step D is performed by controlling a computer to iterate over said Formal Specification to determine a list of agent classes and by controlling a computer to execute a code generation method of a code generation structure stored in memory of a computer which stores requirements data from said Formal Specification which is used by said code generation method to fill in blanks in a source code template so as to generate source code which is structured to control a computer to display a dialog box which provides a list of agent classes from which a user logging onto said application program can choose and displays a field where a user can enter an object ID of a valid object ID for a valid object instance belonging to a class said user selects and displays a field in which said user enters a password, and wherein step G is performed by controlling a computer to execute a code generation method of a code generation structure stored in memory of a computer which stores requirements data from said Formal Specification which is used by said code generation method to fill in blanks in a source code template so as to generate source code for said application computer program which is structured to control a computer to create said data store by creating a table in a relational database for every class defined in said Formal Specification with a field in each said table for each said constant or variable attribute of said class. | 50. The process of claim 49 wherein step D is performed by controlling a computer to iterate over said Formal Specification to determine a list of agent classes and by controlling a computer to execute a code generation method of a code generation structure stored in memory of a computer which stores requirements data from said Formal Specification which is used by said code generation method to fill in blanks in a source code template so as to generate source code which is structured to control a computer to display a dialog box which provides a list of agent classes from which a user logging onto said application program can choose and displays a field where a user can enter an object ID of a valid object ID for a valid object instance belonging to a class said user selects and displays a field in which said user enters a password, and wherein step G is performed by controlling a computer to execute a code generation method of a code generation structure stored in memory of a computer which stores requirements data from said Formal Specification which is used by said code generation method to fill in blanks in a source code template so as to generate source code for said application computer program which is structured to control a computer to create said data store by creating a table in a relational database for every class defined in said Formal Specification with a field in each said table for each said constant or variable attribute of said class. 51. The process of claim 50 wherein step E is performed by controlling a computer to iterate through said Formal Specification and extract requirements data defining classes and services available to a user of said application computer program and which are to be implemented in said application computer program, and controlling a computer to execute a code generation method of a code generation structure stored in memory of a computer which stores requirements data from said Formal Specification which is used by said code generation method to automatically fill in blanks in a source code template so as to automatically generate source code which causes said main form to list said available services in an access hierarchy implemented as menu bars, HTTP pages or any other user interface display structure which allows said user of said application computer program to browse to and select a service said user executing said application computer program has privileges to perform, and wherein said source code automatically generated as part of said application computer program is also structured to control a computer executing said application computer program to, for each class, display an item labelled “query” or something which indicates selecting it will allow said user to access a query form to query said class, and to display an item labelled with the alias of a service for each service of said class available to the user, and, for each class which has an inheritance relationship with other classes, said automatically generated source code is structured to display an item for each subclass labelled with a subclass alias. | 0.906282 |
9,336,772 | 19 | 27 | 19. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining language use prediction data regarding an item; determining, using the language use prediction data and a learning model trained to generate probabilities based on the language use prediction data, probability information regarding a probability that the item will be referenced in a future utterance; generating a natural language processing model based at least partly on the probability information; determining a probability, from a general model, that a name of the item is included in a user utterance; and adjusting, using the natural language processing model, the probability that the name of the item is included in the user utterance. | 19. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining language use prediction data regarding an item; determining, using the language use prediction data and a learning model trained to generate probabilities based on the language use prediction data, probability information regarding a probability that the item will be referenced in a future utterance; generating a natural language processing model based at least partly on the probability information; determining a probability, from a general model, that a name of the item is included in a user utterance; and adjusting, using the natural language processing model, the probability that the name of the item is included in the user utterance. 27. The one or more non-transitory computer readable media of claim 19 , wherein the natural language processing model is interpolated with the general model. | 0.899746 |
8,799,776 | 2 | 4 | 2. The method according to claim 1 , wherein the one or more eSAO components are one or more elements from a group comprising: subjects, objects, actions, adjectives, prepositions, indirect objects, and adverbs. | 2. The method according to claim 1 , wherein the one or more eSAO components are one or more elements from a group comprising: subjects, objects, actions, adjectives, prepositions, indirect objects, and adverbs. 4. The method according to claim 2 , wherein the eSAO Whole-Part relations comprise a sequential operator relating the eSAO components of the Whole eSAO to the eSAO components of the Part eSAO, the operator including one or more of a lexical, grammatical, and semantic language indicator. | 0.932836 |
7,921,416 | 1 | 2 | 1. A method, comprising: accepting as input a program written in a formal language, wherein the input program comprises a plurality of operators that enable a declarative co-grouping of one or more tables, each with an alignment function, and a specification of zero or more procedural operations to be performed on each resulting co-group; co-grouping one or more tables referenced in the program into one or more co-groups according to one or more operators of the formal language used in the program; determining zero or more user-specified operations to be performed on each co-group according to the one or more operators of the formal language used in the program; and a translator corresponding to the formal language program translating the program into one or more jobs according to the one or more operators of the formal language used in the program and based on the one or more co-groups and the zero or more operations to be performed on each co-group, wherein each job comprises one or more structured calls to an application programming interface for encoded logic that is operable to generate a plurality of tasks for the parallel processing of the job on one or more data processing devices in a distributed system. | 1. A method, comprising: accepting as input a program written in a formal language, wherein the input program comprises a plurality of operators that enable a declarative co-grouping of one or more tables, each with an alignment function, and a specification of zero or more procedural operations to be performed on each resulting co-group; co-grouping one or more tables referenced in the program into one or more co-groups according to one or more operators of the formal language used in the program; determining zero or more user-specified operations to be performed on each co-group according to the one or more operators of the formal language used in the program; and a translator corresponding to the formal language program translating the program into one or more jobs according to the one or more operators of the formal language used in the program and based on the one or more co-groups and the zero or more operations to be performed on each co-group, wherein each job comprises one or more structured calls to an application programming interface for encoded logic that is operable to generate a plurality of tasks for the parallel processing of the job on one or more data processing devices in a distributed system. 2. The method of claim 1 , further comprising the steps of: assigning the plurality of tasks to the one or more data processing devices; and processing two or more of the plurality of tasks in parallel. | 0.683386 |
9,268,560 | 9 | 10 | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. 10. The non-transitory computer-readable storage medium of claim 9 , wherein the instructions are for further controlling a computer system to be configured for displaying a user prompt for saving the second change to the first dependent file in a non-transitory computer readable memory device. | 0.541925 |
8,751,217 | 1 | 10 | 1. A computer-implemented input-method editor process comprising: receiving a request from a user of an electronic device for an application-independent input method editor having written and spoken input capabilities, wherein the application-independent input method editor is configured to receive input for a plurality of applications executable by the electronic device; identifying that the user is about to provide spoken input to the application-independent input method editor; receiving a spoken input from the user, wherein the spoken input corresponds to an input to an application from the plurality of applications; generating, with the electronic device, a correlation between the spoken input and the application, from the plurality of applications, to which the spoken input is determined to correspond, wherein generating the correlation comprises (i) determining an application type for the application that identifies a category of application to which the application is assigned, each category of application capable of including a plurality of different applications, and (ii) matching one or more utterances in the spoken input to one or more stored terms that are associated with the application type; providing the spoken input and the generated correlation to a server, wherein the server is remote to the electronic device and includes a speech recognition system configured to access one or more language models for recognizing text based on the spoken input and the correlation; receiving text from the server, wherein the text represents a translation of the spoken input; selecting an application, from the plurality of applications, to receive the text, the selection using the generated correlation; and providing the text as an input to the selected application. | 1. A computer-implemented input-method editor process comprising: receiving a request from a user of an electronic device for an application-independent input method editor having written and spoken input capabilities, wherein the application-independent input method editor is configured to receive input for a plurality of applications executable by the electronic device; identifying that the user is about to provide spoken input to the application-independent input method editor; receiving a spoken input from the user, wherein the spoken input corresponds to an input to an application from the plurality of applications; generating, with the electronic device, a correlation between the spoken input and the application, from the plurality of applications, to which the spoken input is determined to correspond, wherein generating the correlation comprises (i) determining an application type for the application that identifies a category of application to which the application is assigned, each category of application capable of including a plurality of different applications, and (ii) matching one or more utterances in the spoken input to one or more stored terms that are associated with the application type; providing the spoken input and the generated correlation to a server, wherein the server is remote to the electronic device and includes a speech recognition system configured to access one or more language models for recognizing text based on the spoken input and the correlation; receiving text from the server, wherein the text represents a translation of the spoken input; selecting an application, from the plurality of applications, to receive the text, the selection using the generated correlation; and providing the text as an input to the selected application. 10. The process of claim 1 , further comprising: receiving a written input from the user in a first writing system; and presenting one or more candidates in a second writing system based on the written input in the first writing system. | 0.65896 |
9,348,925 | 1 | 11 | 1. A method performed by one or more data processing apparatuses, the method comprising: identifying a general search query that does not include a location phrase, wherein a location phrase is one or more terms that specify a geographic location; determining, for the general search query, a map query rate based on a ratio of a number of times that the general search query was received through an online map interface presenting the geographic location relative to a total number of times that the general search query was received; determining that the general search query is a locally significant query for the geographic location based, at least in part, on the map query rate for the general search query exceeding a threshold value; creating a local search query using the general search query and a location phrase representing the geographic location; requesting a set of general search results responsive to the general search query and a set of local search results responsive to the local search query; selecting, from the set of general search results and the set of local search results, a final set of search results including at least one local search result from the set of local search results and at least one general search result from the set of general search results; and providing data that cause presentation of the final set of search results. | 1. A method performed by one or more data processing apparatuses, the method comprising: identifying a general search query that does not include a location phrase, wherein a location phrase is one or more terms that specify a geographic location; determining, for the general search query, a map query rate based on a ratio of a number of times that the general search query was received through an online map interface presenting the geographic location relative to a total number of times that the general search query was received; determining that the general search query is a locally significant query for the geographic location based, at least in part, on the map query rate for the general search query exceeding a threshold value; creating a local search query using the general search query and a location phrase representing the geographic location; requesting a set of general search results responsive to the general search query and a set of local search results responsive to the local search query; selecting, from the set of general search results and the set of local search results, a final set of search results including at least one local search result from the set of local search results and at least one general search result from the set of general search results; and providing data that cause presentation of the final set of search results. 11. The method of claim 1 , wherein the location phrase is selected from a set of location phrases including a city and a zip code. | 0.924885 |
8,005,816 | 6 | 7 | 6. A method according to claim 1 , further comprising: auto-generating keywords for the suggested links. | 6. A method according to claim 1 , further comprising: auto-generating keywords for the suggested links. 7. A method according to claim 6 , wherein: auto-generating keywords includes capturing anchor text associated with the suggested link. | 0.95283 |
9,093,067 | 12 | 13 | 12. The method of claim 1 , further comprising selecting, based on estimated distances between a plurality of determined prosodic contours and a prosodic contour of text to be synthesized, a final determined prosodic contour associated with a smallest distance. | 12. The method of claim 1 , further comprising selecting, based on estimated distances between a plurality of determined prosodic contours and a prosodic contour of text to be synthesized, a final determined prosodic contour associated with a smallest distance. 13. The method of claim 12 , further comprising generating a prosodic contour for the text to be synthesized using the final determined prosodic contour. | 0.949572 |
9,277,041 | 8 | 10 | 8. A method according to claim 1 , wherein said determining the country comprises examining the language of text on the page. | 8. A method according to claim 1 , wherein said determining the country comprises examining the language of text on the page. 10. A method according to claim 8 , wherein said examining the language of text on the page comprises executing a language recogniser component to recognise the language of preselected words in the text on the page. | 0.899533 |
8,024,195 | 4 | 6 | 4. The apparatus of claim 1 further comprising a network interface for coupling the kiosk to a network. | 4. The apparatus of claim 1 further comprising a network interface for coupling the kiosk to a network. 6. The apparatus of claim 4 wherein at least a second portion of the history information is stored on a remote database. | 0.940417 |
6,134,552 | 1 | 20 | 1. An information repository system for managing, storing and retrieving a computer data file comprising: a content server for storing said file; content model means for defining a three-tiered content model which comprises nested tiers including component classes, physical object classes, and relations classes, and wherein a logical object contains a reference to said file and describes said file in generic terms and with reference to at least one attribute, and further wherein said logical object contains a reference to at least one physical object associated with said logical object, and contains a reference to at least one component associated with said at least one physical object, and wherein relations from said relations classes are used to connect logical objects and physical objects with other logical objects or physical objects; an administration data table which contains administration data associated with physical objects; logical hyperlink means for resolving, in context-based indirect runtime resolution, the logical object, to a physical destination of the file associated with the at least one physical object associated with the logical object; context resolution means, enabled by said logical hyperlink means, for context-based resolution of a particular physical object associated with the logical object on the basis of the context attributes of a request as determined by correlating requested context attributes against attributes of physical objects associated with the logical object and attributes of a front-end client application; and a management agent for managing said logical objects and physical objects using said content model means in conformance with said administration data and for identifying and retrieving the physical object resolved via said logical hyperlink means and said context resolution means. | 1. An information repository system for managing, storing and retrieving a computer data file comprising: a content server for storing said file; content model means for defining a three-tiered content model which comprises nested tiers including component classes, physical object classes, and relations classes, and wherein a logical object contains a reference to said file and describes said file in generic terms and with reference to at least one attribute, and further wherein said logical object contains a reference to at least one physical object associated with said logical object, and contains a reference to at least one component associated with said at least one physical object, and wherein relations from said relations classes are used to connect logical objects and physical objects with other logical objects or physical objects; an administration data table which contains administration data associated with physical objects; logical hyperlink means for resolving, in context-based indirect runtime resolution, the logical object, to a physical destination of the file associated with the at least one physical object associated with the logical object; context resolution means, enabled by said logical hyperlink means, for context-based resolution of a particular physical object associated with the logical object on the basis of the context attributes of a request as determined by correlating requested context attributes against attributes of physical objects associated with the logical object and attributes of a front-end client application; and a management agent for managing said logical objects and physical objects using said content model means in conformance with said administration data and for identifying and retrieving the physical object resolved via said logical hyperlink means and said context resolution means. 20. The system of claim 1 further comprising content access means to maintain inter-physical object relations and to prevent the simultaneous editing of a physical object by multiple users. | 0.824349 |
7,672,940 | 7 | 8 | 7. A method of processing a document, the method comprising: identifying keywords in the document indicative of an informational property of the document; assigning a score to each of the keywords in the document based on a location of each of the keywords, a relation of each of the keywords to other words identified from text in the document, a relation between graphic lines and each of the keywords, and text of each keyword; assigning a combined score to the document based on the score assigned to each of the keywords in the document, wherein assigning the combined score comprises assigning a combined score to the document for each of a plurality of types of document; and using a processor of a computing device, classifying the document as being one type of document selected from the plurality of types of document based on the combined score, wherein classifying the document comprises comparing the combined score to a threshold value. | 7. A method of processing a document, the method comprising: identifying keywords in the document indicative of an informational property of the document; assigning a score to each of the keywords in the document based on a location of each of the keywords, a relation of each of the keywords to other words identified from text in the document, a relation between graphic lines and each of the keywords, and text of each keyword; assigning a combined score to the document based on the score assigned to each of the keywords in the document, wherein assigning the combined score comprises assigning a combined score to the document for each of a plurality of types of document; and using a processor of a computing device, classifying the document as being one type of document selected from the plurality of types of document based on the combined score, wherein classifying the document comprises comparing the combined score to a threshold value. 8. The method of claim 7 wherein scores are assigned to words in the document that are indicative of the words being associated with a particular field. | 0.923155 |
9,489,688 | 8 | 12 | 8. A system for recommending search phrases, comprising at least one processor configured to: obtain one or more subject terms and one or more descriptive terms relating to the one or more subject terms from title information of information published by publishers; combine at least some of the one or more subject terms with at least some of the one or more descriptive terms to form a set of one or more search phrases; calculate a first appraisal value for a search phrase among the set of one or more search phrases, the calculating of the first appraisal value comprising multiplying term frequency of the search phrase with an inverse document frequency of the search phrase; determine a second appraisal value of the search phrase, the determining of the second appraisal value comprising: calculate an inverse class frequency of the search phrase within a designated category, wherein the inverse class frequency is regarded as the second appraisal value; calculate a third appraisal value of the search phrase, comprising to: calculate a first probability that a first term associated with a search phrase that appears in the published information; calculate a second probability that the first term appears jointly with a second term in the search phrase associated with the published information; and combine the first probability and the second probability to obtain the third appraisal value; combine at least the first appraisal value, the second appraisal value, and the third appraisal value of the search phrase to obtain a publisher recommendation appraisal value for the search phrase; and select a recommended phrase among the set of one or more search phrases based at least in part on a set of one or more corresponding publisher recommendation appraisal values for the set of one or more search phrases; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions. | 8. A system for recommending search phrases, comprising at least one processor configured to: obtain one or more subject terms and one or more descriptive terms relating to the one or more subject terms from title information of information published by publishers; combine at least some of the one or more subject terms with at least some of the one or more descriptive terms to form a set of one or more search phrases; calculate a first appraisal value for a search phrase among the set of one or more search phrases, the calculating of the first appraisal value comprising multiplying term frequency of the search phrase with an inverse document frequency of the search phrase; determine a second appraisal value of the search phrase, the determining of the second appraisal value comprising: calculate an inverse class frequency of the search phrase within a designated category, wherein the inverse class frequency is regarded as the second appraisal value; calculate a third appraisal value of the search phrase, comprising to: calculate a first probability that a first term associated with a search phrase that appears in the published information; calculate a second probability that the first term appears jointly with a second term in the search phrase associated with the published information; and combine the first probability and the second probability to obtain the third appraisal value; combine at least the first appraisal value, the second appraisal value, and the third appraisal value of the search phrase to obtain a publisher recommendation appraisal value for the search phrase; and select a recommended phrase among the set of one or more search phrases based at least in part on a set of one or more corresponding publisher recommendation appraisal values for the set of one or more search phrases; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions. 12. The system as described in claim 8 , wherein the at least one processor further configured to: prior to combining at least the first appraisal value and the second appraisal value of the search phrase, set sixth appraisal values of search phrases whose subject term is related to new merchandise, the sixth appraisal values being higher for search phrases whose subject term is related to new merchandise. | 0.850839 |
8,676,566 | 15 | 16 | 15. The method of claim 14 , wherein generating the verb classifier includes: extracting the statistical features from a training verb set including activity verbs and state verbs; and generating the verb classifier for classifying verbs using the machine learning algorithm based on the extracted statistical features. | 15. The method of claim 14 , wherein generating the verb classifier includes: extracting the statistical features from a training verb set including activity verbs and state verbs; and generating the verb classifier for classifying verbs using the machine learning algorithm based on the extracted statistical features. 16. The method of claim 15 , wherein extracting the statistical features includes: generating an appropriate query about a given verb for a search engine; and extracting a statistical value of the query from the search engine. | 0.85875 |
8,291,316 | 14 | 17 | 14. In a variable imaging (VI) production system receiving a VI job stream, a VI interpreter system comprising: a Customer Relationship Management (CRM) processor configured to perform CRM information gathering, the CRM information gathering including: providing at least one digital image included in a digital asset database; associating at least one or more keywords with each digital image in the digital asset database, the at least one or more keywords including marketing information related to the digital image for associating the at least one digital image with a recipient; merging the at least one digital image with variable information included in a database using a template to generate a VI job stream; after the merging and during processing of the VI job stream, extracting, for each digital image contained in the VI job stream, the at least one or more keywords previously associated with the digital image; generating a CRM output containing the at least one or more extracted keywords; and delivering the CRM output to a user, wherein the marketing information included in the CRM output is adapted to be used for providing personalized advertising to the recipient; a raster image processor configured to produce electronic output document images based on a variable imaging job included in the received VI job stream; a user interface for receiving instructions from an operator of the VI interpreter and for displaying messages and images to the operator; and a finishing system configured to produce a final product based on the electronic output document images. | 14. In a variable imaging (VI) production system receiving a VI job stream, a VI interpreter system comprising: a Customer Relationship Management (CRM) processor configured to perform CRM information gathering, the CRM information gathering including: providing at least one digital image included in a digital asset database; associating at least one or more keywords with each digital image in the digital asset database, the at least one or more keywords including marketing information related to the digital image for associating the at least one digital image with a recipient; merging the at least one digital image with variable information included in a database using a template to generate a VI job stream; after the merging and during processing of the VI job stream, extracting, for each digital image contained in the VI job stream, the at least one or more keywords previously associated with the digital image; generating a CRM output containing the at least one or more extracted keywords; and delivering the CRM output to a user, wherein the marketing information included in the CRM output is adapted to be used for providing personalized advertising to the recipient; a raster image processor configured to produce electronic output document images based on a variable imaging job included in the received VI job stream; a user interface for receiving instructions from an operator of the VI interpreter and for displaying messages and images to the operator; and a finishing system configured to produce a final product based on the electronic output document images. 17. The VI interpreter system set forth in claim 14 , wherein the step of extracting the least one or more keywords previously associated with the digital image further includes: extracting the least one or more associated keywords stored in an image header portion. | 0.684834 |
8,925,108 | 11 | 13 | 11. A software product embodied in a non-transient machine-readable medium, the software product comprising instructions operable to cause one or more processors to perform operations comprising: generating a consent statement relating to an electronic document tethered to a document control system; transmitting the consent statement to a client that is authorized to access the electronic document; receiving, from the client and in response to the consent statement, a consent indication that represents an affirmative response to the consent statement; modifying, based on the consent indication, actions-taken information associated with the electronic document, the actions-taken information describing actions taken with respect to the electronic document; combining and signing the electronic document and the modified actions-taken information to form a signed document that includes the modified actions-taken information and that can be accessed independent of the document control system. | 11. A software product embodied in a non-transient machine-readable medium, the software product comprising instructions operable to cause one or more processors to perform operations comprising: generating a consent statement relating to an electronic document tethered to a document control system; transmitting the consent statement to a client that is authorized to access the electronic document; receiving, from the client and in response to the consent statement, a consent indication that represents an affirmative response to the consent statement; modifying, based on the consent indication, actions-taken information associated with the electronic document, the actions-taken information describing actions taken with respect to the electronic document; combining and signing the electronic document and the modified actions-taken information to form a signed document that includes the modified actions-taken information and that can be accessed independent of the document control system. 13. The software product of claim 11 , wherein forming the signed document comprises signing the modified actions-taken information, combining the signed modified actions-taken information with the electronic document, and signing the combination of the electronic document and the signed modified actions-taken information. | 0.79597 |
9,063,765 | 1 | 11 | 1. A system for generating source code, comprising: a processor configured to: receive a source binary representation encoded using a first programming language, trace the source binary representation to determine an intermediate representation of the source binary representation, optimize the intermediate representation, and use the optimized intermediate representation to generate a target source code in at least a second programming language that does not require a virtual machine to execute, wherein the target source code has not been compiled; wherein optimizing the intermediate representation includes using an intermediate programming language to functionally modify an object-oriented programming model object reference into a procedural programming model version; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions; wherein functionally modifying the object-oriented programming model object reference includes functionally flatting the object-oriented programming model object reference by resolving and relinking an object-oriented look-up into the procedural programming model version, generating a renamed procedural programming model method by prepending a fully qualified class name to a name of a corresponding oriented programming model method, and modifying the intermediate representation to use a chained tail recursion to approximate a multithreading not directly supported by the second programming language. | 1. A system for generating source code, comprising: a processor configured to: receive a source binary representation encoded using a first programming language, trace the source binary representation to determine an intermediate representation of the source binary representation, optimize the intermediate representation, and use the optimized intermediate representation to generate a target source code in at least a second programming language that does not require a virtual machine to execute, wherein the target source code has not been compiled; wherein optimizing the intermediate representation includes using an intermediate programming language to functionally modify an object-oriented programming model object reference into a procedural programming model version; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions; wherein functionally modifying the object-oriented programming model object reference includes functionally flatting the object-oriented programming model object reference by resolving and relinking an object-oriented look-up into the procedural programming model version, generating a renamed procedural programming model method by prepending a fully qualified class name to a name of a corresponding oriented programming model method, and modifying the intermediate representation to use a chained tail recursion to approximate a multithreading not directly supported by the second programming language. 11. The system of claim 1 , wherein functionally modifying the object-oriented programming model object reference includes emulating a threading synchronization using a continuation function to reschedule an emulated thread. | 0.559055 |
7,630,895 | 11 | 14 | 11. A computer readable medium having instructions stored thereon that, when executed, cause a machine to: compare a plurality of different test utterances to a plurality of training utterances for the speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weight each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combine the weighted preliminary verification decisions to form a verification decision. | 11. A computer readable medium having instructions stored thereon that, when executed, cause a machine to: compare a plurality of different test utterances to a plurality of training utterances for the speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weight each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combine the weighted preliminary verification decisions to form a verification decision. 14. The computer readable medium of claim 11 having instructions stored thereon that, when executed, cause the machine to generate a code book associated with a plurality of speakers and including the plurality of training utterances. | 0.737079 |
9,455,945 | 1 | 7 | 1. A method comprising: by one or more computers of a social-networking system, accessing a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; by the one or more computers of the social-networking system, determining, from the social graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers of the social-networking system, determining that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; by the one or more computers of the social-networking system, determining that a main page is associated with the particular version and the one or more other versions of the media content; and by the one or more computers of the social-networking system, aggregating the user's “like” of the first page to the main page. | 1. A method comprising: by one or more computers of a social-networking system, accessing a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; by the one or more computers of the social-networking system, determining, from the social graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers of the social-networking system, determining that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; by the one or more computers of the social-networking system, determining that a main page is associated with the particular version and the one or more other versions of the media content; and by the one or more computers of the social-networking system, aggregating the user's “like” of the first page to the main page. 7. The method of claim 1 , wherein the “like” comprises an indication that the user likes the media content. | 0.843931 |
7,617,224 | 1 | 4 | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. | 1. A method for managing hierarchically related software components, comprising: creating a first software component descriptor containing information about a first software component of a plurality of software components; creating a second software component descriptor containing information about a second software component of the plurality of software components; creating a plurality of aggregate descriptors, each descriptor containing information about relationships among the plurality of software components and aggregates of the plurality of software components; defining hierarchical interrelationships between the plurality of software components and the aggregate descriptors to produce a component hierarchy; managing lifecycles, access controls, interrelationships, versioning and a list of the plurality of software components to maintain the consistency of the component hierarchy; filtering the list of software components based upon the component hierarchy to produce a filtered list of software components; selecting a particular software component from the filtered list of software components; and integrating the particular software component into a software application; and modifying the component hierarchy based upon associations generated by the filtering. 4. The method of claim 1 , wherein the component hierarchy is made up of a plurality of layers, each layer of the plurality of layers defining a different scope of connectivity between corresponding software components or aggregates of software components. | 0.501946 |
7,693,956 | 1 | 3 | 1. A computer implemented method, comprising: receiving by a search service computer server on the Internet, from a client device having access to the Internet, a search request, wherein the search request includes one or more search criteria and directs the search service computing server to search the Internet for a plurality of information locations having information associated with the plurality of search criteria; and returning to the client device, in response to the search request, by the search service computing server, an answer page having a plurality of answers identifying a plurality of information locations on the Internet having information associated with the one or more search criteria, wherein at least a first of the answers associated with a first information page of a first information location having information associated with the search criteria does not include any input field displayed on the answer page, and at least a second of the answers associated with a second information page of a second information location having information associated with the search criteria includes at least one input field displayed on the answer page, the input field being associated with the second information page; wherein the second answer is placed in the answer page either ahead of or at a side of the first answer; wherein the second answer including at least one input field further includes an index indexing to the second information location from which the input field is generated, the index including the one or more search criteria and a set of one or more associated parameters, and the set of one or more associated parameters including at least one parameter variable corresponding to the at least one input field. | 1. A computer implemented method, comprising: receiving by a search service computer server on the Internet, from a client device having access to the Internet, a search request, wherein the search request includes one or more search criteria and directs the search service computing server to search the Internet for a plurality of information locations having information associated with the plurality of search criteria; and returning to the client device, in response to the search request, by the search service computing server, an answer page having a plurality of answers identifying a plurality of information locations on the Internet having information associated with the one or more search criteria, wherein at least a first of the answers associated with a first information page of a first information location having information associated with the search criteria does not include any input field displayed on the answer page, and at least a second of the answers associated with a second information page of a second information location having information associated with the search criteria includes at least one input field displayed on the answer page, the input field being associated with the second information page; wherein the second answer is placed in the answer page either ahead of or at a side of the first answer; wherein the second answer including at least one input field further includes an index indexing to the second information location from which the input field is generated, the index including the one or more search criteria and a set of one or more associated parameters, and the set of one or more associated parameters including at least one parameter variable corresponding to the at least one input field. 3. The method of claim 1 , wherein the method further comprises transmitting a query to the second information location with whose second information page the input field is associated, the query including one or more query parameters, and the one or more query parameters including at least one value input through the at least one input field. | 0.717213 |
8,065,292 | 8 | 9 | 8. The method as claimed in claim 7 , wherein the traffic statistics include a number of times a website associated with the URL has been accessed, wherein search results associated with the search engine index includes information about multiple websites, and wherein the search results are ranked at least according to the number of times each of the multiple websites is accessed. | 8. The method as claimed in claim 7 , wherein the traffic statistics include a number of times a website associated with the URL has been accessed, wherein search results associated with the search engine index includes information about multiple websites, and wherein the search results are ranked at least according to the number of times each of the multiple websites is accessed. 9. The method as claimed in claim 8 , wherein the search results are further ranked according to algorithmic weightings. | 0.966574 |
8,244,709 | 7 | 8 | 7. The computer-implemented method of claim 1 , wherein the at least one data item is linked to a web page. | 7. The computer-implemented method of claim 1 , wherein the at least one data item is linked to a web page. 8. The computer-implemented method of claim 7 , further comprising displaying contents of the web page via a user device. | 0.931172 |
7,660,791 | 13 | 14 | 13. A system for providing a document relevance determination to a selected category for a document contained within a linked network of documents, wherein the system is implemented utilizing a processor that executes instructions from a computer-storage medium, the network represented by a network map including nodes representing documents and edges representing links between the documents, the system comprising: a category determination component for identifying each node in the network map known to belong to the selected category, identifying each node known to be outside of the selected category, and identifying nodes having an unknown category; an initial weight assignment component for assigning a category rank based on the node category identification, wherein each node known to belong to the selected category receives a weight of 1, each node having an unknown category receives a weight of 1 divided by the total number of documents having an unknown category and documents known to be outside the selected category, and each node known to be outside of the selected category receives a weight of 0, and wherein further the three components can be scaled by a scaling factor; a link locator for identifying each link from each node and each link to each node and assigning link weights based on the identified links; and a relevance determination component for determining node relevance to the selected category based on the assigned category rank and the assigned link weights. | 13. A system for providing a document relevance determination to a selected category for a document contained within a linked network of documents, wherein the system is implemented utilizing a processor that executes instructions from a computer-storage medium, the network represented by a network map including nodes representing documents and edges representing links between the documents, the system comprising: a category determination component for identifying each node in the network map known to belong to the selected category, identifying each node known to be outside of the selected category, and identifying nodes having an unknown category; an initial weight assignment component for assigning a category rank based on the node category identification, wherein each node known to belong to the selected category receives a weight of 1, each node having an unknown category receives a weight of 1 divided by the total number of documents having an unknown category and documents known to be outside the selected category, and each node known to be outside of the selected category receives a weight of 0, and wherein further the three components can be scaled by a scaling factor; a link locator for identifying each link from each node and each link to each node and assigning link weights based on the identified links; and a relevance determination component for determining node relevance to the selected category based on the assigned category rank and the assigned link weights. 14. The system of claim 13 , further comprising a domain determination component for identifying an origination domain and a destination domain for each link. | 0.771676 |
7,529,852 | 27 | 28 | 27. A computer program product as recited in claim 26 , wherein when (i) a valid IPv6 reply is not received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, (ii) a “no answer” IPv6 reply having an IP6.INT string is only received from the IPv6 DNS Server in response to the first IPv6 query having the IP6.INT string and (iii) the timer has not expired, translating the “no answer” IPv6 reply having the IP6.INT string into an IPv4 reply having the IP-ADDR.ARPA string. | 27. A computer program product as recited in claim 26 , wherein when (i) a valid IPv6 reply is not received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, (ii) a “no answer” IPv6 reply having an IP6.INT string is only received from the IPv6 DNS Server in response to the first IPv6 query having the IP6.INT string and (iii) the timer has not expired, translating the “no answer” IPv6 reply having the IP6.INT string into an IPv4 reply having the IP-ADDR.ARPA string. 28. A computer program product as recited in claim 27 , wherein when (i) a valid IPv6 reply is not received from the IPv6 DNS Server in response to either the second IPv6 query having the IP6.ARPA string or the first IPv6 query having the IP6.INT string, (ii) a “no answer” IPv6 reply having an IP6.ARPA is only received from the IPv6 DNS Server in response to the second IPv6 query having the IP6.ARPA and (iii) the timer has not expired, translating the “no answer” IPv6 reply having an IP6.ARPA into an IPv4 reply having the IP-ADDR.ARPA string. | 0.85245 |
8,560,297 | 9 | 12 | 9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs. | 9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs. 12. The computing apparatus of claim 9 , wherein the first electronic document and the second electronic document are a first web page and a second web page, respectively. | 0.881085 |
8,073,893 | 60 | 61 | 60. The article of claim 59 , wherein said machine-readable instructions are further executable by said computing platform to: represent said signs of differences as 2's-complement binary expressions in registers; and shift bits in at least some of said registers. | 60. The article of claim 59 , wherein said machine-readable instructions are further executable by said computing platform to: represent said signs of differences as 2's-complement binary expressions in registers; and shift bits in at least some of said registers. 61. The article of claim 60 , wherein said machine-readable instructions are further executable by said computing platform to shift said bits by a number of bit positions based, at least in part, on a significance of differences represented in said registers. | 0.904499 |
8,423,362 | 13 | 16 | 13. A method of circumstantial speech recognition in a vehicle based on user interactivity with the vehicle, the method comprising the steps of: monitoring a plurality of different vehicle devices for interaction by a user using at least one processor located in the vehicle; and then identifying a vehicle device for user-intended automatic speech recognition (ASR) control based on user interaction with the vehicle device; and then receiving speech from the user via a microphone located in the vehicle, the received speech being received within an elapsed time following the user interaction; and disambiguating between two or more possible commands contained in the speech based at least in part on the user interaction with the identified vehicle device. | 13. A method of circumstantial speech recognition in a vehicle based on user interactivity with the vehicle, the method comprising the steps of: monitoring a plurality of different vehicle devices for interaction by a user using at least one processor located in the vehicle; and then identifying a vehicle device for user-intended automatic speech recognition (ASR) control based on user interaction with the vehicle device; and then receiving speech from the user via a microphone located in the vehicle, the received speech being received within an elapsed time following the user interaction; and disambiguating between two or more possible commands contained in the speech based at least in part on the user interaction with the identified vehicle device. 16. The method set forth in claim 13 , further comprising the step of controlling the identified vehicle device using the recognized speech data. | 0.763072 |
9,442,928 | 19 | 23 | 19. The computer-implemented method according to claim 1 further comprising: a computer-implemented data processing method for performing the automated workflow process of improving accuracy of computerized topic identification on the at least one content document comprising: f) receiving, by the at least one computer processor, the at least one content document; g) processing, by the at least one computer processor, the at least one content document according to said (a) through said (f) to analyze at least one topic, said processing comprising at least one of: organizing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; discovering, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; indexing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; searching, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; linking, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; tagging, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; filtering, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; prioritizing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; or ranking, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; and h) taking action, by the at least one computer processor, on the at least one content document, based on the at least one topic analyzed. | 19. The computer-implemented method according to claim 1 further comprising: a computer-implemented data processing method for performing the automated workflow process of improving accuracy of computerized topic identification on the at least one content document comprising: f) receiving, by the at least one computer processor, the at least one content document; g) processing, by the at least one computer processor, the at least one content document according to said (a) through said (f) to analyze at least one topic, said processing comprising at least one of: organizing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; discovering, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; indexing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; searching, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; linking, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; tagging, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; filtering, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; prioritizing, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; or ranking, by the at least one computer processor, the at least one content document, which is determined to be associated with the at least one content document; and h) taking action, by the at least one computer processor, on the at least one content document, based on the at least one topic analyzed. 23. The method according to claim 19 , wherein the at least one content document comprises text content. | 0.989281 |
8,527,281 | 11 | 15 | 11. A method as in claim 10 , wherein performing an editing function includes changing at least one or more parameters of a target-cost function. | 11. A method as in claim 10 , wherein performing an editing function includes changing at least one or more parameters of a target-cost function. 15. A method as in claim 11 , wherein the step of pruning comprises defining a pruning threshold having regard to a reference phonetic-unit. | 0.920455 |
9,912,775 | 1 | 2 | 1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device. | 1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device. 2. The machine-readable medium of claim 1 , wherein determining that the communication message is to be transmitted comprises: comparing a type of communication message permitted for transmittal to the secondary computing device, according to the message mode, with the type of the received communication message. | 0.634346 |
8,467,716 | 1 | 3 | 1. A processor-implemented method to build a trait model for essay evaluation, comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. | 1. A processor-implemented method to build a trait model for essay evaluation, comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. 3. The method of claim 1 , wherein the received at least one evaluated essay discusses one or more topics. | 0.958366 |
9,147,393 | 13 | 14 | 13. The method of claim 12 wherein step (c) comprises using adjacent pairs of syllable schemata in the schemata list to access a database and retrieving blended syllable schemata. | 13. The method of claim 12 wherein step (c) comprises using adjacent pairs of syllable schemata in the schemata list to access a database and retrieving blended syllable schemata. 14. The method of claim 13 wherein identified primary and secondary figure words are used to block or limit replacement of located pairs with blended syllable schemata. | 0.896806 |
9,256,676 | 1 | 6 | 1. A method of presenting computer-generated search result information, comprising: receiving a search request from a first user; obtaining a plurality of search results, wherein each search result identifies a respective search result document responsive to the search request; determining an initial ranking of the plurality of search results; determining that one or more particular web notebooks each have a respective title that matches the search request and that a particular search result document corresponding to a particular search result has document content related to respective notebook content in the one or more particular web notebooks of a plurality of web notebooks, wherein each web notebook has an author, the first user is not the author of any of the one or more particular web notebooks, and the related notebook content in each of the plurality of web notebooks includes web clippings taken by the author of the respective web notebook, wherein each of the web clippings is a snippet or a portion of a web document added to the respective web notebook by the author of the respective web notebook; modifying the ranking of the plurality of search results including modifying the ranking of the particular search result based on a web notebook based ranker and using the content from the one or more particular web notebooks; and providing a response to the search request including the plurality of search results for presentation in an order based on the modified ranking. | 1. A method of presenting computer-generated search result information, comprising: receiving a search request from a first user; obtaining a plurality of search results, wherein each search result identifies a respective search result document responsive to the search request; determining an initial ranking of the plurality of search results; determining that one or more particular web notebooks each have a respective title that matches the search request and that a particular search result document corresponding to a particular search result has document content related to respective notebook content in the one or more particular web notebooks of a plurality of web notebooks, wherein each web notebook has an author, the first user is not the author of any of the one or more particular web notebooks, and the related notebook content in each of the plurality of web notebooks includes web clippings taken by the author of the respective web notebook, wherein each of the web clippings is a snippet or a portion of a web document added to the respective web notebook by the author of the respective web notebook; modifying the ranking of the plurality of search results including modifying the ranking of the particular search result based on a web notebook based ranker and using the content from the one or more particular web notebooks; and providing a response to the search request including the plurality of search results for presentation in an order based on the modified ranking. 6. The method of claim 1 , further comprising generating snippet information by identifying portions of search result documents that have been referenced in the plurality of web notebooks, and providing the snippet information with the search results. | 0.682278 |
7,475,337 | 2 | 3 | 2. The method of claim 1 , wherein the modified output presentation further includes the displayable objects, each of the displayable objects being modified in accordance with the at least one of the definitions in the definition file. | 2. The method of claim 1 , wherein the modified output presentation further includes the displayable objects, each of the displayable objects being modified in accordance with the at least one of the definitions in the definition file. 3. The method of claim 2 further comprising: converting the output presentation to a markup language file in accordance with a set of mapping rules. | 0.946338 |
9,087,396 | 1 | 10 | 1. A method comprising: determining, with a processing unit that has received a digital image, a brightness of an area of the digital image, the area being designated as an area upon which text is to be added to the digital image; selecting, with the processing unit, a color of the text based upon the determined brightness; adding, with the processing unit, a semi-transparent mask layer to the digital image, wherein a colored portion of the semi-transparent mask layer follows an outline of individual characters of the text being added to the digital image; and adding the text, to be outlined by the coloration of the semi-transparent mask layer, to the digital image with the processing unit. | 1. A method comprising: determining, with a processing unit that has received a digital image, a brightness of an area of the digital image, the area being designated as an area upon which text is to be added to the digital image; selecting, with the processing unit, a color of the text based upon the determined brightness; adding, with the processing unit, a semi-transparent mask layer to the digital image, wherein a colored portion of the semi-transparent mask layer follows an outline of individual characters of the text being added to the digital image; and adding the text, to be outlined by the coloration of the semi-transparent mask layer, to the digital image with the processing unit. 10. The method of claim 1 , wherein the semi-transparent mask layer has an opacity of between 10% and 20%. | 0.897881 |
8,760,451 | 30 | 42 | 30. A method of creating a text string lookup table, comprising: storing, in a computer memory at memory positions defining the text string lookup table, a set of glyphs, wherein each glyph is stored as a field of pixels defining a displayable image associated with a text character such that multiple pixels are stored in the memory for each glyph; and storing, in the computer memory at memory positions defining the text string lookup table, one or more sections of encoding data, wherein each section of encoding data defines a text string of two or more text characters to be rendered in an image and wherein each section of encoding data includes two or more sets of character encoding data with each set of character encoding data defining a text character of the text string and including first encoding data defining information about a position of a text character in the text string from which the center position of the text character can be determined and second encoding data defining a reference to one of the glyphs to define the identity of the text character in the text string. | 30. A method of creating a text string lookup table, comprising: storing, in a computer memory at memory positions defining the text string lookup table, a set of glyphs, wherein each glyph is stored as a field of pixels defining a displayable image associated with a text character such that multiple pixels are stored in the memory for each glyph; and storing, in the computer memory at memory positions defining the text string lookup table, one or more sections of encoding data, wherein each section of encoding data defines a text string of two or more text characters to be rendered in an image and wherein each section of encoding data includes two or more sets of character encoding data with each set of character encoding data defining a text character of the text string and including first encoding data defining information about a position of a text character in the text string from which the center position of the text character can be determined and second encoding data defining a reference to one of the glyphs to define the identity of the text character in the text string. 42. The method of claim 30 , including storing first encoding data for at least one text character in a first one of the lines of sets of character encoding data in a column that overlaps with a column for a different text character in a second one of the lines of sets of character encoding data. | 0.890487 |
7,761,843 | 29 | 42 | 29. A tangible computer-readable medium having computer-executable instructions for implementing a method of creating computer code for a target programming language, the computer executable instructions comprising instructions for: defining a programming command as a predefined command sentence comprising at least one constant word and at least one enterable word, wherein the predefined command sentence comprises a structure other than a syntax of the target programming language and wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command; receiving data relating to an input value for the enterable word; and converting the predefined command sentence and the input value for the enterable word into a completed programming command. | 29. A tangible computer-readable medium having computer-executable instructions for implementing a method of creating computer code for a target programming language, the computer executable instructions comprising instructions for: defining a programming command as a predefined command sentence comprising at least one constant word and at least one enterable word, wherein the predefined command sentence comprises a structure other than a syntax of the target programming language and wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command; receiving data relating to an input value for the enterable word; and converting the predefined command sentence and the input value for the enterable word into a completed programming command. 42. The tangible computer-readable medium having computer-executable instructions of claim 29 wherein the enterable word comprises a list word comprising two or more options, and wherein the input value comprises an option selected from the list word. | 0.842535 |
9,256,580 | 5 | 7 | 5. A computer-readable memory storing instructions that, when executed by a computing device, cause the computing device to perform gesture recognition operations, comprising: receiving, via a virtual keyboard interface, a continuous stroke from a user, wherein the continuous stroke comprises a start-point and an end-point; determining a most probable candidate word based at least in part on the received continuous stroke from the user; and displaying, over the virtual keyboard interface, a representation of the determined most probable candidate word, wherein the representation of the determined most probable candidate word is displayed to appear over the virtual keyboard and at a particular location selected based at least in part on the continuous stroke end-point. | 5. A computer-readable memory storing instructions that, when executed by a computing device, cause the computing device to perform gesture recognition operations, comprising: receiving, via a virtual keyboard interface, a continuous stroke from a user, wherein the continuous stroke comprises a start-point and an end-point; determining a most probable candidate word based at least in part on the received continuous stroke from the user; and displaying, over the virtual keyboard interface, a representation of the determined most probable candidate word, wherein the representation of the determined most probable candidate word is displayed to appear over the virtual keyboard and at a particular location selected based at least in part on the continuous stroke end-point. 7. The computer-readable memory of claim 5 further storing instructions that, when executed by the computing device, cause the computing device to perform further operations comprising: comparing the received continuous stroke to a set of template patterns such that a n-best list of possible matching template patterns are selected; wherein the determining a most probable candidate word is performed by determining a best-match from among the n-best list of possible matching template patterns. | 0.785467 |
8,312,041 | 11 | 13 | 11. An RDF (Resource Description Framework) network construction method using an ontology schema, comprising: using an ontology schema storing module that stores the ontology schema defining a relationship system between concepts in a domain, using a class managing module that connects and stores, in a set, authority data composed of classes corresponding to the concepts of the ontology schema, terms classified by the classes, identifiers of the terms, representative terms, and identifier of the representative terms, wherein the representative terms comprises terms that represent corresponding characteristic of the concepts, using a mining rule managing module that connects and stores, in a set, properties of the ontology schema, one or more mining patterns corresponding to the properties, and one or more RDF triples corresponding to the mining patterns, wherein each RDF triple comprises of a subject, an object, and a relationship between the subject and the object, wherein the ontology schema storing module, the class managing module, and the mining rule managing module being linked with each other, and the method further comprising: recognizing terms from an input text document and representing the recognized terms into the classes stored in the class managing module and the properties representing relationships of the classes; converting the input text document represented by the classes and the properties into mining patterns; searching same mining patterns by comparing the mining patterns stored in the mining rule managing module and the mining patterns of the text document, in link with the mining rule managing module; and determining an RDF triple corresponding to the searched mining patterns, and wherein the determining of an RDF triple corresponding to the searched mining patterns includes: determining a class-based RDF triple composed of classes and properties corresponding to the same mining patterns of the mining pattern managing module, on the basis of the result of comparing mining patterns; creating a term-based RDF triple composed of terms and properties by converting the classes of the class-based RDF triple into the corresponding terms, in link with the class managing module; and creating an identifier-based RDF tripe composed of identifiers and properties by converting the terms of the term-based RDF triple into the identifiers of the terms, in link with the class managing module. | 11. An RDF (Resource Description Framework) network construction method using an ontology schema, comprising: using an ontology schema storing module that stores the ontology schema defining a relationship system between concepts in a domain, using a class managing module that connects and stores, in a set, authority data composed of classes corresponding to the concepts of the ontology schema, terms classified by the classes, identifiers of the terms, representative terms, and identifier of the representative terms, wherein the representative terms comprises terms that represent corresponding characteristic of the concepts, using a mining rule managing module that connects and stores, in a set, properties of the ontology schema, one or more mining patterns corresponding to the properties, and one or more RDF triples corresponding to the mining patterns, wherein each RDF triple comprises of a subject, an object, and a relationship between the subject and the object, wherein the ontology schema storing module, the class managing module, and the mining rule managing module being linked with each other, and the method further comprising: recognizing terms from an input text document and representing the recognized terms into the classes stored in the class managing module and the properties representing relationships of the classes; converting the input text document represented by the classes and the properties into mining patterns; searching same mining patterns by comparing the mining patterns stored in the mining rule managing module and the mining patterns of the text document, in link with the mining rule managing module; and determining an RDF triple corresponding to the searched mining patterns, and wherein the determining of an RDF triple corresponding to the searched mining patterns includes: determining a class-based RDF triple composed of classes and properties corresponding to the same mining patterns of the mining pattern managing module, on the basis of the result of comparing mining patterns; creating a term-based RDF triple composed of terms and properties by converting the classes of the class-based RDF triple into the corresponding terms, in link with the class managing module; and creating an identifier-based RDF tripe composed of identifiers and properties by converting the terms of the term-based RDF triple into the identifiers of the terms, in link with the class managing module. 13. The RDF network construction method according to claim 11 , wherein the recognizing terms from the input text document and representing the terms into classes stored in the class managing module and properties representing relationships of the classes, includes: recognizing the terms from the input text document; searching classes corresponding to the recognized terms by using the class managing module; searching properties of the ontology schema by using concepts corresponding to the classes of the class managing module; and representing relationships of the classes by using the searched properties. | 0.816517 |
9,846,806 | 6 | 7 | 6. The method of claim 4 , wherein the first set of imaging data comprises at least one image of the object, wherein the at least one visual cue is expressed within the at least one image of the object. | 6. The method of claim 4 , wherein the first set of imaging data comprises at least one image of the object, wherein the at least one visual cue is expressed within the at least one image of the object. 7. The method of claim 6 , further comprising: presenting, by at least one human, at least one of the object or the at least one visual cue within a field of view of the at least one imaging device at a first time, wherein the at least one image is captured by the at least one imaging device at the first time. | 0.94049 |
7,610,546 | 14 | 17 | 14. A document processing method comprising: detecting video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; generating a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; selecting video data in accordance with said detected video data designation information; storing a categorization model including a plurality of data categories; creating an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; updating the categorization model with the automatic categorization; controlling an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; controlling an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; controlling an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. | 14. A document processing method comprising: detecting video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; generating a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; selecting video data in accordance with said detected video data designation information; storing a categorization model including a plurality of data categories; creating an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; updating the categorization model with the automatic categorization; controlling an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; controlling an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; controlling an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. 17. The document processing method of claim 14 , wherein said video data is motion image data. | 0.931587 |
9,646,000 | 28 | 29 | 28. A search method comprising: inputting a keyword, wherein the keyword is generated by request information; and conducting a full-text search in a structured database according to the keyword, wherein the structured database stores at least one record, each of the at least one record comprises at least one field, and data stored in the at least one field collectively describe attributes of the at least one record, wherein when the at least one record stored in the structured database matches the keyword, indication data corresponding to the at least one field are output as recognition of an intention included in the request information, wherein the at least one field comprises at least one sub-field, each of the at least one sub-field at least consists of an indication field and a value field, the indication field stores indication data consisting of at least one letter of alphabet, and the value field stores value data consisting of at least one of at least one letter of alphabet, at least one comma and at least one number. | 28. A search method comprising: inputting a keyword, wherein the keyword is generated by request information; and conducting a full-text search in a structured database according to the keyword, wherein the structured database stores at least one record, each of the at least one record comprises at least one field, and data stored in the at least one field collectively describe attributes of the at least one record, wherein when the at least one record stored in the structured database matches the keyword, indication data corresponding to the at least one field are output as recognition of an intention included in the request information, wherein the at least one field comprises at least one sub-field, each of the at least one sub-field at least consists of an indication field and a value field, the indication field stores indication data consisting of at least one letter of alphabet, and the value field stores value data consisting of at least one of at least one letter of alphabet, at least one comma and at least one number. 29. The search method as recited in claim 28 , wherein the full-text search is conducted by matching the keyword with the value data. | 0.805556 |
9,626,429 | 17 | 23 | 17. A computer program product, tangibly embodied in a non-transitory computer-readable storage medium, the computer program product including instructions operable to cause a data processing apparatus of a client user input device to perform a method comprising: storing a local primary vocabulary at the client device, wherein the local primary vocabulary pertains to any of a language, a subject matter, a functional purpose, or a content; receiving a sequence of one or more symbols from a user through entry of a sequence of keypresses by the user; transmitting at least a most recent portion of the sequence over a network after each of the keypresses; updating the locally stored primary vocabulary from a corresponding remote vocabulary of a plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, when the transmitted portion of the sequence includes one or more words that overlaps both the corresponding remote vocabulary and the locally stored primary vocabulary; receiving a new vocabulary of the plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, wherein the new vocabulary pertains to a topic, when the new vocabulary includes a plurality of words that correspond to the topic, and wherein the transmitted most recent portion of the sequence includes one or more words that overlap the vocabulary, such that the new vocabulary has associated therewith a measure of confidence above a prescribed threshold with respect to the transmitted most recent portion of the sequence, wherein the transmitted most recent portion of the sequence significantly overlaps the new vocabulary while lacking significant overlaps with the locally stored primary vocabulary and others of the plurality of remote vocabularies, wherein receiving the new vocabulary comprises receiving a notice over the network that the new vocabulary is available that pertains to the transmitted sequence, and downloading the new vocabulary over the network in response to the received notice; locally storing the received new vocabulary at the client device; receiving text entered by the user; and for the received text, using the updated locally stored primary vocabulary or the locally stored new vocabulary for any of word prediction, completion, or word correction. | 17. A computer program product, tangibly embodied in a non-transitory computer-readable storage medium, the computer program product including instructions operable to cause a data processing apparatus of a client user input device to perform a method comprising: storing a local primary vocabulary at the client device, wherein the local primary vocabulary pertains to any of a language, a subject matter, a functional purpose, or a content; receiving a sequence of one or more symbols from a user through entry of a sequence of keypresses by the user; transmitting at least a most recent portion of the sequence over a network after each of the keypresses; updating the locally stored primary vocabulary from a corresponding remote vocabulary of a plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, when the transmitted portion of the sequence includes one or more words that overlaps both the corresponding remote vocabulary and the locally stored primary vocabulary; receiving a new vocabulary of the plurality of remote vocabularies over the network that pertains to the transmitted most recent portion of the sequence after each of the keypresses, wherein the new vocabulary pertains to a topic, when the new vocabulary includes a plurality of words that correspond to the topic, and wherein the transmitted most recent portion of the sequence includes one or more words that overlap the vocabulary, such that the new vocabulary has associated therewith a measure of confidence above a prescribed threshold with respect to the transmitted most recent portion of the sequence, wherein the transmitted most recent portion of the sequence significantly overlaps the new vocabulary while lacking significant overlaps with the locally stored primary vocabulary and others of the plurality of remote vocabularies, wherein receiving the new vocabulary comprises receiving a notice over the network that the new vocabulary is available that pertains to the transmitted sequence, and downloading the new vocabulary over the network in response to the received notice; locally storing the received new vocabulary at the client device; receiving text entered by the user; and for the received text, using the updated locally stored primary vocabulary or the locally stored new vocabulary for any of word prediction, completion, or word correction. 23. The computer program product of claim 17 , wherein the method further comprises: transmitting an opt-in or acceptance from the user over the network to receive a new vocabulary that includes or is dedicated to profanity; wherein the received new vocabulary includes or is dedicated to profanity; such that the received new vocabulary is only received by the user if wanted by the user, and is not received by the user if the new vocabulary is unwanted by the user. | 0.501066 |
9,666,182 | 1 | 8 | 1. A method comprising: performing, via a processor, automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting, via the processor, a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances. | 1. A method comprising: performing, via a processor, automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting, via the processor, a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances. 8. The method of claim 1 , wherein the language model is further based on the bootstrap model. | 0.911985 |
7,657,005 | 5 | 6 | 5. The method of claim 4 , further comprising populating a name field at a graphical user interface of the service agent terminal with the caller name when the probability that the title and the caller name are correct is above the predetermined threshold. | 5. The method of claim 4 , further comprising populating a name field at a graphical user interface of the service agent terminal with the caller name when the probability that the title and the caller name are correct is above the predetermined threshold. 6. The method of claim 5 , further comprising populating a title field at the graphical user interface with the title of the caller. | 0.957692 |
8,150,842 | 1 | 7 | 1. A computer implemented online-content management method, comprising: receiving at one or more first computers a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) scores of online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be; and in response to a query for online content received from a second computer, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. | 1. A computer implemented online-content management method, comprising: receiving at one or more first computers a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) scores of online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be; and in response to a query for online content received from a second computer, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. 7. The method of claim 1 , wherein the online content item corresponding to the author is about a first topic and the reputation score is further based on a previous reputation score of the author calculated in relation to one or more different online content items of the author also about the first topic that were previously published. | 0.697133 |
8,037,041 | 3 | 4 | 3. The method of claim 1 , further comprising, prior to said submitting, determining by the computing device whether a connection to the search facility is available. | 3. The method of claim 1 , further comprising, prior to said submitting, determining by the computing device whether a connection to the search facility is available. 4. The method of claim 3 , further comprising, in response to determining that the connection is not available, waiting until the connection becomes available and performing said submitting when the connection is available. | 0.922191 |
8,910,120 | 17 | 18 | 17. The process of claim 16 , further comprising the actions of: for each of the identified software bug descriptions in the database that are deemed to be similar to the prescribed degree to the software bug description query, performing a link analysis on the relationship model to identify contextually relevant information associated with the software bug description under consideration, and outputting the identified contextually relevant information associated with the software bug description under consideration. | 17. The process of claim 16 , further comprising the actions of: for each of the identified software bug descriptions in the database that are deemed to be similar to the prescribed degree to the software bug description query, performing a link analysis on the relationship model to identify contextually relevant information associated with the software bug description under consideration, and outputting the identified contextually relevant information associated with the software bug description under consideration. 18. The process of claim 17 , wherein the relationship model is a weighted multipartite relationship graph, and wherein the process action of performing the link analysis on the relationship model, comprises an action of performing a random walk technique to identify associations between ones of items of the contextually relevant information and ones of the software bug descriptions that exceed a prescribed probability level based on the graph weights. | 0.907618 |
6,138,089 | 7 | 9 | 7. A speech processor for processing a speech signal, said speech processor comprising: a plurality of delay circuits, each receiving said speech signal f(t) as an input and generating a different time delayed version of said speech signal f(t-Td.sub.i) as an output; a plurality of correlator circuits, each said correlator circuit receiving said input speech signal f(t) and one of said time delayed speech signals f(t-Td.sub.i) and generating a correlation value indicating the amount of correlation between said speech signal f(t) and said time delayed speech signal; a comparator circuit receiving said plurality of correlation values and generating an autocorrelation of said input signal with time delayed versions of said speech signal, one correlation value being received from each of said correlator circuits; a pitch detector receiving said autocorrelation signal and identifying a pitch length for at least a portion of said speech signal; and an encoder receiving said pitch length and said speech signal and generating an encoded version of said speech signal wherein speech pitches of said speech signal are retained or omitted on the basis of said pitch detector input. | 7. A speech processor for processing a speech signal, said speech processor comprising: a plurality of delay circuits, each receiving said speech signal f(t) as an input and generating a different time delayed version of said speech signal f(t-Td.sub.i) as an output; a plurality of correlator circuits, each said correlator circuit receiving said input speech signal f(t) and one of said time delayed speech signals f(t-Td.sub.i) and generating a correlation value indicating the amount of correlation between said speech signal f(t) and said time delayed speech signal; a comparator circuit receiving said plurality of correlation values and generating an autocorrelation of said input signal with time delayed versions of said speech signal, one correlation value being received from each of said correlator circuits; a pitch detector receiving said autocorrelation signal and identifying a pitch length for at least a portion of said speech signal; and an encoder receiving said pitch length and said speech signal and generating an encoded version of said speech signal wherein speech pitches of said speech signal are retained or omitted on the basis of said pitch detector input. 9. The speech processor in claim 7, further comprising: a pitch counter circuit which compares the values of the auto-correlation function for a sequence of pitches and determines when the autocorrelation value crosses some predetermined threshold, a new reference pitch being inserted in said encoded signal when said value of said auto-correlation function drops below said threshold. | 0.921957 |
8,127,336 | 1 | 2 | 1. A system for policy-based service management, comprising: a hardware device including a rules definition interface module configured to receive a plurality of rule definitions stored in a data storage, wherein a rule definition includes a condition containing a rule definition variable; a policy management interface module configured to allow a user to define a rule instance from a rule definition and to define a policy instance based on one or more defined rule instances, wherein the user defines the rule instance by associating the condition in the rule definition containing the rule definition variable with one or more values in a user-defined value set; and a policy decision interface module configured to evaluate the policy instance upon request, for access to a network or a network resource by a subscriber device, wherein the policy decision interface is configured to retrieve one or more rule instances associated with the policy instance and to substitute one or more values in the user-defined value set associated with each variable in the rule instance in real-time when the rule instance is being evaluated by the policy decision interface module. | 1. A system for policy-based service management, comprising: a hardware device including a rules definition interface module configured to receive a plurality of rule definitions stored in a data storage, wherein a rule definition includes a condition containing a rule definition variable; a policy management interface module configured to allow a user to define a rule instance from a rule definition and to define a policy instance based on one or more defined rule instances, wherein the user defines the rule instance by associating the condition in the rule definition containing the rule definition variable with one or more values in a user-defined value set; and a policy decision interface module configured to evaluate the policy instance upon request, for access to a network or a network resource by a subscriber device, wherein the policy decision interface is configured to retrieve one or more rule instances associated with the policy instance and to substitute one or more values in the user-defined value set associated with each variable in the rule instance in real-time when the rule instance is being evaluated by the policy decision interface module. 2. The system of claim 1 , further comprising: a rule repository configured to store the plurality of rule definitions. | 0.850877 |
7,493,333 | 23 | 35 | 23. A computer-implemented method for parsing and exporting data from one or more multi-relational ontologies, the method comprising: selecting two or more concepts from one or more master multi-relational ontologies, wherein the one or more master ontologies include a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of individual assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of the individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; applying one or more path-finding constraints to the two or more concepts to produce a subset of individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts; and selecting a starting concept from the subset of individual assertions; applying one or more expansion parameters to the starting concept to yield a redacted subset of individual assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of individual assertions includes at least one assertion that includes the starting concept; outputting the redacted subset of individual assertions to a predetermined location in a predetermined format. | 23. A computer-implemented method for parsing and exporting data from one or more multi-relational ontologies, the method comprising: selecting two or more concepts from one or more master multi-relational ontologies, wherein the one or more master ontologies include a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of individual assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of the individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; applying one or more path-finding constraints to the two or more concepts to produce a subset of individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts; and selecting a starting concept from the subset of individual assertions; applying one or more expansion parameters to the starting concept to yield a redacted subset of individual assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of individual assertions includes at least one assertion that includes the starting concept; outputting the redacted subset of individual assertions to a predetermined location in a predetermined format. 35. The method of claim 23 , wherein one or more of the path-finding constraints or the expansion parameters include user access rights, such that one or more of the subset of individual assertions or the redacted subset of individual assertions include only assertions to which a particular user is permitted access. | 0.831023 |
9,342,836 | 1 | 2 | 1. A computer implemented method in a host organization, the method comprising: generating, by using a computer system, indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database of the host organization; exposing the database of the host organization via a request interface; receiving, at the request interface, a query for the database specifying at least (i) a PREDICT command term, (ii) one or more specified columns to be predicted, and (iii) one or more column name=value pairs specifying column names to be fixed and corresponding values by which to fix the column names; and querying the database using the PREDICT command term and passing the one or more specified columns to be predicted and the one or more column name=value pairs to generate a representation of a joint conditional distribution of the one or more specified columns to be predicted fixed according to the column name=value pairs using the indices stored in the database, wherein querying the database using the PREDICT command term comprises passing a JavaScript Object Notation (JSON) structured query to the database, the JSON structured query having a query syntax of: the PREDICT command term as a required term; required specification of the one or more specified columns to be predicted; the required specification of the column names to be fixed and the values by which to fix the column names as the one or more column name=value pairs restricting output of the query to a predictive record set having returned elements that are probabilistically related to the one or more columns to be fixed and the corresponding values by which to fix the column names as specified via the one or more column name=value pairs; and an optional specification of one or more tables, datasets, data sources, and indices to be queried. | 1. A computer implemented method in a host organization, the method comprising: generating, by using a computer system, indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database of the host organization; exposing the database of the host organization via a request interface; receiving, at the request interface, a query for the database specifying at least (i) a PREDICT command term, (ii) one or more specified columns to be predicted, and (iii) one or more column name=value pairs specifying column names to be fixed and corresponding values by which to fix the column names; and querying the database using the PREDICT command term and passing the one or more specified columns to be predicted and the one or more column name=value pairs to generate a representation of a joint conditional distribution of the one or more specified columns to be predicted fixed according to the column name=value pairs using the indices stored in the database, wherein querying the database using the PREDICT command term comprises passing a JavaScript Object Notation (JSON) structured query to the database, the JSON structured query having a query syntax of: the PREDICT command term as a required term; required specification of the one or more specified columns to be predicted; the required specification of the column names to be fixed and the values by which to fix the column names as the one or more column name=value pairs restricting output of the query to a predictive record set having returned elements that are probabilistically related to the one or more columns to be fixed and the corresponding values by which to fix the column names as specified via the one or more column name=value pairs; and an optional specification of one or more tables, datasets, data sources, and indices to be queried. 2. The method of claim 1 , further comprising: generating a predictive record set responsive to the querying; wherein the predictive record set comprises a plurality of elements therein, each element of the elements specifying a value for each specified column of the one or more specified columns to be predicted; and returning the predictive record set responsive to the query. | 0.815661 |
8,165,878 | 1 | 2 | 1. A computer system method for matching an utterance of a user to a template comprising the steps of: (a) receiving by a processor the utterance from an input device, wherein the utterance includes at least one word; (b) accessing a set of template hierarchies from a database, wherein the set includes at least one template; (c) comparing by the processor the at least one word of the utterance to the at least one term of a template hierarchy in the set of template hierarchies; (d) determining by the processor whether the at least one word of the utterance matches the at least one term of the template hierarchy; (e) calculating by the processor a score based on the match between the at least one word of the utterance and the at least one term of the template hierarchy; (f) repeating steps (c)-(e) until there are no more words of the utterance for said comparing step; (g) populating the at least one template with at least one data element corresponding to the at least one term of the template hierarchy to obtain a populated template; (h) computing a total score based on the match between all words of the utterance to the populated template; (i) selecting by the processor the at least one template with the highest total score; (j) recording the populated template; and (k) communicating the populated template to the user. | 1. A computer system method for matching an utterance of a user to a template comprising the steps of: (a) receiving by a processor the utterance from an input device, wherein the utterance includes at least one word; (b) accessing a set of template hierarchies from a database, wherein the set includes at least one template; (c) comparing by the processor the at least one word of the utterance to the at least one term of a template hierarchy in the set of template hierarchies; (d) determining by the processor whether the at least one word of the utterance matches the at least one term of the template hierarchy; (e) calculating by the processor a score based on the match between the at least one word of the utterance and the at least one term of the template hierarchy; (f) repeating steps (c)-(e) until there are no more words of the utterance for said comparing step; (g) populating the at least one template with at least one data element corresponding to the at least one term of the template hierarchy to obtain a populated template; (h) computing a total score based on the match between all words of the utterance to the populated template; (i) selecting by the processor the at least one template with the highest total score; (j) recording the populated template; and (k) communicating the populated template to the user. 2. The computer system method of claim 1 wherein the total score determines the generation of at least one selected from the group of a narrative template and a report template. | 0.855863 |
6,122,628 | 26 | 46 | 26. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for representing multidimensional data, said method steps comprising: a) partitioning the multidimensional data into one or more clusters; b) generating and storing clustering information for said one or more clusters; c) generating one or more reduced dimensionality clusters and dimensionality reduction information for said one or more clusters; and d) storing the dimensionality reduction information; e) creating a hierarchy of reduced dimensionality clusters by recursively applying said steps a) through d); and f) generating and storing one or more low-dimensional indexes for clusters at a lowest level of said hierarchy. | 26. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for representing multidimensional data, said method steps comprising: a) partitioning the multidimensional data into one or more clusters; b) generating and storing clustering information for said one or more clusters; c) generating one or more reduced dimensionality clusters and dimensionality reduction information for said one or more clusters; and d) storing the dimensionality reduction information; e) creating a hierarchy of reduced dimensionality clusters by recursively applying said steps a) through d); and f) generating and storing one or more low-dimensional indexes for clusters at a lowest level of said hierarchy. 46. The program storage device of claim 26, for performing a similarity search, further comprising the steps of: reducing the dimensionality of the specified data; recursively applying the steps of: finding the cluster to which reduced dimensionality specified data belongs, using stored clustering information; and reducing the dimensionality of the reduced dimensionality specified data to correspond to a lowest level of a hierarchy of reduced dimensionality clusters, using stored dimensionality reduction information; searching for candidate terminal clusters that can contain one or more of k nearest neighbors of the reduced dimensionality specified data at each level of the hierarchy of reduced dimensionality clusters starting from a terminal cluster at a lowest level of said hierarchy to which the specified data belongs; and for each candidate terminal cluster, performing an intra-cluster search for the k nearest neighbors to the reduced dimensionality specified data. | 0.753387 |
7,656,861 | 9 | 18 | 9. A network processing device, comprising: a processor configured to: convert media signaling into Internet Protocol (IP) media packets; receive text signaling comprising different analog audio tones representing different alpha-numeric characters; identify the alpha-numeric characters represented by the analog audio tones and generate digital values that represent the same identified alpha-numeric characters; formatting the digital values into IP text packets absent analog signaling characteristics describing the audio tones; and sending the IP media packets and the IP text packets in interleaved manner over an IP network using the same real-time IP transport session. | 9. A network processing device, comprising: a processor configured to: convert media signaling into Internet Protocol (IP) media packets; receive text signaling comprising different analog audio tones representing different alpha-numeric characters; identify the alpha-numeric characters represented by the analog audio tones and generate digital values that represent the same identified alpha-numeric characters; formatting the digital values into IP text packets absent analog signaling characteristics describing the audio tones; and sending the IP media packets and the IP text packets in interleaved manner over an IP network using the same real-time IP transport session. 18. The network processing device according to claim 9 wherein the network processing device communicates over an IP network through a gateway. | 0.953298 |
8,406,752 | 1 | 9 | 1. A mobile terminal, comprising: a wireless communication unit configured to wirelessly communicate with at least one other terminal; a touchscreen configured to display an input menu for inputting information, said input menu including at least one input option being displayed as a thumbnail representing input items that can be selected; and a controller configured to receive a first selection signal indicating a selection of the at least one input option, to expand and display in a first display region on the touchscreen the at least one input option so as to display the input items that can be selected, to display in a second display region on the touchscreen at least first and second input fields used when transmitting an input item, to receive a second selection signal indicating an input of the input item to be transmitted to the at least one other terminal into the first input field, to receive a third selection signal indicating a selection of the second input field, and to automatically provide candidate options to be input into the selected second input field based on characteristics of the input item input into the first input field. | 1. A mobile terminal, comprising: a wireless communication unit configured to wirelessly communicate with at least one other terminal; a touchscreen configured to display an input menu for inputting information, said input menu including at least one input option being displayed as a thumbnail representing input items that can be selected; and a controller configured to receive a first selection signal indicating a selection of the at least one input option, to expand and display in a first display region on the touchscreen the at least one input option so as to display the input items that can be selected, to display in a second display region on the touchscreen at least first and second input fields used when transmitting an input item, to receive a second selection signal indicating an input of the input item to be transmitted to the at least one other terminal into the first input field, to receive a third selection signal indicating a selection of the second input field, and to automatically provide candidate options to be input into the selected second input field based on characteristics of the input item input into the first input field. 9. The mobile terminal of claim 1 , wherein when the input item is erroneously input to the second input field, the controller is further configured to automatically input the input item into the correct first input field, extract information corresponding to the input item, and to input the extracted information into the second input field. | 0.703287 |
10,083,249 | 16 | 19 | 16. A non-transitory computer readable medium comprising machine readable instructions which, when executed by a processor, cause a field device integration (FDI) server to at least: collect information from a process control system, the collected information including searchable items associated with a plurality of field devices of the process control system; publish the collected information to a search database maintained by the FDI server; request an update service in response to receiving a search request, the search request including a user search profile and a search query of the searchable items in the search database; collect updated information from the process control system in response to the requested update service; publish the updated collected information to the search database; modify the search query based on the user search profile; search the searchable items based on the modified search query; filter results of the search based on a filter condition included in the user search profile; and return at least a portion of the collected information and the updated collected information based on the user search profile and the filter condition. | 16. A non-transitory computer readable medium comprising machine readable instructions which, when executed by a processor, cause a field device integration (FDI) server to at least: collect information from a process control system, the collected information including searchable items associated with a plurality of field devices of the process control system; publish the collected information to a search database maintained by the FDI server; request an update service in response to receiving a search request, the search request including a user search profile and a search query of the searchable items in the search database; collect updated information from the process control system in response to the requested update service; publish the updated collected information to the search database; modify the search query based on the user search profile; search the searchable items based on the modified search query; filter results of the search based on a filter condition included in the user search profile; and return at least a portion of the collected information and the updated collected information based on the user search profile and the filter condition. 19. The non-transitory computer readable medium as defined in claim 16 , wherein the user search profile includes a user preference for one or more types of search results. | 0.808889 |
9,159,057 | 1 | 11 | 1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; determining that the user has entered a first person in an address field of a new message being composed by the user; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determining that the user entered the first person in the address field, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages. | 1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; determining that the user has entered a first person in an address field of a new message being composed by the user; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determining that the user entered the first person in the address field, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages. 11. The method of claim 1 , wherein the address field is a To: field. | 0.938503 |
8,694,491 | 26 | 37 | 26. A method, comprising: at a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors: accessing Internet usage data for a particular individual computer user, wherein the usage data include a plurality of search queries previously submitted by the particular individual computer user; identifying, without human intervention by the particular individual computer user, from at least some of the Internet usage data, a search query previously submitted by the particular individual computer user that meets one or more predefined query selection criteria; automatically rerunning, without human intervention by the particular individual computer user, the identified search query in its entirety, wherein the identified search query is a search query previously submitted by the particular individual computer user; and sending-at least some search results from the rerun query to a computer associated with the particular individual computer user for display. | 26. A method, comprising: at a computer system having one or more processors and memory storing one or more programs for execution by the one or more processors: accessing Internet usage data for a particular individual computer user, wherein the usage data include a plurality of search queries previously submitted by the particular individual computer user; identifying, without human intervention by the particular individual computer user, from at least some of the Internet usage data, a search query previously submitted by the particular individual computer user that meets one or more predefined query selection criteria; automatically rerunning, without human intervention by the particular individual computer user, the identified search query in its entirety, wherein the identified search query is a search query previously submitted by the particular individual computer user; and sending-at least some search results from the rerun query to a computer associated with the particular individual computer user for display. 37. The method of claim 26 , wherein the plurality of search queries previously submitted includes search queries against a set of document indices, and wherein the identified search query is a search query against an index of documents. | 0.854244 |
9,871,807 | 1 | 6 | 1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. | 1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. 6. The system of claim 1 , wherein the primitive configured for skipping the first predetermined number of bytes to search for the first predetermined pattern is configured to store a size of an array as a variable and use the variable to indicate the first predetermined number of bytes to skip. | 0.821687 |
9,153,142 | 19 | 21 | 19. A non-transitory computer readable storage medium readable by at least one computerized device, said non-transitory computer readable storage medium storing instructions executable by said at least one computerized device to perform a method comprising: displaying on a user interface at least one subject; displaying on said user interface a location for at least one user to enter at least one problem related to said subject; in response to entry of said at least one problem through said user interface, automatically acquiring factors related to said at least one problem from a record associated with said subject, said factors being categorized into dimensions of evidence; automatically generating questions related to said at least one problem and said factors; in response to said questions, automatically generating answers to said questions by referring to sources; for each dimension of evidence, automatically calculating confidence measures of each of said answers; combining said confidence measures of each of said answers for each dimension of evidence in order to calculate final confidence measures of each of said answers; generating a comparative evidence profile and displaying said answers and said final confidence measures for each of said answers with said comparative evidence profile on said user interface, said comparative evidence profile comprising a chart that provides visual indications of relative contributions of each of said dimensions of evidence to each of said final confidence measures of each of said answers and that has selectable features; displaying, on said user interface with said answers, said final confidence measures and said comparative evidence profile, details of said sources and said factors used to generate said; and, upon receiving a selection of one of said selectable features of said chart through said user interface, automatically filtering said details of said sources and said factors so as to limit display of said details. | 19. A non-transitory computer readable storage medium readable by at least one computerized device, said non-transitory computer readable storage medium storing instructions executable by said at least one computerized device to perform a method comprising: displaying on a user interface at least one subject; displaying on said user interface a location for at least one user to enter at least one problem related to said subject; in response to entry of said at least one problem through said user interface, automatically acquiring factors related to said at least one problem from a record associated with said subject, said factors being categorized into dimensions of evidence; automatically generating questions related to said at least one problem and said factors; in response to said questions, automatically generating answers to said questions by referring to sources; for each dimension of evidence, automatically calculating confidence measures of each of said answers; combining said confidence measures of each of said answers for each dimension of evidence in order to calculate final confidence measures of each of said answers; generating a comparative evidence profile and displaying said answers and said final confidence measures for each of said answers with said comparative evidence profile on said user interface, said comparative evidence profile comprising a chart that provides visual indications of relative contributions of each of said dimensions of evidence to each of said final confidence measures of each of said answers and that has selectable features; displaying, on said user interface with said answers, said final confidence measures and said comparative evidence profile, details of said sources and said factors used to generate said; and, upon receiving a selection of one of said selectable features of said chart through said user interface, automatically filtering said details of said sources and said factors so as to limit display of said details. 21. The non-transitory computer readable storage medium according to claim 19 , said sources comprising first sources stored on said at least one computerized storage medium and second sources accessible online and said details of said sources comprising annotations to said sources. | 0.937362 |
8,892,587 | 3 | 4 | 3. The method of claim 1 , wherein the user is provided with a user interface for selecting the one or more configurable bounds. | 3. The method of claim 1 , wherein the user is provided with a user interface for selecting the one or more configurable bounds. 4. The method of claim 3 , wherein the user interface includes information regarding a degree of correct classification associated with a level of the configuration bounds. | 0.944373 |
8,799,210 | 35 | 37 | 35. A computer program product for use with a computer, the computer program product comprising a non-transitory computer usable medium having a computer readable program code embodied therein suitable for use in transition of one or more applications of an organization, the one or more applications being transitioned from a first set of users to a second set of users, the computer readable program code performing: a. generating one or more transition plans for the one or more applications, the one or more transition plans being generated based on information corresponding to the one or more applications, the one or more transition plans comprising one or more transition activities; b. capturing a plurality of knowledge elements corresponding to the one or more applications and the one or more transition activities, wherein the plurality of knowledge elements are captured using one or more knowledge capturing tools and one or more predefined knowledge reference components, and wherein the plurality of knowledge elements comprise a set of source code, a use case, a test case, and an incident resolution; c. associating each of the plurality of knowledge elements corresponding to a particular application with one or more other elements corresponding to said application, wherein the association between the plurality of knowledge elements is established by the first set of users and the second set of users; d. enabling the first set of users to validate the knowledge of the second set of users regarding the plurality of knowledge elements and association between the plurality of knowledge elements, wherein the validation is performed based on a predefined set of rules; and e. providing collaboration between the first set of users and the second set of users, wherein the collaboration enables communication between the first set of users and the second set of users during the transition of the one or more applications. | 35. A computer program product for use with a computer, the computer program product comprising a non-transitory computer usable medium having a computer readable program code embodied therein suitable for use in transition of one or more applications of an organization, the one or more applications being transitioned from a first set of users to a second set of users, the computer readable program code performing: a. generating one or more transition plans for the one or more applications, the one or more transition plans being generated based on information corresponding to the one or more applications, the one or more transition plans comprising one or more transition activities; b. capturing a plurality of knowledge elements corresponding to the one or more applications and the one or more transition activities, wherein the plurality of knowledge elements are captured using one or more knowledge capturing tools and one or more predefined knowledge reference components, and wherein the plurality of knowledge elements comprise a set of source code, a use case, a test case, and an incident resolution; c. associating each of the plurality of knowledge elements corresponding to a particular application with one or more other elements corresponding to said application, wherein the association between the plurality of knowledge elements is established by the first set of users and the second set of users; d. enabling the first set of users to validate the knowledge of the second set of users regarding the plurality of knowledge elements and association between the plurality of knowledge elements, wherein the validation is performed based on a predefined set of rules; and e. providing collaboration between the first set of users and the second set of users, wherein the collaboration enables communication between the first set of users and the second set of users during the transition of the one or more applications. 37. The computer program product of claim 35 further performing storing the plurality of knowledge elements and the information corresponding to the one or more applications. | 0.87798 |
9,141,672 | 26 | 31 | 26. The method of claim 25 , comprising: determining, using the query log data, that the particular search result is one of the search results that were identified using the one or more revised search queries; and in response to determining that the particular search result is one of the search results that were identified using the one or more revised search queries, adjusting a click count for the one or more query term optionalization rules that are specific to the particular query term. | 26. The method of claim 25 , comprising: determining, using the query log data, that the particular search result is one of the search results that were identified using the one or more revised search queries; and in response to determining that the particular search result is one of the search results that were identified using the one or more revised search queries, adjusting a click count for the one or more query term optionalization rules that are specific to the particular query term. 31. The method of claim 26 , comprising associating a first weight with the click count and a second weight with the skip count. | 0.978495 |
8,762,191 | 1 | 6 | 1. A processor implemented method for identifying risk, comprising: receiving information associated with at least one risk for identifying at least one predetermined indicator of risk-relevant information, wherein based on the identifying, the received information is processed to redact redundant information; analyzing, by a processor, the received information to determine relevancy of the information with regard to the at least one risk; tagging, by the processor, the information with at least one risk-relevancy tag based on the determination of the relevancy of the information with regard to the at least one risk; processing the tagged information to remove redundant information and information not deemed to be relevant to the at least one risk, thereby creating the risk-relevant information; parsing, by the processor, the risk-relevant information into a plurality of portions categorized by the at least one risk-relevancy tag; determining, by the processor, a risk-relevancy metric of each of the plurality of portions, wherein the at least one risk-relevancy tag identifies the risk-relevancy metric associated with a relevant portion of the information with respect to the at least one risk, the risk-relevancy metric indicating a likelihood that the relevant portion of the information is relevant to the at least one risk; storing the risk-relevant information in a data storage structure, wherein the data storage structure includes a plurality of areas that are interrelated to facilitate the identification of the at least one risk; and outputting the risk-relevant information stored in the data storage structure to a risk identification graphical user interface. | 1. A processor implemented method for identifying risk, comprising: receiving information associated with at least one risk for identifying at least one predetermined indicator of risk-relevant information, wherein based on the identifying, the received information is processed to redact redundant information; analyzing, by a processor, the received information to determine relevancy of the information with regard to the at least one risk; tagging, by the processor, the information with at least one risk-relevancy tag based on the determination of the relevancy of the information with regard to the at least one risk; processing the tagged information to remove redundant information and information not deemed to be relevant to the at least one risk, thereby creating the risk-relevant information; parsing, by the processor, the risk-relevant information into a plurality of portions categorized by the at least one risk-relevancy tag; determining, by the processor, a risk-relevancy metric of each of the plurality of portions, wherein the at least one risk-relevancy tag identifies the risk-relevancy metric associated with a relevant portion of the information with respect to the at least one risk, the risk-relevancy metric indicating a likelihood that the relevant portion of the information is relevant to the at least one risk; storing the risk-relevant information in a data storage structure, wherein the data storage structure includes a plurality of areas that are interrelated to facilitate the identification of the at least one risk; and outputting the risk-relevant information stored in the data storage structure to a risk identification graphical user interface. 6. The method of claim 1 , wherein the information is received from a device that collects the information from a plurality of sources. | 0.887124 |
8,713,433 | 20 | 21 | 20. A computing system comprising: an input device; a display device; at least one processor; and at least one module operable by the at least one processor to: receive, from the input device, an indication of a selection of one or more of a plurality of keys of a keyboard associated with the input device; determine, based at least in part on the indication of the selection, a character string; determine, based at least in part on the character string, a plurality of candidate words; determine, based at least in part on the plurality of candidate words and a plurality of features, a spelling probability that the character string comprises an incorrect spelling of at least one of the plurality of candidate words, the plurality of features comprising at least a spatial model probability associated with each of the one or more candidate words; and responsive to determining that the spelling probability satisfies a threshold, output, for display at the display device, the at least one of the plurality of candidate words. | 20. A computing system comprising: an input device; a display device; at least one processor; and at least one module operable by the at least one processor to: receive, from the input device, an indication of a selection of one or more of a plurality of keys of a keyboard associated with the input device; determine, based at least in part on the indication of the selection, a character string; determine, based at least in part on the character string, a plurality of candidate words; determine, based at least in part on the plurality of candidate words and a plurality of features, a spelling probability that the character string comprises an incorrect spelling of at least one of the plurality of candidate words, the plurality of features comprising at least a spatial model probability associated with each of the one or more candidate words; and responsive to determining that the spelling probability satisfies a threshold, output, for display at the display device, the at least one of the plurality of candidate words. 21. The computing device of claim 20 , wherein the at least one module is further operable by the at least one processor to output a graphical keyboard for display at the display device, wherein the keyboard associated with the input device comprises the graphical keyboard. | 0.886023 |
7,676,517 | 1 | 7 | 1. A system embodied in a computer readable storage medium that, when executed by one or more processors, facilitates query processing, the system comprising the following computer executable components: a query component that facilitates input of a portion of query data into a client application during a query generation process, wherein the query generation process comprises automatic injection of additional query data into the client application; a search component that executes a query against an indexed network based service in real time to suggest the additional query data in response to receiving the portion of the query data and communicates the additional query data to the query component for presentation to a user; a trigger component that facilitates the inclusion of one or more additional data elements to affect the query generation process and facilitates one or more of impacting, refining, and filtering the additional query data; an adaptive component that adapts the query generation process to a skill level of the user, wherein the query generation process is more automated when the user is determined to be more skillful and the query generation process is less automated when the user is determined to be more novice; and a machine learning and reasoning component that employs a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. | 1. A system embodied in a computer readable storage medium that, when executed by one or more processors, facilitates query processing, the system comprising the following computer executable components: a query component that facilitates input of a portion of query data into a client application during a query generation process, wherein the query generation process comprises automatic injection of additional query data into the client application; a search component that executes a query against an indexed network based service in real time to suggest the additional query data in response to receiving the portion of the query data and communicates the additional query data to the query component for presentation to a user; a trigger component that facilitates the inclusion of one or more additional data elements to affect the query generation process and facilitates one or more of impacting, refining, and filtering the additional query data; an adaptive component that adapts the query generation process to a skill level of the user, wherein the query generation process is more automated when the user is determined to be more skillful and the query generation process is less automated when the user is determined to be more novice; and a machine learning and reasoning component that employs a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. 7. The system of claim 1 , the client application is at least one of a word processing application, a browser application, a spreadsheet application, or a presentation application. | 0.647059 |
10,127,569 | 1 | 9 | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. 9. The non-transitory computer-readable medium of claim 1 , wherein at least one child entity of the one or more child entities is a parent of another child entity of the one or more child entities. | 0.876404 |
8,666,040 | 5 | 6 | 5. The method of claim 1 , further comprising grouping calls having matching call paths. | 5. The method of claim 1 , further comprising grouping calls having matching call paths. 6. The method of claim 5 , wherein indicating at least one call path further comprises indicating a group of calls according to a measure of the number of occurrences of the selected type of event within the call paths of the group of calls. | 0.889551 |
9,304,974 | 1 | 11 | 1. A computer implemented method, comprising: identifying a message of a user, wherein the message includes a plurality of terms and is an electronic communication sent or received by the user; determining an event based on the message, wherein the event includes one or more event properties that are determined based on one or more of the terms; determining an event confidence level based on the event properties; determining an effect on dissemination of information related to the event, wherein the effect is determined based on the event confidence level, wherein the dissemination of information includes a first dissemination of information that is related to a first computer application and a second dissemination of information that is related to a second computer application and that is unique from the first dissemination of information, and wherein the determining the effect on the dissemination of information comprises: determining, based on the event confidence level, to influence the first dissemination of information based on the event and to not influence the second dissemination of information based on the event, the influence of the first dissemination of information being reflected in output provided to the user via the first computer application; identifying additional data associated with the user and the event; determining a new event confidence level based on the additional data; and adjusting the effect on the dissemination of information related to the event based on the new event confidence level, wherein the adjusting the effect on the dissemination of information comprises determining, based on the new event confidence level, to influence both the first dissemination of information and the second dissemination of information based on the event, the influence of the second dissemination of information being reflected in additional output provided to the user via the second computer application. | 1. A computer implemented method, comprising: identifying a message of a user, wherein the message includes a plurality of terms and is an electronic communication sent or received by the user; determining an event based on the message, wherein the event includes one or more event properties that are determined based on one or more of the terms; determining an event confidence level based on the event properties; determining an effect on dissemination of information related to the event, wherein the effect is determined based on the event confidence level, wherein the dissemination of information includes a first dissemination of information that is related to a first computer application and a second dissemination of information that is related to a second computer application and that is unique from the first dissemination of information, and wherein the determining the effect on the dissemination of information comprises: determining, based on the event confidence level, to influence the first dissemination of information based on the event and to not influence the second dissemination of information based on the event, the influence of the first dissemination of information being reflected in output provided to the user via the first computer application; identifying additional data associated with the user and the event; determining a new event confidence level based on the additional data; and adjusting the effect on the dissemination of information related to the event based on the new event confidence level, wherein the adjusting the effect on the dissemination of information comprises determining, based on the new event confidence level, to influence both the first dissemination of information and the second dissemination of information based on the event, the influence of the second dissemination of information being reflected in additional output provided to the user via the second computer application. 11. The method of claim 1 , wherein the first dissemination of information includes providing a notification to the user and the effect on the first dissemination of information includes one or more characteristics of the notification to the user. | 0.856729 |
8,392,249 | 19 | 23 | 19. Apparatus for determining one or more ad targeting keywords, the apparatus comprising: a) an input for accepting a category; b) a plurality of networked processors; and c) at least one storage device storing executable instructions which, when executed by the plurality of networked processors, performs a method including 1) looking up one or more keywords using the accepted category and a previously stored association of a plurality of categories and keywords, 2) storing at least some of the keywords as one or more ad targeting keywords of an advertisement, 3) controlling a serving of the advertisement using the stored one or more ad targeting keywords, wherein when the advertisement is served, presentation of the advertisement to a user is induced, performing qualification testing of the one or more keywords, and determining if a keyword is qualified or unqualified for use as an ad targeting keyword of the advertisement, wherein each of the at least some of the keywords stored as one or more ad targeting keywords of the advertisement are qualified keywords, and wherein the act of performing qualification testing of the keywords tracks a performance of the set of one or more advertisements served using the keyword as an ad targeting keyword, wherein the set of one or more advertisements includes the advertisement. | 19. Apparatus for determining one or more ad targeting keywords, the apparatus comprising: a) an input for accepting a category; b) a plurality of networked processors; and c) at least one storage device storing executable instructions which, when executed by the plurality of networked processors, performs a method including 1) looking up one or more keywords using the accepted category and a previously stored association of a plurality of categories and keywords, 2) storing at least some of the keywords as one or more ad targeting keywords of an advertisement, 3) controlling a serving of the advertisement using the stored one or more ad targeting keywords, wherein when the advertisement is served, presentation of the advertisement to a user is induced, performing qualification testing of the one or more keywords, and determining if a keyword is qualified or unqualified for use as an ad targeting keyword of the advertisement, wherein each of the at least some of the keywords stored as one or more ad targeting keywords of the advertisement are qualified keywords, and wherein the act of performing qualification testing of the keywords tracks a performance of the set of one or more advertisements served using the keyword as an ad targeting keyword, wherein the set of one or more advertisements includes the advertisement. 23. The apparatus of claim 19 wherein the set of one or more advertisements served using the keyword as an ad targeting keyword by the act of performing qualification testing of the keywords, is only served on available ad spots that otherwise would be unused by any ads. | 0.715933 |
5,506,933 | 1 | 8 | 1. A recognition system comprising: feature extracting means for extracting a feature vector x from an input signal; and recognizing means for obtaining continuous density Hidden Markov Models (HMMs) of predetermined categories K represented by transition network models each having parameters of transition probabilities p(k,i,j) that a state Si transits to a next state Sj and output probabilities g(k,s) that the feature vector x is output in transition from the state Si to one of the states Si and Sj, and for recognizing the input signal on the basis of similarity between a feature vector sequence x of the feature vectors x each extracted by said feature extracting means and the continuous density HMMs; wherein said recognizing means includes memory means for storing a set of orthogonal vectors .phi..sub.m (k,s) provided for the continuous density HMMs, and processing means for obtaining each of the output probabilities g(k,s) for the continuous density HMMs in accordance with the orthogonal vectors .phi..sub.m (k,s) or a corresponding category k. | 1. A recognition system comprising: feature extracting means for extracting a feature vector x from an input signal; and recognizing means for obtaining continuous density Hidden Markov Models (HMMs) of predetermined categories K represented by transition network models each having parameters of transition probabilities p(k,i,j) that a state Si transits to a next state Sj and output probabilities g(k,s) that the feature vector x is output in transition from the state Si to one of the states Si and Sj, and for recognizing the input signal on the basis of similarity between a feature vector sequence x of the feature vectors x each extracted by said feature extracting means and the continuous density HMMs; wherein said recognizing means includes memory means for storing a set of orthogonal vectors .phi..sub.m (k,s) provided for the continuous density HMMs, and processing means for obtaining each of the output probabilities g(k,s) for the continuous density HMMs in accordance with the orthogonal vectors .phi..sub.m (k,s) or a corresponding category k. 8. A recognition system according to claim 1, wherein said input signal is a speech signal. | 0.895642 |
9,836,192 | 1 | 8 | 1. A system to facilitate a graphical user interface in a computing environment, the system comprising a computing device configured to execute computer code in order to: interact with a graphical user interface (GUI) in a window, the GUI comprising at least one user interface (UI) object accessible using a mouse; receive a first command from a user to position a mouse cursor at a location in the window of the UI object in preparation for receiving a second command from the user to generate a marker representing the UI object, wherein the marker comprises a marker label; receive the second command from the user; display the marker label proximate the location of the UI object in the window; and receive a voice command from the user that identifies the marker label, and in response to the voice command, generate an input representing the user interfacing with the UI object. | 1. A system to facilitate a graphical user interface in a computing environment, the system comprising a computing device configured to execute computer code in order to: interact with a graphical user interface (GUI) in a window, the GUI comprising at least one user interface (UI) object accessible using a mouse; receive a first command from a user to position a mouse cursor at a location in the window of the UI object in preparation for receiving a second command from the user to generate a marker representing the UI object, wherein the marker comprises a marker label; receive the second command from the user; display the marker label proximate the location of the UI object in the window; and receive a voice command from the user that identifies the marker label, and in response to the voice command, generate an input representing the user interfacing with the UI object. 8. The system as recited in claim 1 , wherein the UI object comprises at least one of a menu command, an icon command, an icon tool, a check box, and a text input field. | 0.753644 |
8,438,494 | 17 | 24 | 17. A non-transitory computer-readable medium storing instructions executable by a digital processing apparatus to perform an operation to formulate a computerized presentation of a sequence of scripts, the operation comprising: providing scripts comprising fixed content; providing users to control presentation of the scripts; allowing users to interject into the presentation of the scripts with agent content; observing the users during presentation to a contact and recording the execution of the script segments and interjection of agent content as presented at the discretion of the user during an interaction between the user and the contact; and providing a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded during the execution of the script segments and interjection of agent content by the user. | 17. A non-transitory computer-readable medium storing instructions executable by a digital processing apparatus to perform an operation to formulate a computerized presentation of a sequence of scripts, the operation comprising: providing scripts comprising fixed content; providing users to control presentation of the scripts; allowing users to interject into the presentation of the scripts with agent content; observing the users during presentation to a contact and recording the execution of the script segments and interjection of agent content as presented at the discretion of the user during an interaction between the user and the contact; and providing a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded during the execution of the script segments and interjection of agent content by the user. 24. The computer-readable medium of claim 17 , wherein the instructions further comprise an operation to modify the script to incorporate the content and sequences of agent content observed. | 0.680135 |
8,959,211 | 1 | 2 | 1. A method comprising: maintaining a profile for a user of a social networking system, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; generating a feed that comprises a plurality of stories, wherein each of the stories comprises a description of an action performed by or related to another user of the social networking system with whom the user has established a connection; obtaining a plurality of prompts associated with one or more information items, each prompt having a response probability indicating a likelihood of receiving a response to a prompt when presented, each prompt related to one or more stories in the feed; selecting an unknown information item from the set of unknown information items based at least in part on data acquisition values associated with each of the unknown information items; selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item and content of the feed; incorporating the selected prompt into one of the stories of the feed to which the selected prompt is related; and sending the feed for display to the user. | 1. A method comprising: maintaining a profile for a user of a social networking system, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; generating a feed that comprises a plurality of stories, wherein each of the stories comprises a description of an action performed by or related to another user of the social networking system with whom the user has established a connection; obtaining a plurality of prompts associated with one or more information items, each prompt having a response probability indicating a likelihood of receiving a response to a prompt when presented, each prompt related to one or more stories in the feed; selecting an unknown information item from the set of unknown information items based at least in part on data acquisition values associated with each of the unknown information items; selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item and content of the feed; incorporating the selected prompt into one of the stories of the feed to which the selected prompt is related; and sending the feed for display to the user. 2. The method of claim 1 , further comprising: receiving a response to the selected prompt from the user; and storing the response to the selected prompt in the user profile as data associated with the selected unknown information item. | 0.690289 |
9,785,753 | 1 | 5 | 1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a sterile procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the sterile procedure, wherein transcribing the audio data comprises performing automatic speech recognition (ASR) on the audio data using a speech recognition model trained to recognize speech of the first clinician; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the sterile procedure, using at least one processor, to identify relevant information for documenting the sterile procedure; and automatically generating a text report including the identified relevant information documenting the sterile procedure; wherein identifying the relevant information comprises detecting within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the sterile procedure; wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the sterile procedure was performed. | 1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a sterile procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the sterile procedure, wherein transcribing the audio data comprises performing automatic speech recognition (ASR) on the audio data using a speech recognition model trained to recognize speech of the first clinician; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the sterile procedure, using at least one processor, to identify relevant information for documenting the sterile procedure; and automatically generating a text report including the identified relevant information documenting the sterile procedure; wherein identifying the relevant information comprises detecting within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the sterile procedure; wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the sterile procedure was performed. 5. The method of claim 1 , wherein the sterile procedure is performed on a patient, wherein the audio data comprises audio of the one or more clinical personnel orally identifying one or more observations of a condition of the patient during the sterile procedure, wherein the analyzing comprises automatically determining whether the observed condition of the patient indicates that the patient suffered a complication of the sterile procedure, and wherein generating the text report comprises, in response to determining that the observed condition indicates that the patient suffered a complication of the sterile procedure, automatically generating text stating that the condition was observed as a complication. | 0.593182 |
9,405,834 | 13 | 22 | 13. A system to identify related search queries, comprising: at least one processor; memory; and at least one program stored in the memory and executable by the at least one processor, the at least one program comprising instructions to: receive a search query from a user; identify a set of ranked search results satisfying the search query; identify, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and return the set of ranked search results and the at least one last related search query to the user. | 13. A system to identify related search queries, comprising: at least one processor; memory; and at least one program stored in the memory and executable by the at least one processor, the at least one program comprising instructions to: receive a search query from a user; identify a set of ranked search results satisfying the search query; identify, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and return the set of ranked search results and the at least one last related search query to the user. 22. The system of claim 13 , wherein a likelihood that the at least one last related search query is related to objectionable content is below a predetermined likelihood threshold. | 0.810127 |
8,793,120 | 6 | 7 | 6. The computer-implemented method of claim 1 , wherein each of the relative measurement values corresponds to an indication of a frequency of use of one of the forms in the output set. | 6. The computer-implemented method of claim 1 , wherein each of the relative measurement values corresponds to an indication of a frequency of use of one of the forms in the output set. 7. The computer-implemented method of claim 6 , further comprising: filtering out forms having a frequency that does not at least meet a minimum frequency threshold. | 0.940605 |
8,451,275 | 1 | 10 | 1. In a computer system for monitoring a process, the computer system having a display device and a graphical user interface for displaying on the display device the status of components used in operation of the process, each component being represented on the graphical user interface by an associated graphical object that is generated or rendered by an application from a related vector graphic file, the improvement comprising a method of animating said graphical object to show a change in the status of the component being represented, the method comprising: inserting into said vector graphic file an animation instruction, wherein the animation instruction: is not executable code, complies with a predefined syntax, does not violate a prescribed format for the vector graphic file, is ignored by said application; and defines one or more animation effects that are dependent upon a value of at least one variable and a set of conditions applying to the at least one variable; the value of said at least one variable being dependent upon the status of said component being represented; running an interpreter engine to: (a) recognize and parse said animation instruction, (b) retrieve a current value of said at least one variable, (c) determine a required animation effect based on checking the retrieved current value of the at least one variable against said set of conditions, and (d) instruct the application to modify said graphical object to exhibit the determined animation effect; and displaying said graphical object with the determined animation effect on the display device. | 1. In a computer system for monitoring a process, the computer system having a display device and a graphical user interface for displaying on the display device the status of components used in operation of the process, each component being represented on the graphical user interface by an associated graphical object that is generated or rendered by an application from a related vector graphic file, the improvement comprising a method of animating said graphical object to show a change in the status of the component being represented, the method comprising: inserting into said vector graphic file an animation instruction, wherein the animation instruction: is not executable code, complies with a predefined syntax, does not violate a prescribed format for the vector graphic file, is ignored by said application; and defines one or more animation effects that are dependent upon a value of at least one variable and a set of conditions applying to the at least one variable; the value of said at least one variable being dependent upon the status of said component being represented; running an interpreter engine to: (a) recognize and parse said animation instruction, (b) retrieve a current value of said at least one variable, (c) determine a required animation effect based on checking the retrieved current value of the at least one variable against said set of conditions, and (d) instruct the application to modify said graphical object to exhibit the determined animation effect; and displaying said graphical object with the determined animation effect on the display device. 10. The method of claim 1 , wherein step (d) comprises manipulating an object model or object properties or styles of said graphical object. | 0.583333 |
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