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8,245,277 | 9 | 10 | 9. A non-transitory computer readable medium whose contents cause a security access computing system to: receive a request for a web page including a completely automated public turing test to tell computer and humans apart (CAPTCHA); randomly select an image file and an audio file from a collection of multiple image file and audio file pairs, wherein each of said image file and audio file pairs are contextually related to one another; in response to said request, transmit a web page including said randomly selected image file and audio file, wherein said randomly selected image file and audio file are contextually related to one another; receive a user selection of a label; determine whether said user selected label matches one or more stored labels that are contextually related to said randomly selected image file and audio file; and allow access to said electronic service upon a determination that said user selected label matches said one or more stored labels. | 9. A non-transitory computer readable medium whose contents cause a security access computing system to: receive a request for a web page including a completely automated public turing test to tell computer and humans apart (CAPTCHA); randomly select an image file and an audio file from a collection of multiple image file and audio file pairs, wherein each of said image file and audio file pairs are contextually related to one another; in response to said request, transmit a web page including said randomly selected image file and audio file, wherein said randomly selected image file and audio file are contextually related to one another; receive a user selection of a label; determine whether said user selected label matches one or more stored labels that are contextually related to said randomly selected image file and audio file; and allow access to said electronic service upon a determination that said user selected label matches said one or more stored labels. 10. The non-transitory computer readable medium of claim 9 , wherein said image file and said audio file are maintained in a database accessible by said computing system, and wherein said database further comprising a collection of multiple image file and audio file pairs, wherein each of said image file and audio file pairs are contextually related to one another. | 0.715504 |
8,316,032 | 13 | 15 | 13. A system, comprising: a memory, the memory storing an index of distinct book content items and corresponding characteristics of the distinct book content items; one or more computers configured to interact with the memory, the one or more computers being further configured to perform operations comprising: identifying image content for a plurality of distinct book content items, the image content defining images that appear in the plurality of distinct book content items; identifying descriptor points from the image content, the descriptor points defining localized features of the image content of the distinct book content items, the localized features being characteristics of a portion of the image content; representing the distinct book content items as a weighted graph in computer memory, where each of the distinct book content items is represented as a distinct node in the weighted graph and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching descriptor point, matching descriptor points being identified based on similarities between pairs of descriptor points, and each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching image content in the image content of other distinct book content items that are represented by other distinct nodes, each matching image content being image content that has descriptor points that match the corresponding descriptor points of image content in the distinct book content item corresponding to the distinct node; generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of image content in the distinct book content item to matching image content in another distinct book content item; determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items. | 13. A system, comprising: a memory, the memory storing an index of distinct book content items and corresponding characteristics of the distinct book content items; one or more computers configured to interact with the memory, the one or more computers being further configured to perform operations comprising: identifying image content for a plurality of distinct book content items, the image content defining images that appear in the plurality of distinct book content items; identifying descriptor points from the image content, the descriptor points defining localized features of the image content of the distinct book content items, the localized features being characteristics of a portion of the image content; representing the distinct book content items as a weighted graph in computer memory, where each of the distinct book content items is represented as a distinct node in the weighted graph and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching descriptor point, matching descriptor points being identified based on similarities between pairs of descriptor points, and each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching image content in the image content of other distinct book content items that are represented by other distinct nodes, each matching image content being image content that has descriptor points that match the corresponding descriptor points of image content in the distinct book content item corresponding to the distinct node; generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of image content in the distinct book content item to matching image content in another distinct book content item; determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items. 15. The system of claim 13 , wherein the operations further comprise determining edge weights for each edge based on a number of matching descriptor points between distinct book content items. | 0.697161 |
7,672,841 | 1 | 6 | 1. A method of processing speech data from an utterance for a distributed speech query recognition system comprising the steps of: establishing a network connection between a server computing system and a client device suitable for transporting a streaming communication; receiving a continuous speech byte data stream containing speech data processed by a first component of the distributed speech query recognition system situated in the client device; wherein said speech data is characterized by a form and data content representing only a partial recognition of an utterance; further wherein said data stream includes NULL data used to identify a silence in speech data from said client device said NULL data being inserted at the client device after other NULL data is removed prior to transmission of the speech byte data stream; and further processing said speech data at a second component of the distributed speech query recognition system situated at said server computing system to generate additional speech related content and complete recognition of words in said speech data. | 1. A method of processing speech data from an utterance for a distributed speech query recognition system comprising the steps of: establishing a network connection between a server computing system and a client device suitable for transporting a streaming communication; receiving a continuous speech byte data stream containing speech data processed by a first component of the distributed speech query recognition system situated in the client device; wherein said speech data is characterized by a form and data content representing only a partial recognition of an utterance; further wherein said data stream includes NULL data used to identify a silence in speech data from said client device said NULL data being inserted at the client device after other NULL data is removed prior to transmission of the speech byte data stream; and further processing said speech data at a second component of the distributed speech query recognition system situated at said server computing system to generate additional speech related content and complete recognition of words in said speech data. 6. The method of claim 1 , wherein speech recognition tasks required by the distributed speech recognition system for recognizing words are allocated to said server computing device on a connection by connection basis. | 0.558704 |
9,514,128 | 6 | 7 | 6. The method of claim 5 , further comprising providing a plurality of predetermined language constructs in the first language to the first entity, wherein the first language construct comprises a selected language construct from the plurality of predetermined language constructs. | 6. The method of claim 5 , further comprising providing a plurality of predetermined language constructs in the first language to the first entity, wherein the first language construct comprises a selected language construct from the plurality of predetermined language constructs. 7. The method of claim 6 , wherein the providing the plurality of predetermined language constructs comprises causing presentation of the plurality of predetermined language constructs in an interactive area of a web form. | 0.915525 |
9,015,097 | 11 | 19 | 11. A system comprising: a processor; and a non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by the processor, causes the processor to implement: a structure generation module configured to retrieve, from a memory, a global structure and a plurality of candidate answers therein; a computation module including: (i) a first computation unit configured to compute a first probability of a candidate answer based on a local structure of the candidate answer within the global structure; (ii) a second computation unit configured to compute a second probability of the candidate answer based on content of the candidate answer given content of a query; and (iii) a third computation unit configured to compute a third probability of the candidate answer based on context of the candidate answer given the content of the query; and a combination module configured to provide a combined probability for the candidate answer as a function of the first probability, second probability, and third probability. | 11. A system comprising: a processor; and a non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by the processor, causes the processor to implement: a structure generation module configured to retrieve, from a memory, a global structure and a plurality of candidate answers therein; a computation module including: (i) a first computation unit configured to compute a first probability of a candidate answer based on a local structure of the candidate answer within the global structure; (ii) a second computation unit configured to compute a second probability of the candidate answer based on content of the candidate answer given content of a query; and (iii) a third computation unit configured to compute a third probability of the candidate answer based on context of the candidate answer given the content of the query; and a combination module configured to provide a combined probability for the candidate answer as a function of the first probability, second probability, and third probability. 19. The system of claim 11 , wherein the structure generation module is further configured retrieve input data with a particular structure and generating the global structure automatically based on the input data by parsing the particular structure. | 0.77847 |
8,832,135 | 1 | 9 | 1. A method for automatically providing a plurality of additional database query terms to a user, the method comprising: receiving a first query term from the user; receiving a plurality of characters from the user, wherein the plurality of characters is only a portion of a second query term; selecting a first set of records from a database based on the first query term, wherein the database comprises records, and wherein the records comprise text translated from audio data associated with a call, wherein each word in a record is associated with a corresponding confidence factor, the confidence factor representing an accuracy of translation of the word from audio to text, the records further comprising metadata that includes information about a party to the call, a time of the call and a date of the call; determining, in a first pass, a first plurality of additional query terms based on the plurality of characters, wherein the first plurality of additional query terms are in a semantic network; for each one of the first plurality of additional query terms, determining a relevance of the additional query term with respect to the first plurality of additional query terms by processing all records in the database, including the metadata, to select a second set of records from the database based on the additional query term and comparing the second set of records with the first set of records selected based on the first query term, wherein the relevance is also determined at least in part based on semantic information related to the records; recursively determining, in at least a subsequent pass to the first pass, a second plurality of additional query terms based on previously determined additional query terms and determining the relevance of the recursively determined second plurality of additional query terms, wherein the relevance is determined at least in part based on semantic information related to the records; displaying at least one additional query term selected from the first plurality of additional query terms and the second plurality of additional query terms to the user for selection, the display based on the relevance of each of the plurality of additional query terms and on the confidence factor of each additional query term. | 1. A method for automatically providing a plurality of additional database query terms to a user, the method comprising: receiving a first query term from the user; receiving a plurality of characters from the user, wherein the plurality of characters is only a portion of a second query term; selecting a first set of records from a database based on the first query term, wherein the database comprises records, and wherein the records comprise text translated from audio data associated with a call, wherein each word in a record is associated with a corresponding confidence factor, the confidence factor representing an accuracy of translation of the word from audio to text, the records further comprising metadata that includes information about a party to the call, a time of the call and a date of the call; determining, in a first pass, a first plurality of additional query terms based on the plurality of characters, wherein the first plurality of additional query terms are in a semantic network; for each one of the first plurality of additional query terms, determining a relevance of the additional query term with respect to the first plurality of additional query terms by processing all records in the database, including the metadata, to select a second set of records from the database based on the additional query term and comparing the second set of records with the first set of records selected based on the first query term, wherein the relevance is also determined at least in part based on semantic information related to the records; recursively determining, in at least a subsequent pass to the first pass, a second plurality of additional query terms based on previously determined additional query terms and determining the relevance of the recursively determined second plurality of additional query terms, wherein the relevance is determined at least in part based on semantic information related to the records; displaying at least one additional query term selected from the first plurality of additional query terms and the second plurality of additional query terms to the user for selection, the display based on the relevance of each of the plurality of additional query terms and on the confidence factor of each additional query term. 9. The method of claim 1 , wherein at least one of the plurality of additional query terms includes at least one word similar in sound to at least one word in the first query term or in the plurality of additional query terms. | 0.727053 |
9,280,798 | 6 | 8 | 6. A computer-implemented method for facilitating review of electronic documents, the method comprising the steps of: (a) displaying on a user interface information relating to a role of the user in reviewing the electronic documents, wherein each electronic document comprises a patent record or specification, a trade mark record or specification, or a design record or specification; (b) enabling the user to enter into the user interface an indication that the role is to be performed by an alternative reviewer, and a first time period that the role is to be performed by the alternative user; and (c) during the first period of time, allowing access to the electronic documents to the alternative user for review and via a display interface associated with the alternative user, wherein allowing access to the electronic documents comprises enabling a display by the user interface associated with the alternative user a visual map of different groups associated with a particular context, the different groups represented by the visual map comprise different business competitors associated with the particular context, the particular context relating to the role within a business context that the user is performing the review, each group is represented by an icon that is proportionately sized to represent a number of items within the group in relation to items within other groups represented by the visual map, and the visual map is configured to present additional information about the items represented by an icon as an overlay on the visual map in response to a user selecting the icon, the additional information comprising at least one of a brief description of a commercial operation of the business competitor associated with the icon, a country of origin of the business competitor associated with the icon, and a number of patent properties of the business competitor associated with the icon that have previously been reviewed and indicated as relevant to the electronic document. | 6. A computer-implemented method for facilitating review of electronic documents, the method comprising the steps of: (a) displaying on a user interface information relating to a role of the user in reviewing the electronic documents, wherein each electronic document comprises a patent record or specification, a trade mark record or specification, or a design record or specification; (b) enabling the user to enter into the user interface an indication that the role is to be performed by an alternative reviewer, and a first time period that the role is to be performed by the alternative user; and (c) during the first period of time, allowing access to the electronic documents to the alternative user for review and via a display interface associated with the alternative user, wherein allowing access to the electronic documents comprises enabling a display by the user interface associated with the alternative user a visual map of different groups associated with a particular context, the different groups represented by the visual map comprise different business competitors associated with the particular context, the particular context relating to the role within a business context that the user is performing the review, each group is represented by an icon that is proportionately sized to represent a number of items within the group in relation to items within other groups represented by the visual map, and the visual map is configured to present additional information about the items represented by an icon as an overlay on the visual map in response to a user selecting the icon, the additional information comprising at least one of a brief description of a commercial operation of the business competitor associated with the icon, a country of origin of the business competitor associated with the icon, and a number of patent properties of the business competitor associated with the icon that have previously been reviewed and indicated as relevant to the electronic document. 8. A computer-implemented method according to claim 6 , further comprising: enabling the user to enter into the user interface an indication that the role is no longer to be performed by the alternative user; and disallowing access to the electronic documents by the alternative user. | 0.777778 |
7,856,375 | 1 | 27 | 1. A method for automatically preparing customized communication documents for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using a computing system configured to access said first data file and second data file to compose an electronic document file representing a customized communication document for at least one of said certain of the plurality of the consumer entities, said customized communication document comprising information relating to an offering for one or more financial products or services; wherein at least some content included in said customized communication document is customized content generated by said computing system for said electronic document file which includes variable data specifically for a consumer entity automatically derived and/or calculated from said first electronic data file and/or said second electronic data file during said automated composition process for said electronic document file and said consumer entity; delivering said customized communication documents based on said electronic document file to at least one of said certain of the plurality of consumer entities. | 1. A method for automatically preparing customized communication documents for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using a computing system configured to access said first data file and second data file to compose an electronic document file representing a customized communication document for at least one of said certain of the plurality of the consumer entities, said customized communication document comprising information relating to an offering for one or more financial products or services; wherein at least some content included in said customized communication document is customized content generated by said computing system for said electronic document file which includes variable data specifically for a consumer entity automatically derived and/or calculated from said first electronic data file and/or said second electronic data file during said automated composition process for said electronic document file and said consumer entity; delivering said customized communication documents based on said electronic document file to at least one of said certain of the plurality of consumer entities. 27. The method of claim 1 wherein said customized content is determined for a consumer entity by a routine which analyzes personal data for each consumer entity and evaluates which of said plurality of descriptions, characteristics and/or identifications should be used in presenting said at least first financial product and/or financial service to such consumer entity. | 0.657749 |
7,934,660 | 75 | 77 | 75. The system of claim 74 , wherein said host computer is configured to be commanded to encode on a physically transportable medium a decodable dataform, the decodable dataform encoding said edited configuration file and being readable by said encoded information reader device. | 75. The system of claim 74 , wherein said host computer is configured to be commanded to encode on a physically transportable medium a decodable dataform, the decodable dataform encoding said edited configuration file and being readable by said encoded information reader device. 77. The system of claim 75 , wherein said host computer is configured to be commanded to encode on a physically transportable medium a decodable dataform, the decodable dataform encoding said edited configuration file, the host computer having an information entry area enabling a user to designate whether content should be removed from said edited configuration file prior to being encoded. | 0.875556 |
8,391,613 | 1 | 6 | 1. A method for generating patterns for use in online character recognition, the method comprising: performing one or more pre-processing operations on a character sample; performing one or more feature extraction operations on the character sample, wherein the one or more feature extraction operations produce a feature vector for the character sample, wherein said performing the one or more feature extraction operations utilizes a Gabor filter, wherein the one or more feature extraction operations comprise: extracting directional features based on the direction of the character sample's points; generating directional pattern images based on the directional features; filtering the directional pattern images using a Gabor filter; and forming the feature vector based on the filtered directional pattern images; performing statistical training to generate patterns based on the feature vector of the character sample; storing the patterns in a memory, wherein the patterns are configured to be used to recognize handwritten characters. | 1. A method for generating patterns for use in online character recognition, the method comprising: performing one or more pre-processing operations on a character sample; performing one or more feature extraction operations on the character sample, wherein the one or more feature extraction operations produce a feature vector for the character sample, wherein said performing the one or more feature extraction operations utilizes a Gabor filter, wherein the one or more feature extraction operations comprise: extracting directional features based on the direction of the character sample's points; generating directional pattern images based on the directional features; filtering the directional pattern images using a Gabor filter; and forming the feature vector based on the filtered directional pattern images; performing statistical training to generate patterns based on the feature vector of the character sample; storing the patterns in a memory, wherein the patterns are configured to be used to recognize handwritten characters. 6. The method of claim 1 , wherein the statistical training comprises a clustering algorithm. | 0.954678 |
9,223,547 | 12 | 13 | 12. The system of claim 11 , wherein the at least one processor is further configured to: generate the computer program in the target language, the computer program including: the elements in the arrangement determined based on the analyzing of the audio input; and source code for the at least one of the elements, the source code including the one or more syntax-level tokens. | 12. The system of claim 11 , wherein the at least one processor is further configured to: generate the computer program in the target language, the computer program including: the elements in the arrangement determined based on the analyzing of the audio input; and source code for the at least one of the elements, the source code including the one or more syntax-level tokens. 13. The system of claim 12 , wherein the at least one processor is further configured to: perform at least one action, including one or more of compiling, interpreting, linking, or executing the computer program; and present the audio output that describes at least one error in performing the at least one action. | 0.947841 |
9,792,330 | 1 | 12 | 1. A method of ranking local search results based on reviews by experts, the method comprising: receiving a query from a user via a user device; identifying a geographic area and a category of business for the query; identifying, with one or more processors using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking, with the one or more processors, local search results responsive to the query based on reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. | 1. A method of ranking local search results based on reviews by experts, the method comprising: receiving a query from a user via a user device; identifying a geographic area and a category of business for the query; identifying, with one or more processors using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking, with the one or more processors, local search results responsive to the query based on reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. 12. The method of claim 1 , wherein identifying the plurality of experts further comprises: initializing the category of business to an initial category of business for the query; determining that no experts are designated for the geographic area and category of business; and iteratively decreasing specificity of the category of business until an expert is designated for the modified category of business and the geographic area. | 0.501155 |
9,760,545 | 14 | 21 | 14. An ebook device comprising: a command and selection input module, the input module adapted to accept and digitize user commands and user selections; a processor communicatively coupled with the input module, the processor adapted to receive digitized user commands and user selections from the input module; a memory communicatively coupled with the processor and comprising an ebook reader and at least one ebook, the ebook comprising digitized text separated into a plurality of textual segments; a display screen, the display screen communicatively coupled with the memory and adapted to render digitized text of the ebook segments; and the ebook comprising: a first plurality of segments of the textual segments comprising digitized text and associated with a first tag, wherein each segment of the first plurality of segments is assigned a unique sequence number by a user; a second plurality of segments of the textual segments associated with a second tag, wherein each segment of the second plurality of segments is assigned a unique sequence number by the user, and wherein at least one segment of the textual segments is associated with both the first tag and the second tag and the at least one segment of the textual segments is included within both the first plurality of segments and the second plurality of segments; and logic directing the processor to perform the following rendering at the display screen: execute upon receipt a user command to sequentially render segments associated with the first tag; generate a first node record and associate the segments associated with the first tag with the first node record; associate the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially render each segment associated with the first node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; execute upon receipt a user command to sequentially render segments associated with the second tag; generate a second node record and associate segments associated with the second tag with the second node record; sequentially render segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. | 14. An ebook device comprising: a command and selection input module, the input module adapted to accept and digitize user commands and user selections; a processor communicatively coupled with the input module, the processor adapted to receive digitized user commands and user selections from the input module; a memory communicatively coupled with the processor and comprising an ebook reader and at least one ebook, the ebook comprising digitized text separated into a plurality of textual segments; a display screen, the display screen communicatively coupled with the memory and adapted to render digitized text of the ebook segments; and the ebook comprising: a first plurality of segments of the textual segments comprising digitized text and associated with a first tag, wherein each segment of the first plurality of segments is assigned a unique sequence number by a user; a second plurality of segments of the textual segments associated with a second tag, wherein each segment of the second plurality of segments is assigned a unique sequence number by the user, and wherein at least one segment of the textual segments is associated with both the first tag and the second tag and the at least one segment of the textual segments is included within both the first plurality of segments and the second plurality of segments; and logic directing the processor to perform the following rendering at the display screen: execute upon receipt a user command to sequentially render segments associated with the first tag; generate a first node record and associate the segments associated with the first tag with the first node record; associate the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially render each segment associated with the first node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; execute upon receipt a user command to sequentially render segments associated with the second tag; generate a second node record and associate segments associated with the second tag with the second node record; sequentially render segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. 21. The device of claim 14 , wherein a delineation provides overlapping inclusion of a source digitized text within at least two segments. | 0.616667 |
8,799,186 | 31 | 32 | 31. A method for allocating a treatment to a survey respondent from a set of treatments in an online choice model survey, comprising the steps of: receiving a set of treatments for use in an online choice model survey; initializing an allocation frequency counter for each treatment in the set of treatments; receiving a request for a treatment to be provided to a survey respondent; creating a length N global binary Deck Vector D and initializing as a string of N ones indicating that all treatments are available where N is the number of treatments; creating a respondent allocation vector R of length N for each respondent for indicating whether a given treatments has been delivered to the respondent and initializing each respondent vector as string of N ones; and allocating a treatment to a survey respondent from the set of treatments; wherein the allocated treatment is selected from the subset of treatments which have not previously been allocated to the survey respondent and whose allocation frequency differs by no more than a predefined maximum difference amount from the most allocated treatment in the set of treatments; wherein allocating a treatment to a survey respondent from the set of treatments comprises: generating an availability vector A by performing a binary AND between the global binary Deck Vector D and respondent allocation vector R to obtain an availability vector A in which a one represents an available treatment; randomly selecting one of the available positions in the availability vector A; allocating the selected treatment to the respondent; and updating the global binary Deck Vector D and the respondent vector R by changing the state of the allocated position to a zero in both vectors. | 31. A method for allocating a treatment to a survey respondent from a set of treatments in an online choice model survey, comprising the steps of: receiving a set of treatments for use in an online choice model survey; initializing an allocation frequency counter for each treatment in the set of treatments; receiving a request for a treatment to be provided to a survey respondent; creating a length N global binary Deck Vector D and initializing as a string of N ones indicating that all treatments are available where N is the number of treatments; creating a respondent allocation vector R of length N for each respondent for indicating whether a given treatments has been delivered to the respondent and initializing each respondent vector as string of N ones; and allocating a treatment to a survey respondent from the set of treatments; wherein the allocated treatment is selected from the subset of treatments which have not previously been allocated to the survey respondent and whose allocation frequency differs by no more than a predefined maximum difference amount from the most allocated treatment in the set of treatments; wherein allocating a treatment to a survey respondent from the set of treatments comprises: generating an availability vector A by performing a binary AND between the global binary Deck Vector D and respondent allocation vector R to obtain an availability vector A in which a one represents an available treatment; randomly selecting one of the available positions in the availability vector A; allocating the selected treatment to the respondent; and updating the global binary Deck Vector D and the respondent vector R by changing the state of the allocated position to a zero in both vectors. 32. The method as claimed in claim 31 , wherein the predefined maximum difference amount is 1. | 0.984829 |
8,239,593 | 7 | 9 | 7. The method of claim 1 wherein the electronic device has a plurality of input members, and wherein the electronic device has stored therein a map file comprising an assignment of each character to a corresponding input member, and further comprising: detecting a press-and-hold actuation of a particular input member; and outputting at least a first character from the map file that is assigned to the particular input member and is in the inactive character set. | 7. The method of claim 1 wherein the electronic device has a plurality of input members, and wherein the electronic device has stored therein a map file comprising an assignment of each character to a corresponding input member, and further comprising: detecting a press-and-hold actuation of a particular input member; and outputting at least a first character from the map file that is assigned to the particular input member and is in the inactive character set. 9. The method of claim 7 , further comprising detecting as the input of the particular character an input of a character from the map file that is not already included in the active character set. | 0.895411 |
10,055,702 | 1 | 4 | 1. A method performed by a visual workflow-management server computing device (“workflow device”) of a database system in a multi-tenant environment having tenants including organizations, the workflow device comprising a hardware processing device coupled to a memory device, wherein the workflow device further comprises a visual workflow mechanism having a visual workflow processing unit that is at least partially embedded in the hardware processing device, the hardware processing device to facilitate the method comprising: receiving, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, a query to perform a collection of data relating to a tenant including an organization, wherein the query represents creating a new business process relating to workings of the organization; collecting, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the data from one or more accounts relating to the organization; assigning, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, one or more tasks to the collected data; performing, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the one or more tasks; dynamically generating, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, a visual workflow in response to the one or more tasks, wherein the visual workflow to facilitate the new business process based on the one or more tasks; and displaying, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the visual workflow at a display device. | 1. A method performed by a visual workflow-management server computing device (“workflow device”) of a database system in a multi-tenant environment having tenants including organizations, the workflow device comprising a hardware processing device coupled to a memory device, wherein the workflow device further comprises a visual workflow mechanism having a visual workflow processing unit that is at least partially embedded in the hardware processing device, the hardware processing device to facilitate the method comprising: receiving, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, a query to perform a collection of data relating to a tenant including an organization, wherein the query represents creating a new business process relating to workings of the organization; collecting, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the data from one or more accounts relating to the organization; assigning, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, one or more tasks to the collected data; performing, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the one or more tasks; dynamically generating, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, a visual workflow in response to the one or more tasks, wherein the visual workflow to facilitate the new business process based on the one or more tasks; and displaying, by the visual workflow processing unit that is at least partially embedded in the hardware processing device, the visual workflow at a display device. 4. The method of claim 1 , wherein the one or more tasks are assigned to the collected data based on one or more assignment elements included in the query, wherein the one or more tasks comprise one or more of delete, print, forward, email, text, add, analyze, assign, delegate, publish, share, lower one or more privileges, increase one or more privileges, and maintain status quo. | 0.501305 |
8,560,615 | 14 | 40 | 14. A computer-implemented method of processing messages, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, each conversation in the list of conversations being represented as a single row in the set of rows, the single row including conversation identifying information for the conversation and the sender list associated with the conversation; and wherein the sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. | 14. A computer-implemented method of processing messages, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, each conversation in the list of conversations being represented as a single row in the set of rows, the single row including conversation identifying information for the conversation and the sender list associated with the conversation; and wherein the sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. 40. The method of claim 14 , wherein a least one message in the plurality of messages is directed to a plurality of users including the particular user. | 0.915649 |
9,052,934 | 19 | 20 | 19. A non-transitory computer-readable medium carrying instructions for a method to permit a user to debug a set of interpretation rules for a host instrument, the method comprising: providing one or more sets of interpretation rules to be selected by a user for downloading to a host instrument; transmitting one or more non-native commands to the host instrument, wherein the one or more non-native commands is part of a command set supported by an alternate instrument to trigger the alternate instrument to perform one or more actions when received; and providing access to the one or more sets of interpretation rules for editing by the user, wherein the host instrument applies the downloaded and edited interpretation rules to the one or more non-native commands to determine the one or more actions that the one or more non-native commands instruct the alternate instrument to perform; wherein the edited interpretation rules are subsequently used by the host instrument to interpret the one or more non-native commands to determine the one or more actions and performing by the host instrument the one or more actions that the alternate instrument performs upon receiving the non-native command. | 19. A non-transitory computer-readable medium carrying instructions for a method to permit a user to debug a set of interpretation rules for a host instrument, the method comprising: providing one or more sets of interpretation rules to be selected by a user for downloading to a host instrument; transmitting one or more non-native commands to the host instrument, wherein the one or more non-native commands is part of a command set supported by an alternate instrument to trigger the alternate instrument to perform one or more actions when received; and providing access to the one or more sets of interpretation rules for editing by the user, wherein the host instrument applies the downloaded and edited interpretation rules to the one or more non-native commands to determine the one or more actions that the one or more non-native commands instruct the alternate instrument to perform; wherein the edited interpretation rules are subsequently used by the host instrument to interpret the one or more non-native commands to determine the one or more actions and performing by the host instrument the one or more actions that the alternate instrument performs upon receiving the non-native command. 20. The computer-readable medium of claim 19 wherein the one or more non-native commands are part of an application program. | 0.70892 |
9,865,281 | 2 | 4 | 2. The computer program product of claim 1 , wherein analyzing the vocal and video recordings for the first user according to one or more parameters for speech and one or more parameters for gestures comprises program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to: identify the one or more parameters for speech, wherein the one or more parameters are selected from a group of measures including: pauses, hesitations, interruptions, vibrato, stress, timbre, stuttering, laughter, volume, and word rate; analyze the one or more parameters for speech; and produce at least one output data point for each of the one or more parameters for speech. | 2. The computer program product of claim 1 , wherein analyzing the vocal and video recordings for the first user according to one or more parameters for speech and one or more parameters for gestures comprises program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to: identify the one or more parameters for speech, wherein the one or more parameters are selected from a group of measures including: pauses, hesitations, interruptions, vibrato, stress, timbre, stuttering, laughter, volume, and word rate; analyze the one or more parameters for speech; and produce at least one output data point for each of the one or more parameters for speech. 4. The computer program product of claim 2 , wherein determining one or more emotions and a role in the meeting for the first user comprises program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to: identify one or more highest recurring output data points from the at least one output data point for each of the one or more parameters for gestures; identify the one or more highest recurring output data points as the one or more emotions for the first user; and determine the role in the meeting for the first user based at least on the identified one or more emotions for the first user. | 0.834644 |
7,599,899 | 5 | 8 | 5. A computer implemented method of creating a prose style of a user, for the purpose of applying said prose style to an information of interest in a given context, comprising the steps of: providing equivalent name sets; deriving a plurality of preferred equivalent name set entries from said equivalent name sets for said given context; providing a plurality of equivalent pattern specification sets; deriving a preferred pattern specification set from said equivalent pattern specification sets for the given context; and creating said prose style based on said preferred equivalent name set entries and said preferred pattern specification sets. | 5. A computer implemented method of creating a prose style of a user, for the purpose of applying said prose style to an information of interest in a given context, comprising the steps of: providing equivalent name sets; deriving a plurality of preferred equivalent name set entries from said equivalent name sets for said given context; providing a plurality of equivalent pattern specification sets; deriving a preferred pattern specification set from said equivalent pattern specification sets for the given context; and creating said prose style based on said preferred equivalent name set entries and said preferred pattern specification sets. 8. The computer implemented method of claim 5 , wherein the preferred pattern specification set further comprises embellishments that are words or phrases that the user characteristically uses to describe a subject, an object or a verb, and wherein said embellishments are applicable for creating said prose style and are selected from the equivalent name sets depending on the context of the information of interest. | 0.707163 |
7,617,202 | 9 | 11 | 9. A system embodied on a computer readable storage medium, that employs distributional analysis on a query log to facilitate improving search engine query results, comprising: a component that obtains a set of queries by mining queries from a query log based on at least one of a distributional algorithm, a substring, a string, or a user identification, wherein the set of queries comprises a saved search query or a null set; a profiling component that generates probability distributional profiles for the set of queries based at least on one of a substring distribution algorithm that represents a distribution characteristic for a substring as a probability distribution over strings from the query log that include the substring or a string sequence distribution algorithm that represents a distribution characteristic for a query as a probability distribution of queries that a user queries subsequent the query, wherein the obtained set of queries is dependent upon the distribution algorithm; and a similarity component that employs the distributional profiles to output query terms with similar profiles by generating a distributional similarity between the distributional profiles. | 9. A system embodied on a computer readable storage medium, that employs distributional analysis on a query log to facilitate improving search engine query results, comprising: a component that obtains a set of queries by mining queries from a query log based on at least one of a distributional algorithm, a substring, a string, or a user identification, wherein the set of queries comprises a saved search query or a null set; a profiling component that generates probability distributional profiles for the set of queries based at least on one of a substring distribution algorithm that represents a distribution characteristic for a substring as a probability distribution over strings from the query log that include the substring or a string sequence distribution algorithm that represents a distribution characteristic for a query as a probability distribution of queries that a user queries subsequent the query, wherein the obtained set of queries is dependent upon the distribution algorithm; and a similarity component that employs the distributional profiles to output query terms with similar profiles by generating a distributional similarity between the distributional profiles. 11. The system of claim 9 , the profiling component further comprising determining the frequency of occurrence for respective search queries, and employing the frequency of occurrence to generate a substring distributional profile. | 0.609797 |
8,918,734 | 1 | 2 | 1. A system for disambiguating a text input of a sub-word of a long word on an electronic device comprising: a memory storing computer-executable instructions of: a virtual keyboard having a plurality of virtual keys; the virtual keyboard receiving input from a pointing device that is placed on a key of the keyboard corresponding to the first character of the sub-word and moved to subsequent keys corresponding to subsequent characters of the sub-word, wherein the received input represents a trajectory pattern; a dictionary database associated with the keyboard and the pointing device, the dictionary database comprising words and associated frequencies of usage; a long word dictionary (LWD) derived from the dictionary database, the LWD having a smaller size than the dictionary database and configured according to an arrangement of the keys in the keyboard; and a partial trajectory recognition module associated with the keyboard and the pointing device, and configured to evaluate the trajectory pattern to produce sub-word solutions; wherein the sub-word solutions are used in conjunction with the LWD to generate at least one prediction solution corresponding to at least one long word, and a processor for executing the computer-executable instructions stored in the memory. | 1. A system for disambiguating a text input of a sub-word of a long word on an electronic device comprising: a memory storing computer-executable instructions of: a virtual keyboard having a plurality of virtual keys; the virtual keyboard receiving input from a pointing device that is placed on a key of the keyboard corresponding to the first character of the sub-word and moved to subsequent keys corresponding to subsequent characters of the sub-word, wherein the received input represents a trajectory pattern; a dictionary database associated with the keyboard and the pointing device, the dictionary database comprising words and associated frequencies of usage; a long word dictionary (LWD) derived from the dictionary database, the LWD having a smaller size than the dictionary database and configured according to an arrangement of the keys in the keyboard; and a partial trajectory recognition module associated with the keyboard and the pointing device, and configured to evaluate the trajectory pattern to produce sub-word solutions; wherein the sub-word solutions are used in conjunction with the LWD to generate at least one prediction solution corresponding to at least one long word, and a processor for executing the computer-executable instructions stored in the memory. 2. The system according to claim 1 , wherein the pointing device is at least one chosen from the list including: a finger; a mouse; a remote control; and a pen. | 0.503106 |
7,496,854 | 50 | 52 | 50. A computer system related to information handling within a document operated on by a first application program, the document containing first information that can be utilized in a second application program, comprising: means for identifying without user intervention or designation the first information; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. | 50. A computer system related to information handling within a document operated on by a first application program, the document containing first information that can be utilized in a second application program, comprising: means for identifying without user intervention or designation the first information; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. 52. The computer system of claim 50 , wherein the means for inserting the second information into the document further comprises: means for initializing the second application program; means for searching, using the second application program, for the second information associated with the first information; and means for retrieving the second information. | 0.580796 |
9,588,965 | 8 | 9 | 8. A system for identifying and characterizing an analogy in a document, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is capable of executing instructions to perform steps of: identifying a candidate document, wherein the candidate document comprises an analogy for a target concept, a region of interest and a linguistic marker included in the region of interest; classifying the candidate document as an analogy document or a non-analogy document based upon a size of the region of interest and a count of the linguistic marker; identifying a source concept from the analogy document, wherein the source concept comprises the analogy; and characterizing the source concept with corresponding metadata, wherein the metadata comprises a familiarity of the source concept, a length of the source concept, and a readability of the source concept, and wherein the familiarity of the source concept is calculated using an extracting Distributional related words using Co-occurrences (DISCO) tool, the length of the source concept is calculated using the size of the region of interest, and the readability of the source concept is calculated using a Flesch-Kincaid readability score method. | 8. A system for identifying and characterizing an analogy in a document, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is capable of executing instructions to perform steps of: identifying a candidate document, wherein the candidate document comprises an analogy for a target concept, a region of interest and a linguistic marker included in the region of interest; classifying the candidate document as an analogy document or a non-analogy document based upon a size of the region of interest and a count of the linguistic marker; identifying a source concept from the analogy document, wherein the source concept comprises the analogy; and characterizing the source concept with corresponding metadata, wherein the metadata comprises a familiarity of the source concept, a length of the source concept, and a readability of the source concept, and wherein the familiarity of the source concept is calculated using an extracting Distributional related words using Co-occurrences (DISCO) tool, the length of the source concept is calculated using the size of the region of interest, and the readability of the source concept is calculated using a Flesch-Kincaid readability score method. 9. The system of claim 8 , wherein the processor is further capable of executing instructions to perform steps of defining the region of interest in the candidate document; identifying the size of the region of interest; and detecting the count of linguistic marker included in the region of interest. | 0.501656 |
9,516,155 | 4 | 5 | 4. The method of claim 1 , the mobile device further maintaining character data that defines at least one of the two or more related message templates associated with the category. | 4. The method of claim 1 , the mobile device further maintaining character data that defines at least one of the two or more related message templates associated with the category. 5. The method of claim 4 , the mobile device further maintaining one or more fill tags that enables a user to add character data to at least one of the two or more related template messages. | 0.94898 |
9,672,524 | 20 | 23 | 20. A method for organizing, managing, and reporting data relating to a corporate entity, comprising: retrieving an entity record comprising a value and a lineage entry, the lineage entry comprising a value source, the value source referencing a first document; retrieving a corporate action stored as a computer-readable process definition, the corporate action defining a set of stakeholders; creating a second document based on the entity record and on stakeholder input; applying a status tag to the second document indicating a status of the second document in a document workflow, the status tag being applied as a human-readable, freeform text format data object associated with the second document; and storing the second document record in association with both a hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags. | 20. A method for organizing, managing, and reporting data relating to a corporate entity, comprising: retrieving an entity record comprising a value and a lineage entry, the lineage entry comprising a value source, the value source referencing a first document; retrieving a corporate action stored as a computer-readable process definition, the corporate action defining a set of stakeholders; creating a second document based on the entity record and on stakeholder input; applying a status tag to the second document indicating a status of the second document in a document workflow, the status tag being applied as a human-readable, freeform text format data object associated with the second document; and storing the second document record in association with both a hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags. 23. The method of claim 20 , further comprising: applying a document type tag to the second document based on contents of the second document; and retrieving, using the document type tag, the second document and a third document sharing the same document type tag. | 0.825166 |
7,904,298 | 1 | 12 | 1. A method of multi-modal text prediction, comprising: (a) receiving a speech waveform corresponding to text to be recognized; (b) receiving at least one letter corresponding to a portion of the text, the at least one letter being received from an unambiguous data source; (c) dynamically determining a search network based on the at least one letter, the search network including units of sound based on the at least one letter; (d) applying speech recognition techniques that pattern-match the speech waveform against the search network to generate a list of matching text choices; (e) re-ordering the list of matching text choices using a statistical language model, the statistical language model using usage statistics; (f) providing the re-ordered list to a user interface for a determination whether one of the words in the list is the text to be recognized; and (g) reiterating steps (b) to (f) until one of the words in the list is the text to be recognized. | 1. A method of multi-modal text prediction, comprising: (a) receiving a speech waveform corresponding to text to be recognized; (b) receiving at least one letter corresponding to a portion of the text, the at least one letter being received from an unambiguous data source; (c) dynamically determining a search network based on the at least one letter, the search network including units of sound based on the at least one letter; (d) applying speech recognition techniques that pattern-match the speech waveform against the search network to generate a list of matching text choices; (e) re-ordering the list of matching text choices using a statistical language model, the statistical language model using usage statistics; (f) providing the re-ordered list to a user interface for a determination whether one of the words in the list is the text to be recognized; and (g) reiterating steps (b) to (f) until one of the words in the list is the text to be recognized. 12. The method recited in claim 1 , wherein dynamically determining the search network comprises dynamically generating the search network from a base lexicon. | 0.567935 |
9,684,701 | 1 | 12 | 1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database using a processor before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node. | 1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database using a processor before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node. 12. A method as recited in claim 1 , wherein the semantic command is determined not to have a conflict with the master version of the database, and further including sending the semantic command to the second node having a second local version of the database to replicate any IP address assignment changes associated with the semantic command on the second node. | 0.721198 |
8,583,580 | 1 | 4 | 1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts. | 1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts. 4. The method according to claim 1 , wherein identifying a group of syntactic structures comprises identifying a phrase. | 0.929988 |
9,552,414 | 15 | 20 | 15. An application search server comprising: a non-transitory computer-readable medium storing a plurality of application indexes, wherein each application index corresponds to one or more application categories of a plurality of application categories and wherein each application index comprises identifiers for a plurality of application representations; one or more processors that execute computer program instructions that when executed cause the one or more processors to: receive a search query from a computing device associated with a partner system; identify an application category based on the received search query, the application category indicating a platform executing on the computing device; select an index from the plurality of application indexes based on the identified application category and a partner identifier of the partner system; query the selected index corresponding to the identified application category to identify a first plurality of application representations associated with the identified application category; identify a second application category based on the received search query; select a second index from the plurality of application indexes based on the second identified application category and the partner identifier; query the second index to identify a second plurality of application representations corresponding to the second application category; generate search results based on a union of the first plurality of application representations and the second plurality of application representations; and provide, for display, the generated search results to the computing device. | 15. An application search server comprising: a non-transitory computer-readable medium storing a plurality of application indexes, wherein each application index corresponds to one or more application categories of a plurality of application categories and wherein each application index comprises identifiers for a plurality of application representations; one or more processors that execute computer program instructions that when executed cause the one or more processors to: receive a search query from a computing device associated with a partner system; identify an application category based on the received search query, the application category indicating a platform executing on the computing device; select an index from the plurality of application indexes based on the identified application category and a partner identifier of the partner system; query the selected index corresponding to the identified application category to identify a first plurality of application representations associated with the identified application category; identify a second application category based on the received search query; select a second index from the plurality of application indexes based on the second identified application category and the partner identifier; query the second index to identify a second plurality of application representations corresponding to the second application category; generate search results based on a union of the first plurality of application representations and the second plurality of application representations; and provide, for display, the generated search results to the computing device. 20. The application search server of claim 15 , wherein the instructions cause the one or more processors to identify the application category based on the received search query by identifying an association between a platform identifier of the computing device and an application category. | 0.683406 |
6,061,063 | 12 | 15 | 12. The computer product of claim 11, wherein said second blank region has a height equal to h-h/k. | 12. The computer product of claim 11, wherein said second blank region has a height equal to h-h/k. 15. The computer product of claim 12, wherein a field comprises one or more text characters. | 0.972537 |
7,949,738 | 1 | 6 | 1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. | 1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. 6. The computer-readable memory of claim 1 , wherein the rule-editing area contains: a menu having a set of user-selectable options for determining the action name of the action; and a text-entry field to accept user input for determining the action value of the action. | 0.719335 |
7,865,561 | 16 | 17 | 16. The system of claim 11 , wherein the updated spam detection rules are obtained from the email server after spam detection rules used by the email server are updated. | 16. The system of claim 11 , wherein the updated spam detection rules are obtained from the email server after spam detection rules used by the email server are updated. 17. The system of claim 16 , wherein the updated spam detection rules are the updated spam detection rules of the email server. | 0.93906 |
8,880,519 | 9 | 13 | 9. A computer program product comprising: a computer readable hardware storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method for determining a service description that most closely matches a service name provided by a user, said method comprising: said processor determining that the service name provided by the user is not an exact match to a service name in a service registry that comprises service names and associated service descriptions; said processor generating a ranked service name list by use of a name parser, a dictionary, and a name composer, wherein the ranked service name list comprise at least one alternative service name and a respective rank of each alternative service name of the at least one alternative service name, and wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining a service description associated with a service name in the service registry that either matches the highest ranked alternative service name in the service name list or if not, matches a second alternative service name which is the next highest ranked alternative service name in the service name list; and said processor communicating the ascertained service description to the user. | 9. A computer program product comprising: a computer readable hardware storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method for determining a service description that most closely matches a service name provided by a user, said method comprising: said processor determining that the service name provided by the user is not an exact match to a service name in a service registry that comprises service names and associated service descriptions; said processor generating a ranked service name list by use of a name parser, a dictionary, and a name composer, wherein the ranked service name list comprise at least one alternative service name and a respective rank of each alternative service name of the at least one alternative service name, and wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining a service description associated with a service name in the service registry that either matches the highest ranked alternative service name in the service name list or if not, matches a second alternative service name which is the next highest ranked alternative service name in the service name list; and said processor communicating the ascertained service description to the user. 13. The computer program product of claim 9 , said ascertaining comprising: searching a top rank by locating a greatest value among all ranks in the ranked service name list; and looking up the service registry for the service description with a first alternative service name associated with the top rank from said searching such that the service description is associated with the highest ranked alternative service name. | 0.790801 |
9,992,642 | 17 | 18 | 17. A method, comprising: receiving audio input data from a first device, the audio input data corresponding to an uninterrupted user utterance that includes a spoken instruction for performing an action and an intended recipient account for the action; determining a customer account for which the first device is enabled to send and receive a data transmission via a connection to a data network, the data transmission initiated upon the uninterrupted user utterance received by a microphone of the first device; generating message body data based at least in part on the audio input data; identifying the intended recipient account based at least in part on the audio input data; determining that an electronic communication to be sent to the intended recipient account is a first electronic communication sent from the customer account to the intended recipient account as part of the action; generating first electronic message data that includes information to indicate a name for the customer account; generating second electronic message data that includes the message body data; sending the first electronic message data to the intended recipient account; and sending the second electronic message data to the intended recipient account. | 17. A method, comprising: receiving audio input data from a first device, the audio input data corresponding to an uninterrupted user utterance that includes a spoken instruction for performing an action and an intended recipient account for the action; determining a customer account for which the first device is enabled to send and receive a data transmission via a connection to a data network, the data transmission initiated upon the uninterrupted user utterance received by a microphone of the first device; generating message body data based at least in part on the audio input data; identifying the intended recipient account based at least in part on the audio input data; determining that an electronic communication to be sent to the intended recipient account is a first electronic communication sent from the customer account to the intended recipient account as part of the action; generating first electronic message data that includes information to indicate a name for the customer account; generating second electronic message data that includes the message body data; sending the first electronic message data to the intended recipient account; and sending the second electronic message data to the intended recipient account. 18. The method of claim 17 , further including: providing the customer account with a contacts authority; identifying the intended recipient account as a contact in the contacts authority; identifying a mobile telephone number for the intended recipient account; determining a relationship between the customer account and the intended recipient account; and including in the second electronic message data one of an image for the customer account, a video file for the customer account, or a second URL that references the audio input data based at least in part on the relationship. | 0.753378 |
9,558,280 | 17 | 26 | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. 26. The apparatus of claim 17 , wherein said computer-readable medium coupled to said one or more processors has further instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations further comprising: selecting an ad based on a count of location records of the user's contacts associated with said ad from a database; and sending said ad to said client device. | 0.867638 |
10,114,872 | 12 | 14 | 12. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 12. An apparatus for analyzing data, the apparatus comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to generate, by an entity, a query based at least in part on a topic of interest; to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 14. The apparatus of claim 12 , in which the plurality of data sources include open-source data sources that are publically available and closed-source data sources that are not publically accessible. | 0.789916 |
9,244,887 | 37 | 47 | 37. A machine-readable non-transitory storage medium, including instructions configured to cause a data processing system to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation. | 37. A machine-readable non-transitory storage medium, including instructions configured to cause a data processing system to perform operations including: analyzing, using a time series engine, a distribution of unstructured time-stamped data to identify a plurality of potential time series data hierarchies for structuring the unstructured time-stamped data, wherein a potential time series data hierarchy is a framework for structuring the data through use of multiple time series, and wherein the time series engine is at a server layer of a time series computing system; performing, using the time series engine, an analysis of the plurality of potential time series data hierarchies, wherein performing the analysis of the plurality of potential time series data hierarchies includes determining an optimal time series frequency and a data sufficiency metric for each of the plurality of potential time series data hierarchies; comparing data sufficiency metrics for the plurality of potential time series data hierarchies; selecting a hierarchy of the plurality of potential time series data hierarchies based on the comparison of the data sufficiency metrics; structuring the unstructured time-stamped data into structured time-stamped data according to the hierarchy and the optimal time series frequency, wherein structuring the transformed time-stamped data into the structured time-stamped data is performed using a single pass of the unstructured time-stamped data through the time series engine; computing a plurality of transformations of the structured time-stamped data using the single pass of the structured time-stamped data through the time series engine; transforming the structured time-stamped data into transformed time-stamped data according to the plurality of transformations; and providing, using an application programming interface, the transformed time-stamped data for visual presentation. 47. The machine-readable non-transitory storage medium of claim 37 , further comprising instructions configured to cause a data processing system to perform operations including: outputting, using the time series engine, information corresponding to the structured data, wherein outputting the information is performed using the single pass of the time stamped unstructured data. | 0.722141 |
10,108,680 | 1 | 4 | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of financial data, operational data, human resources data, production data, information technology data, or a combination thereof; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of financial data, operational data, human resources data, production data, information technology data, or a combination thereof; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 4. The method of claim 1 , in which the plurality of data sources include open-source data sources that are publically available and closed-source data sources that are not publically accessible. | 0.839109 |
9,152,674 | 10 | 11 | 10. The server of claim 8 , wherein the result processing module is configured to determine the initial result set by, for each application representation in the consideration set: determining the one or more query/result features of the application representation; and augmenting the features of the application representation with the one or more query/result features. | 10. The server of claim 8 , wherein the result processing module is configured to determine the initial result set by, for each application representation in the consideration set: determining the one or more query/result features of the application representation; and augmenting the features of the application representation with the one or more query/result features. 11. The server of claim 10 , wherein the scoring module is configured to determine the score for each application representation in the initial result set by, for each application representation, inputting the features of the application representation, the query/result features of the application representation, and the query features into the one or more scoring models. | 0.925646 |
9,049,123 | 9 | 10 | 9. A system comprising: a processor; a data bus coupled to the processor; a module for receiving a function template for at least one permissible action on a given resource type, the function template comprising an annotation of indications of success and failure; a module for performing an action on a resource based upon the resource type and the function template corresponding to the given resource type; and, a module for determining a policy follow up action based upon the annotation of indications of success and failure, the policy follow-up action conforming to a definite course of action to guide and determine present and future decisions, the policy follow-up action conforming to a distributed management task force (DMTF) policy model, the DMTF policy model providing a common framework for specifying system behaviors that are scalable to configuring computer systems; and wherein the annotation of indications of success and failure is associated with a Policy Action class of the DMTF policy model, the Policy Action class comprises a CopyData Policy Action comprising a directive to copy data and the directive returns a failure indication comprising a failure annotation, the failure annotation being associated with the Policy Action, the failure annotation being set forth as FAILURE:=0; the DMTF policy model comprises a role-based deployment framework, the role-based deployment framework comprising an administratively assigned name for an enforcement role played by the DMTF policy model when consuming sets of policy rules. | 9. A system comprising: a processor; a data bus coupled to the processor; a module for receiving a function template for at least one permissible action on a given resource type, the function template comprising an annotation of indications of success and failure; a module for performing an action on a resource based upon the resource type and the function template corresponding to the given resource type; and, a module for determining a policy follow up action based upon the annotation of indications of success and failure, the policy follow-up action conforming to a definite course of action to guide and determine present and future decisions, the policy follow-up action conforming to a distributed management task force (DMTF) policy model, the DMTF policy model providing a common framework for specifying system behaviors that are scalable to configuring computer systems; and wherein the annotation of indications of success and failure is associated with a Policy Action class of the DMTF policy model, the Policy Action class comprises a CopyData Policy Action comprising a directive to copy data and the directive returns a failure indication comprising a failure annotation, the failure annotation being associated with the Policy Action, the failure annotation being set forth as FAILURE:=0; the DMTF policy model comprises a role-based deployment framework, the role-based deployment framework comprising an administratively assigned name for an enforcement role played by the DMTF policy model when consuming sets of policy rules. 10. The system of claim 9 wherein: the annotation comprises a user specified status indication; wherein the module for determining a policy follow up action based upon the annotation of indications of success and failure further comprises determining a policy follow up action based upon the user specified indication. | 0.766862 |
9,477,646 | 1 | 4 | 1. A computer-implemented method of drawing an arbitrary graphics object in a web page comprising: creating, by a web browser, a file in a non-transitory computer readable storage medium, including coded markup language that specifies a drawing space as an extent within the web page and coded procedural language that specifies a drawing command to draw the arbitrary graphics object in the drawing space in the web page; creating the drawing space within the web page using the coded markup language; and drawing, by the web browser, the arbitrary graphics object into the drawing space within the web page using the coded procedural language. | 1. A computer-implemented method of drawing an arbitrary graphics object in a web page comprising: creating, by a web browser, a file in a non-transitory computer readable storage medium, including coded markup language that specifies a drawing space as an extent within the web page and coded procedural language that specifies a drawing command to draw the arbitrary graphics object in the drawing space in the web page; creating the drawing space within the web page using the coded markup language; and drawing, by the web browser, the arbitrary graphics object into the drawing space within the web page using the coded procedural language. 4. The method of claim 1 , wherein coding procedural language that specifies the drawing command to draw the arbitrary graphics object is in response to receiving, at an application, a user input graphically representing the arbitrary graphics object within the web page. | 0.798961 |
9,477,711 | 18 | 19 | 18. The system of claim 17 , wherein determining that content items for only a first of the two identified content categories will be presented in the particular module type comprises: determining that presenting both of the of the two identified content categories in the particular module type will cause a number of the knowledge modules of the particular module type to exceed a maximum number of knowledge modules that are allowed to be of the particular module type; and determining that the content items in the first content category have a higher rank score than the rank score for the content items in the second content category. | 18. The system of claim 17 , wherein determining that content items for only a first of the two identified content categories will be presented in the particular module type comprises: determining that presenting both of the of the two identified content categories in the particular module type will cause a number of the knowledge modules of the particular module type to exceed a maximum number of knowledge modules that are allowed to be of the particular module type; and determining that the content items in the first content category have a higher rank score than the rank score for the content items in the second content category. 19. The system of claim 18 , wherein the one or more processors are further configured to perform operations comprising selecting the content items in the first content category for presentation in the particular module type, the selection being in response to determining that the rank score for the content items in the first content category is greater than the rank score for the content items in the second content category. | 0.930538 |
8,612,466 | 1 | 4 | 1. A computer executable document search method for searching for a document, comprising: generating, based on user information represented as a group hierarchy having a user identifier and one or more groups joined by one or more operators, an inclusion relationship expression including an operator that designates an inclusion relationship for access authority; combining the inclusion relationship expression with a received search expression to generate a combined search expression; for searching at a private level, using the combined search expression to generate a first search expression using the received search expression and specifying the user identifier without specifying the one or more groups; and for searching at a shared level, using the combined search expression to generate a second search expression using the received search expression and specifying the one or more groups without specifying the user identifier. | 1. A computer executable document search method for searching for a document, comprising: generating, based on user information represented as a group hierarchy having a user identifier and one or more groups joined by one or more operators, an inclusion relationship expression including an operator that designates an inclusion relationship for access authority; combining the inclusion relationship expression with a received search expression to generate a combined search expression; for searching at a private level, using the combined search expression to generate a first search expression using the received search expression and specifying the user identifier without specifying the one or more groups; and for searching at a shared level, using the combined search expression to generate a second search expression using the received search expression and specifying the one or more groups without specifying the user identifier. 4. The document search method according to claim 1 , wherein combining further comprises: registering the search result generated from executing the first search expression at the private level as a cache item using a hash value generated from the first search expression. | 0.790447 |
8,738,358 | 1 | 5 | 1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server. | 1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server. 5. The method of claim 1 , wherein step c. comprises the steps of: c.1. sending a request to a translator application server for the translation of the message from the first language into the language used by each of the multiple SM servers; and c.2. receiving back the translation of the message in the language used by each of the multiple SM servers. | 0.779851 |
8,249,906 | 5 | 6 | 5. The planning method according to claim 4 , further comprising the steps of: a) calculating, by such at least one computational device, at least one cut float value relating to such at least one time-dependent relationship i) wherein such calculation comprises CF j =min [min[H ij +AF j ], H i,m ], where “H i,m ” denotes the such at least one relationship float value between such at least one “I” activity and a connected, one milestone deadline; and b) displaying, continuously, by such at least one computational device, such at least one cut float value on such at least one time-scaled calendar on such at least one graphical user interface. | 5. The planning method according to claim 4 , further comprising the steps of: a) calculating, by such at least one computational device, at least one cut float value relating to such at least one time-dependent relationship i) wherein such calculation comprises CF j =min [min[H ij +AF j ], H i,m ], where “H i,m ” denotes the such at least one relationship float value between such at least one “I” activity and a connected, one milestone deadline; and b) displaying, continuously, by such at least one computational device, such at least one cut float value on such at least one time-scaled calendar on such at least one graphical user interface. 6. The planning method according to claim 5 , further comprising the steps of: a) calculating, by such at least one computational device, at least one reverse float value relating to such at least one time-dependent relationship i) wherein such calculation comprises RF j =min [RF i +H i,j ], for all “I”, where “I” denotes each and every predecessor activity, of a plurality of such predecessor activities to at least one “J” activity and “H i,j ” denotes such at least one relationship float value relating to each and every such predecessor activity; and b) displaying, continuously, by such at least one computational device, such at least one reverse float value on such at least one time-scaled calendar on such at least one graphical user interface. | 0.807438 |
7,672,922 | 2 | 6 | 2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation). | 2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation). 6. The pointer-oriented object acquisition method according to claim 2 , characterized in that the element functions of a class of the abstract object which manipulate with the element variables are initialized with the objects of the classes in which the words that belong to the word stem of a verb of the natural language in which the computer system of Artificial Intelligence of a cyborg or an android is working at this timeframe are classified and are instantiated under the element variable that is represented with an object of the class in which words that belong to the word stem of the verb “do” are classified. | 0.785763 |
5,555,343 | 5 | 10 | 5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table. | 5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table. 10. A text processor according to claim 5, wherein said look-up table is comprised by format templates. | 0.960078 |
4,450,520 | 6 | 7 | 6. The method of claim 1 wherein each state additionally has instructions which indicate a successful match of an element of the pattern. | 6. The method of claim 1 wherein each state additionally has instructions which indicate a successful match of an element of the pattern. 7. The method of claim 6 wherein the indication of a successful match additionally includes an identifier for the specific element of the pattern that has been matched. | 0.969197 |
8,468,142 | 1 | 2 | 1. A method comprising: constructing, by one or more computer systems, a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; constructing, by the one or more computer systems, a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; constructing, by the one or more computer systems, a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; constructing, by the one or more computer systems, a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; constructing, by the one or more computer systems, a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing, by the one or more computer systems, a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. | 1. A method comprising: constructing, by one or more computer systems, a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; constructing, by the one or more computer systems, a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; constructing, by the one or more computer systems, a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; constructing, by the one or more computer systems, a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; constructing, by the one or more computer systems, a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing, by the one or more computer systems, a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. 2. The method of claim 1 , wherein: the sixth BDD comprises: a binary 0 terminal node; a binary 1 terminal node; and a plurality of paths, each path comprising a plurality of decision nodes and leading to either the 0 terminal node or the 1 terminal node, and for each of the paths that leads to the 1 terminal node, a web page represented by first one or more of the decision nodes on the path is included in a search result for a search query represented by second one or more of the decision nodes on the path. | 0.504826 |
7,502,738 | 16 | 17 | 16. The system according to claim 1 , wherein the parser formulates at least one request in accordance with a grammar that the selected domain agent uses to process requests associated with the context for the one or more keywords contained in the utterance. | 16. The system according to claim 1 , wherein the parser formulates at least one request in accordance with a grammar that the selected domain agent uses to process requests associated with the context for the one or more keywords contained in the utterance. 17. The system according to claim 16 , wherein the parser provides the formulated request to the event manager to invoke the selected domain agent, and the event manager sends and receives one or more events to the agent architecture to process the formulated request, the event manager thereby coordinating interaction between the parser and the agent architecture. | 0.824713 |
5,486,112 | 1 | 11 | 1. An autonomous wearable computing device comprising: a first glove having fingers and a second glove having fingers, said first glove being adapted to fit the left hand of a user, said first glove having a first portion on a palm side and a second portion on a back side, said second glove being adapted to fit the right hand of said user, said second glove having a third portion on a palm side and a fourth portion on a back side, said first glove having a first set of indicia mounted on said first portion thereof and a second set of indicia mounted on said second portion thereof, said second glove having a third set of indicia mounted on said third portion thereof, and a fourth set of indicia mounted on said fourth portion thereof; first keys mounted within the first portion of said first glove in association with each indicium of said first set of indicia, said first keys corresponding to the keys of a keyboard of arbitrary format and content to be struck by the fingers of the left hand, said first keys having indicia mounted thereon, said indicia mounted on said first keys identifying the letters, numbers, or symbols associated to said first keys; second keys mounted within the third portion of said second glove in association with each indicium of said third set of indicia, said second keys corresponding to the keys of said keyboard to be struck by the fingers of the right hand, said second keys having indicia mounted thereon, said indicia mounted on said second keys identifying the letters, numbers, or symbols associated to said second keys; the positions of said first set of indicia and said second set of indicia being mirror images of each other, said second set of indicia thereby corresponding to said first keys of said first glove, and providing said user with a representation of said first keys; the positions of said third set of indicia and said fourth set of indicia being mirror images of each other, said fourth set of indicia thereby corresponding to said second keys of said second glove, and providing said user with a representation of said second keys; a first microprocessor connected to said first keys of said first glove with a first set of interconnections, said first set of interconnections being embedded within said first glove; a second microprocessor connected to said second keys of said second glove with a second set of interconnections, said second set of interconnections being embedded within said second glove; said first microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said first glove to be struck by the fingers of the left hand, said second glove microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said second glove to be struck by the fingers of the right hand; said first microprocessor monitoring the flow of data input through the keys of said first glove, said second microprocessor monitoring the flow of data input through the keys of said second glove; a first set of external input/output ports mounted within said first glove, a second set of external input/output ports mounted within said second glove; said first and second sets of ports allowing said gloves to be interfaced with any processing unit that can be interfaced with a conventional keyboard; first means for enabling said gloves to transmit and receive information to and from any data processing unit that can be interfaced with said gloves, and allowing said user to easily interpret the information that is transmitted or received; second means for providing said gloves with autonomous computing capabilities. | 1. An autonomous wearable computing device comprising: a first glove having fingers and a second glove having fingers, said first glove being adapted to fit the left hand of a user, said first glove having a first portion on a palm side and a second portion on a back side, said second glove being adapted to fit the right hand of said user, said second glove having a third portion on a palm side and a fourth portion on a back side, said first glove having a first set of indicia mounted on said first portion thereof and a second set of indicia mounted on said second portion thereof, said second glove having a third set of indicia mounted on said third portion thereof, and a fourth set of indicia mounted on said fourth portion thereof; first keys mounted within the first portion of said first glove in association with each indicium of said first set of indicia, said first keys corresponding to the keys of a keyboard of arbitrary format and content to be struck by the fingers of the left hand, said first keys having indicia mounted thereon, said indicia mounted on said first keys identifying the letters, numbers, or symbols associated to said first keys; second keys mounted within the third portion of said second glove in association with each indicium of said third set of indicia, said second keys corresponding to the keys of said keyboard to be struck by the fingers of the right hand, said second keys having indicia mounted thereon, said indicia mounted on said second keys identifying the letters, numbers, or symbols associated to said second keys; the positions of said first set of indicia and said second set of indicia being mirror images of each other, said second set of indicia thereby corresponding to said first keys of said first glove, and providing said user with a representation of said first keys; the positions of said third set of indicia and said fourth set of indicia being mirror images of each other, said fourth set of indicia thereby corresponding to said second keys of said second glove, and providing said user with a representation of said second keys; a first microprocessor connected to said first keys of said first glove with a first set of interconnections, said first set of interconnections being embedded within said first glove; a second microprocessor connected to said second keys of said second glove with a second set of interconnections, said second set of interconnections being embedded within said second glove; said first microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said first glove to be struck by the fingers of the left hand, said second glove microprocessor having the functionality of a conventional keyboard microprocessor for the keys of said second glove to be struck by the fingers of the right hand; said first microprocessor monitoring the flow of data input through the keys of said first glove, said second microprocessor monitoring the flow of data input through the keys of said second glove; a first set of external input/output ports mounted within said first glove, a second set of external input/output ports mounted within said second glove; said first and second sets of ports allowing said gloves to be interfaced with any processing unit that can be interfaced with a conventional keyboard; first means for enabling said gloves to transmit and receive information to and from any data processing unit that can be interfaced with said gloves, and allowing said user to easily interpret the information that is transmitted or received; second means for providing said gloves with autonomous computing capabilities. 11. The autonomous wearable computing device as claimed in claim 1 wherein said first means comprise: a first microdisk interface mounted within said first glove and connected to a first internal data processing unit; a second microdisk interface mounted within said second glove and connected to a second internal data processing unit; said microdisk interfaces providing said gloves with data input and output capabilities. | 0.847561 |
4,122,533 | 3 | 5 | 3. The system set forth in claim 2 wherein said first means includes directory memory means containing data representative of a said set of symbol generating means to be operated for each selectable language. | 3. The system set forth in claim 2 wherein said first means includes directory memory means containing data representative of a said set of symbol generating means to be operated for each selectable language. 5. The system set forth in claim 3 wherein said first means includes switching means for energizing the predetermined ones of said directory memory means corresponding to the language selected by said language selection means. | 0.925265 |
7,505,409 | 8 | 13 | 8. A Generic Framing Procedure (GFP) data mapping device for adjusting a transmission rate of ISC words, comprising: a transceiver configured to receive ISC words and to transmit ISC words; a FIFO buffer operably coupled to the transceiver configured to store ISC words received by the transceiver; and a processor operably coupled to the FIFO buffer, the processor configured to read first and second ISC words from the FIFO buffer; the processor further configured to determine whether a first number of ISC words stored in the FIFO buffer is greater than a second predetermined number indicating an over-running condition; the processor further configured to determine whether the first and second ISC words indicate either an ISC continuous sequence of words or an ISC idle sequence of words only if the first number of ISC words is greater than the second predetermined number; the processor further configured to delete the first and second ISC words only if the first and second ISC words indicate either the ISC continuous sequence of words or the ISC idle sequence of words, and the first number of ISC words is greater than the second predetermined number indicating the over-running; and the processor further configured to read a third ISC word from the FIFO buffer and to induce the transceiver to transmit the third ISC word. | 8. A Generic Framing Procedure (GFP) data mapping device for adjusting a transmission rate of ISC words, comprising: a transceiver configured to receive ISC words and to transmit ISC words; a FIFO buffer operably coupled to the transceiver configured to store ISC words received by the transceiver; and a processor operably coupled to the FIFO buffer, the processor configured to read first and second ISC words from the FIFO buffer; the processor further configured to determine whether a first number of ISC words stored in the FIFO buffer is greater than a second predetermined number indicating an over-running condition; the processor further configured to determine whether the first and second ISC words indicate either an ISC continuous sequence of words or an ISC idle sequence of words only if the first number of ISC words is greater than the second predetermined number; the processor further configured to delete the first and second ISC words only if the first and second ISC words indicate either the ISC continuous sequence of words or the ISC idle sequence of words, and the first number of ISC words is greater than the second predetermined number indicating the over-running; and the processor further configured to read a third ISC word from the FIFO buffer and to induce the transceiver to transmit the third ISC word. 13. The data mapping device of claim 8 , wherein the processor is farther configured to determine whether the first number of ISC words stored in the FIFO buffer is less than a third predetermined number indicating an under-running condition, the processor further configured to induce the transceiver to transmit a third ISC null word. | 0.732909 |
8,429,188 | 2 | 4 | 2. The method of claim 1 , further comprising weighting the learned content preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed descriptive terms, number of selections of the content item having the analyzed descriptive terms, and time of use of the content item having the analyzed descriptive terms, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned content preferences so that content items associated with descriptive terms comparable to the learned content preferences having relatively higher weights are ranked relatively more highly. | 2. The method of claim 1 , further comprising weighting the learned content preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed descriptive terms, number of selections of the content item having the analyzed descriptive terms, and time of use of the content item having the analyzed descriptive terms, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned content preferences so that content items associated with descriptive terms comparable to the learned content preferences having relatively higher weights are ranked relatively more highly. 4. The method of claim 2 , wherein the weights of the learned content preferences are decayed according to a specified reoccurring interval of time. | 0.977798 |
9,971,774 | 25 | 28 | 25. The method of claim 22 , further comprising: accessing the user-generated information from an information source. | 25. The method of claim 22 , further comprising: accessing the user-generated information from an information source. 28. The method of claim 25 , wherein the one or more query terms include an event name, and wherein the information source associates event names with dates. | 0.943647 |
9,785,312 | 11 | 12 | 11. A system in accordance with claim 7 wherein an administrator can use the interface to create a question for the list of questions by specifying a question name and by choosing a question type from a plurality of predetermined possible types. | 11. A system in accordance with claim 7 wherein an administrator can use the interface to create a question for the list of questions by specifying a question name and by choosing a question type from a plurality of predetermined possible types. 12. A system in accordance with claim 11 wherein the question types comprise at least three of the following: yes-no, text, number, date, and select one. | 0.964185 |
10,013,721 | 1 | 4 | 1. A computer-implemented method comprising: a computing device, by executing computer executable instructions of a computerized tax return preparation system stored in a memory and executed by a processor of the computing device, receiving, by a user interface controller of the computerized tax return preparation system, first electronic data and storing, by the user interface controller, the first electronic data to a shared data store, wherein field of an electronic tax return is populated with the first electronic data in the shared data store by the computerized tax return preparation system; the computing device, by executing a rule-based logic agent of the computerized tax return preparation system in communication with the shared data store, reading the first electronic data from the shared data store; the computing device, by executing a constraint engine associated with the rule-based logic agent, identifying a constraint of a tax authority requirement associated with the first electronic data read by the rule-based logic agent, the tax authority requirement and the constraint being expressed in a declarative programming format, generating an output indicating an electronic tax return error based at least in part upon the first electronic data failing to satisfy the constraint, and the computing device, by the rule-based logic agent, generating a non-binding suggestion based at least in part upon the output generated by the constraint engine, wherein rules utilized by the rule-based logic agent concerning the electronic tax return error are separate from interview screens of the interface controller, and transmitting the non-binding suggestion to the user interface controller; and the computing device, by executing the user interface controller, receiving the non-binding suggestion from the rule-based logic agent, generating or selecting an interactive interview screen comprising an alert concerning the electronic tax return error, presenting the interactive interview screen to a user through a display of the computing device, receiving user input through the interactive interview screen in response to the alert, and updating the first electronic data stored in the shared data store resulting in second electronic data based at least in part upon the user input concerning the alert. | 1. A computer-implemented method comprising: a computing device, by executing computer executable instructions of a computerized tax return preparation system stored in a memory and executed by a processor of the computing device, receiving, by a user interface controller of the computerized tax return preparation system, first electronic data and storing, by the user interface controller, the first electronic data to a shared data store, wherein field of an electronic tax return is populated with the first electronic data in the shared data store by the computerized tax return preparation system; the computing device, by executing a rule-based logic agent of the computerized tax return preparation system in communication with the shared data store, reading the first electronic data from the shared data store; the computing device, by executing a constraint engine associated with the rule-based logic agent, identifying a constraint of a tax authority requirement associated with the first electronic data read by the rule-based logic agent, the tax authority requirement and the constraint being expressed in a declarative programming format, generating an output indicating an electronic tax return error based at least in part upon the first electronic data failing to satisfy the constraint, and the computing device, by the rule-based logic agent, generating a non-binding suggestion based at least in part upon the output generated by the constraint engine, wherein rules utilized by the rule-based logic agent concerning the electronic tax return error are separate from interview screens of the interface controller, and transmitting the non-binding suggestion to the user interface controller; and the computing device, by executing the user interface controller, receiving the non-binding suggestion from the rule-based logic agent, generating or selecting an interactive interview screen comprising an alert concerning the electronic tax return error, presenting the interactive interview screen to a user through a display of the computing device, receiving user input through the interactive interview screen in response to the alert, and updating the first electronic data stored in the shared data store resulting in second electronic data based at least in part upon the user input concerning the alert. 4. The method of claim 1 , the constraint comprising a numerical condition specifying a range of numerical values of the tax authority requirement, wherein the output is generated in response to the constraint engine determining that the first electronic data is outside of the range. | 0.920493 |
9,355,093 | 12 | 13 | 12. A method according to claim 1 , wherein generating the referring noun phrase further comprises: removing a first element in the queue, wherein the first element is designated as a head noun in the referring noun phase. | 12. A method according to claim 1 , wherein generating the referring noun phrase further comprises: removing a first element in the queue, wherein the first element is designated as a head noun in the referring noun phase. 13. A method according to claim 12 , wherein generating the referring noun phrase further comprises: removing a next element in the queue; and setting the next element as a premodifier to the head noun; and in instance in which a predetermined premodifier count threshold is satisfied, removing an element from the queue and setting it as a post modifier to the head noun. | 0.89574 |
7,788,247 | 1 | 2 | 1. A computer-readable medium including executable instructions which, when executed, enable tagging by: identifying a contact as a person of interest to associate with a tag; presenting a number of recommended tags including presenting the number of recommended tags based in part on information collected from electronic communications with the contact; tagging the contact with a characterizing tag, wherein the characterizing tag identifies information associated with the contact and defines an association with the contact based in part on prior electronic communications with the contact, wherein a tagging user can add characterizing tags for other persons of interest by selecting another contact to tag with a same or different characterizing tag, including presenting one or more recommended tags for each person of interest; identifying other users that share a common characterizing tag; and, storing the characterizing tag in a tag store, including storing identification information associated with a tagging user that tagged the contact as the person of interest with the characterization tag. | 1. A computer-readable medium including executable instructions which, when executed, enable tagging by: identifying a contact as a person of interest to associate with a tag; presenting a number of recommended tags including presenting the number of recommended tags based in part on information collected from electronic communications with the contact; tagging the contact with a characterizing tag, wherein the characterizing tag identifies information associated with the contact and defines an association with the contact based in part on prior electronic communications with the contact, wherein a tagging user can add characterizing tags for other persons of interest by selecting another contact to tag with a same or different characterizing tag, including presenting one or more recommended tags for each person of interest; identifying other users that share a common characterizing tag; and, storing the characterizing tag in a tag store, including storing identification information associated with a tagging user that tagged the contact as the person of interest with the characterization tag. 2. The computer-readable medium of claim 1 , wherein the instructions, when executed, enable tagging by recommending the recommended tags based in part on a prior communication with the contact. | 0.734973 |
10,147,427 | 10 | 12 | 10. The computer program product of claim 9 , wherein the program instructions to store one or more meta tags in a data repository comprise: program instructions to analyze the computer searchable data representing previous conversations between the customer and a service representative in order to generate one or more meta tags, wherein each meta tag relates to at least a portion of the searchable data and wherein each meta tag is associated with a contextual item; and program instructions to store the computer searchable data and each said meta tag in the data repository in association with said customer. | 10. The computer program product of claim 9 , wherein the program instructions to store one or more meta tags in a data repository comprise: program instructions to analyze the computer searchable data representing previous conversations between the customer and a service representative in order to generate one or more meta tags, wherein each meta tag relates to at least a portion of the searchable data and wherein each meta tag is associated with a contextual item; and program instructions to store the computer searchable data and each said meta tag in the data repository in association with said customer. 12. The computer program product of claim 10 , wherein program instructions to store one or more meta tags further comprise program instructions to store at least a portion of an audible conversation as a voice data with each said meta tag in the data repository in association with said customer. | 0.93713 |
9,185,125 | 6 | 7 | 6. The method of claim 1 , further comprising: receiving one or more representations of acceptable network traffic; and training each of one or more of the plurality of scoring algorithms to score target operations or events using the one or more representations of acceptable network traffic. | 6. The method of claim 1 , further comprising: receiving one or more representations of acceptable network traffic; and training each of one or more of the plurality of scoring algorithms to score target operations or events using the one or more representations of acceptable network traffic. 7. The method of claim 6 , wherein the one or more representations of acceptable network traffic comprise a plurality of representations of acceptable operations or events, and wherein training at least one of the one or more scoring algorithms to score target operations or events using the one or more representations of acceptable network traffic comprises: parsing the plurality of representations of acceptable operations or events into a plurality of parse trees; and generating a pattern-matching tree that is an isomorphism between two or more of the plurality of parse trees and represents a unification of the two or more parse trees. | 0.79199 |
8,099,283 | 2 | 3 | 2. The method of claim 1 , further comprising determining the presence of the user-specific XML document based on a user identity for the user and the requested prescribed voice application operation. | 2. The method of claim 1 , further comprising determining the presence of the user-specific XML document based on a user identity for the user and the requested prescribed voice application operation. 3. The method of claim 2 , wherein the determining step includes accessing an external database, configured for storing data for respective users, for retrieval of the user-specific XML document. | 0.825269 |
8,200,654 | 1 | 2 | 1. A method of processing a database query, comprising: receiving a query generated using a query builder application; identifying at least a first query condition included in the query having an associated database extension; identifying at least a second query condition included in the query having an associated parallel application extension; submitting the first query condition for execution against a database to produce a first query result, wherein the first query condition is executed according to the database extension associated with the first query condition; receiving a second query result produced by invoking an analysis routine on a parallel computer system, based on the second query condition, wherein the analysis routine is identified by the parallel application extension associated with the second query condition, the invoking comprising: transmitting, over a connection to a compute node of the parallel computing system, the second query condition and the first query result, wherein the compute node is configured to translate the second condition into a format compatible with the analysis routine, and wherein the compute node is further configured to invoke, on the parallel computing system, an execution of the analysis routine using the translated second condition and the first query result to obtain the second query result; merging the first query result and the second query result to produce merged results; and returning, as a response to the received query, the merged results. | 1. A method of processing a database query, comprising: receiving a query generated using a query builder application; identifying at least a first query condition included in the query having an associated database extension; identifying at least a second query condition included in the query having an associated parallel application extension; submitting the first query condition for execution against a database to produce a first query result, wherein the first query condition is executed according to the database extension associated with the first query condition; receiving a second query result produced by invoking an analysis routine on a parallel computer system, based on the second query condition, wherein the analysis routine is identified by the parallel application extension associated with the second query condition, the invoking comprising: transmitting, over a connection to a compute node of the parallel computing system, the second query condition and the first query result, wherein the compute node is configured to translate the second condition into a format compatible with the analysis routine, and wherein the compute node is further configured to invoke, on the parallel computing system, an execution of the analysis routine using the translated second condition and the first query result to obtain the second query result; merging the first query result and the second query result to produce merged results; and returning, as a response to the received query, the merged results. 2. The method of claim 1 , further comprising, writing the translated second condition and the first query result to an input file, wherein the analysis routine parses the input file to obtain the translated second condition and the first query result. | 0.693431 |
8,620,909 | 12 | 16 | 12. A non-transitory computer-readable storage medium storing executable computer program instructions for contextual personalized search comprising instructions for performing the steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. | 12. A non-transitory computer-readable storage medium storing executable computer program instructions for contextual personalized search comprising instructions for performing the steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. 16. The non-transitory computer-readable storage medium of claim 12 , wherein matching further comprises: computing transitive closure for each node in a directed acyclic graph in a specified direction; and storing the computed transitive closure in one or more hierarchical indexes, the indexes dynamically updated when one or more values of the concepts change. | 0.763979 |
10,140,120 | 1 | 10 | 1. A method comprising: determining, from a hierarchical data structure, an internodal relationship between two contextual objects of a set of contextual objects, the hierarchical data structure representing a set of software configuration management (SCM) tools for a selected software program; displaying the set of contextual objects for user-selection of individual contextual objects within the set of contextual objects; receiving a user-context indicator responsive to a user selection of one contextual object of the two contextual objects from the displayed set of contextual objects, the user-context indicator corresponding to the one contextual object, the user-context indicator being creation of a new contextual object; determining a subset of the hierarchical data structure corresponding to the creation of the new contextual object according to the internodal relationship between the two contextual objects; and responsive to determining the subset of the hierarchical data structure, creating a working set including the subset of the hierarchical data structure in a tree view; wherein: at least the steps of receiving, determining, and generating are performed by computer software running on computer hardware. | 1. A method comprising: determining, from a hierarchical data structure, an internodal relationship between two contextual objects of a set of contextual objects, the hierarchical data structure representing a set of software configuration management (SCM) tools for a selected software program; displaying the set of contextual objects for user-selection of individual contextual objects within the set of contextual objects; receiving a user-context indicator responsive to a user selection of one contextual object of the two contextual objects from the displayed set of contextual objects, the user-context indicator corresponding to the one contextual object, the user-context indicator being creation of a new contextual object; determining a subset of the hierarchical data structure corresponding to the creation of the new contextual object according to the internodal relationship between the two contextual objects; and responsive to determining the subset of the hierarchical data structure, creating a working set including the subset of the hierarchical data structure in a tree view; wherein: at least the steps of receiving, determining, and generating are performed by computer software running on computer hardware. 10. The method of claim 1 , wherein the two objects of the set of contextual objects are a first programming view and a first patch stream, the first patch stream corresponds to the first programming view. | 0.882048 |
8,280,841 | 1 | 5 | 1. A stage determination apparatus including a storage and a processor and comprising: a bibliographic database configured to integrate heterogeneous resources; a feature set creation module configured to calculate feature values of predefined features by searching the bibliographic database, and to create a feature set of each technology using the calculated feature values, for technologies positioned on a technology lifecycle; an answer feature set creation module configured to calculate a common feature value of feature sets of technologies belonging to the same stage in the technology lifecycle and to create an answer feature set of each stage; a stage determination module configured to, if a specific technology is inputted, acquire feature values and create a feature set for predefined features by searching the bibliographic database for the specific technology, to compare a corresponding feature value contained in the feature set of the specific technology with a feature value according to a feature selection flow set in a previously constructed decision tree according to the feature selection flow set in the decision tree, and to determine a stage having a feature value finally selected according to the feature selection flow of the decision tree as a stage where the specific technology belongs to in the technology lifecycle. | 1. A stage determination apparatus including a storage and a processor and comprising: a bibliographic database configured to integrate heterogeneous resources; a feature set creation module configured to calculate feature values of predefined features by searching the bibliographic database, and to create a feature set of each technology using the calculated feature values, for technologies positioned on a technology lifecycle; an answer feature set creation module configured to calculate a common feature value of feature sets of technologies belonging to the same stage in the technology lifecycle and to create an answer feature set of each stage; a stage determination module configured to, if a specific technology is inputted, acquire feature values and create a feature set for predefined features by searching the bibliographic database for the specific technology, to compare a corresponding feature value contained in the feature set of the specific technology with a feature value according to a feature selection flow set in a previously constructed decision tree according to the feature selection flow set in the decision tree, and to determine a stage having a feature value finally selected according to the feature selection flow of the decision tree as a stage where the specific technology belongs to in the technology lifecycle. 5. The apparatus according to claim 1 , wherein the feature set creation module includes: a feature-related information acquisition unit configured to acquire feature-related information for calculating feature values of features contained in a predefined feature set by searching the bibliographic database for the technologies; a feature value calculation unit configured to calculate a feature value of each feature by technology using the acquired feature-related information; and a feature set creation unit configured to create a feature set containing the calculated feature values for each technology. | 0.743471 |
8,041,113 | 4 | 6 | 4. The image processing device according to claim 1 , further comprising: an attribute determining computer processor unit configured to determine an attribute of the first document area, wherein the second area extracting computer processor unit is configured to extract a second document area by dividing the first document area or combining the first document area with at least another different unit of a document area based on a rule corresponding to the type of the language determined by the language determining computer processor unit and the attribute determined by the attribute determining unit. | 4. The image processing device according to claim 1 , further comprising: an attribute determining computer processor unit configured to determine an attribute of the first document area, wherein the second area extracting computer processor unit is configured to extract a second document area by dividing the first document area or combining the first document area with at least another different unit of a document area based on a rule corresponding to the type of the language determined by the language determining computer processor unit and the attribute determined by the attribute determining unit. 6. The image processing device according to claim 4 , wherein the attribute determining computer processor unit determines at least one of a writing orientation and a font size of characters included in the first document area, as the attribute. | 0.942917 |
9,177,057 | 12 | 13 | 12. The one or more computer-readable media of claim 11 , wherein the search query includes one or more search terms and the query context includes the one or more search terms. | 12. The one or more computer-readable media of claim 11 , wherein the search query includes one or more search terms and the query context includes the one or more search terms. 13. The one or more computer-readable media of claim 12 , wherein the query context includes information in addition to the one or more search terms. | 0.959312 |
8,768,731 | 1 | 17 | 1. A computer implemented method comprising: generating a data pool to receive and publish data that includes ultrasound echo data, wherein generating the data pool is performed by a microprocessor of the computer executing instructions stored in a non-transitory computer memory and comprises: receiving ultrasound echo data from one or more medical devices; securing the ultrasound echo data with a conditional access mechanism to provide a secure item; adding metadata to the secure item that includes metadata identifying characteristics of a patient; publishing the secure item and the metadata in a syndicated data feed using the microprocessor of a computer executing instructions stored in a non-transitory computer memory; subscribing to the syndicated data feed; storing the syndicated data feed in the data pool, wherein the format of the syndicated data feed is selected from the group consisting of: Really Simple Syndication, Resource Description Framework Site Summary, Rich Site Summary and Outline Processor Markup Language; extracting data related to an abnormality of the ultrasound echo data from the syndicated data feed; comparing the extracted data related to the abnormality with comparable ultrasound echo data from a normal specimen; extracting data related to adverse patient outcomes from the syndicated data feed; and correlating adverse patient outcomes with the abnormality of the ultrasound echo data. | 1. A computer implemented method comprising: generating a data pool to receive and publish data that includes ultrasound echo data, wherein generating the data pool is performed by a microprocessor of the computer executing instructions stored in a non-transitory computer memory and comprises: receiving ultrasound echo data from one or more medical devices; securing the ultrasound echo data with a conditional access mechanism to provide a secure item; adding metadata to the secure item that includes metadata identifying characteristics of a patient; publishing the secure item and the metadata in a syndicated data feed using the microprocessor of a computer executing instructions stored in a non-transitory computer memory; subscribing to the syndicated data feed; storing the syndicated data feed in the data pool, wherein the format of the syndicated data feed is selected from the group consisting of: Really Simple Syndication, Resource Description Framework Site Summary, Rich Site Summary and Outline Processor Markup Language; extracting data related to an abnormality of the ultrasound echo data from the syndicated data feed; comparing the extracted data related to the abnormality with comparable ultrasound echo data from a normal specimen; extracting data related to adverse patient outcomes from the syndicated data feed; and correlating adverse patient outcomes with the abnormality of the ultrasound echo data. 17. The computer implemented method of claim 1 wherein publishing the syndicated data feed includes publishing the syndicated data feed to a publicly-accessible network. | 0.87718 |
7,860,819 | 13 | 17 | 13. An apparatus, comprising: a processor; and a memory coupled to the processor and storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant, wherein the processor is configured to, in response to receiving second data representing one or more variants: determine a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links, and generate third data based on the determined portion of the semantic network. | 13. An apparatus, comprising: a processor; and a memory coupled to the processor and storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant, wherein the processor is configured to, in response to receiving second data representing one or more variants: determine a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links, and generate third data based on the determined portion of the semantic network. 17. The apparatus of claim 13 , wherein the semantic network further comprises a further link having one of the plurality of links as a subject or target of the further link. | 0.70903 |
8,572,093 | 16 | 17 | 16. The system of claim 15 , further comprising a compiler coupled to the software due diligence system, wherein the compiler is configured to perform one or more operations using said complex operators on the attributes of the license description syntax associated with said identified applicable licenses to identify other entries describing software licenses with which the software must comply. | 16. The system of claim 15 , further comprising a compiler coupled to the software due diligence system, wherein the compiler is configured to perform one or more operations using said complex operators on the attributes of the license description syntax associated with said identified applicable licenses to identify other entries describing software licenses with which the software must comply. 17. The system of claim 16 , wherein the one or more operations performed by the compiler include evaluating one or more logical expressions to said determine the permissions and obligations associated with the applicable licenses. | 0.946651 |
8,285,859 | 3 | 7 | 3. A method of claim 2 , wherein the one or more semantic information brokers comprise one or more information spaces, the method further comprising: computing a stability factor corresponding to each of the one or more semantic information brokers; and selecting one or more of the semantic information brokers as master semantic information brokers for a respective one of the information spaces based on the computed stability factors, wherein the one or more master semantic information brokers manage communication among the semantic information brokers within the respective information space. | 3. A method of claim 2 , wherein the one or more semantic information brokers comprise one or more information spaces, the method further comprising: computing a stability factor corresponding to each of the one or more semantic information brokers; and selecting one or more of the semantic information brokers as master semantic information brokers for a respective one of the information spaces based on the computed stability factors, wherein the one or more master semantic information brokers manage communication among the semantic information brokers within the respective information space. 7. A method of claim 3 , further comprising: monitoring a heartbeat signal from each of the plurality of semantic information brokers in the respective information space; detecting whether a connection to one or more of the plurality of semantic information brokers is lost based on the monitored heartbeat signals; computing a new stability factor for each of the semantic information brokers for which a connection is detected; and selecting one or more new master semantic information brokers based on the new stability factors. | 0.7092 |
10,147,428 | 10 | 11 | 10. A system configured for improving computer speed and accuracy of automatic speech transcription, comprising: at least one specialized computer, comprising: a non-transient computer memory, storing particular computer executable program code; and at least one computer processor which, when executing the particular program code, is configured to perform at least the following operations: generating at least one speech recognition model specification for a plurality of distinct speech-to-text transcription engines; wherein each distinct speech-to-text transcription engine corresponds to a respective distinct speech recognition model; wherein, for each distinct speech-to-text transcription engine, the at least one speech recognition model specification at least identifies: i) a respective value for at least one pre-transcription evaluation parameter, and ii) a respective value for at least one post-transcription evaluation parameter; wherein the generating at least one speech recognition model specification comprises: receiving at least one training audio recording and at least one truth transcript of the at least one training audio recording; segmenting the at least one training audio recording into a plurality of training audio segments and the at least one truth transcript into a plurality of corresponding truth training segment transcripts; applying at least one pre-transcription audio classifier to each training audio segment of the plurality of training audio segments to generate first metadata classifying each training audio segment based at least on: i) language, ii) audio quality, and iii) accent; applying at least one text classifier to each corresponding truth training segment transcript of the plurality of corresponding truth training segment transcripts to generate second metadata classifying each corresponding truth training segment transcript based at least on at least one content category; combining the plurality of training audio segments, the plurality of corresponding truth training segment transcripts, the first metadata, and the second metadata to form at least one benchmark set; testing each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines based on the at least one benchmark set to form a plurality of model result sets; wherein each model result set corresponds to a respective distinct speech-to-text transcription engine; wherein each model result set comprises: i) the at least one benchmark set, ii) at least one model-specific training hypothesis for each training audio segment, iii) at least one confidence value associated with the at least one model-specific training hypothesis, and iv) at least one word error rate (WER) associated with the at least one model-specific training hypothesis; determining a respective set of transcription decisions for each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines, wherein the respective set of transcription decisions defines, for each distinct speech-to-text transcription engine, the value of the at least one pre-transcription evaluation parameter and the value of the at least one post-transcription evaluation parameter; combining each respective set of transcription decisions for each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines into the at least one speech recognition model specification for the plurality of distinct speech-to-text transcription engines; receiving at least one audio recording representing at least one speech of at least one person; segmenting the at least one audio recording into a plurality of audio segments; wherein in each audio segment corresponds to a respective single phrase of a respective single person that has been bounded by points of silence in the at least one audio recording; determining, based on the respective value of the at least one pre-transcription evaluation parameter of the respective distinct speech recognition model in the at least one speech recognition model specification, a respective distinct speech-to-text transcription engine from the plurality of distinct speech-to-text transcription engines to be utilized to transcribe a respective audio segment of the plurality of audio segments; submitting the respective audio segment to the respective distinct speech-to-text transcription engine; receiving, from the respective distinct speech-to-text transcription engine, at least one hypothesis for the respective audio segment; accepting the at least one hypothesis for the respective audio segment based on the respective value of the at least one post-transcription evaluation parameter of the respective distinct speech recognition model in the at least one speech recognition model specification to obtain a respective accepted hypothesis for the respective audio segment of the plurality of audio segments of the at least one audio recording; wherein the accepting of the at least one hypothesis for each respective audio segment as the respective accepted hypothesis for the respective audio segment removes a need to submit the respective audio segment to another distinct speech-to-text transcription engine from the plurality of distinct speech-to-text transcription engines resulting in the improved computer speed and the accuracy of automatic speech transcription; generating at least one transcript of the at least one audio recording from respective accepted hypotheses for the plurality of audio segments; and outputting the at least one transcript of the at least one audio recording. | 10. A system configured for improving computer speed and accuracy of automatic speech transcription, comprising: at least one specialized computer, comprising: a non-transient computer memory, storing particular computer executable program code; and at least one computer processor which, when executing the particular program code, is configured to perform at least the following operations: generating at least one speech recognition model specification for a plurality of distinct speech-to-text transcription engines; wherein each distinct speech-to-text transcription engine corresponds to a respective distinct speech recognition model; wherein, for each distinct speech-to-text transcription engine, the at least one speech recognition model specification at least identifies: i) a respective value for at least one pre-transcription evaluation parameter, and ii) a respective value for at least one post-transcription evaluation parameter; wherein the generating at least one speech recognition model specification comprises: receiving at least one training audio recording and at least one truth transcript of the at least one training audio recording; segmenting the at least one training audio recording into a plurality of training audio segments and the at least one truth transcript into a plurality of corresponding truth training segment transcripts; applying at least one pre-transcription audio classifier to each training audio segment of the plurality of training audio segments to generate first metadata classifying each training audio segment based at least on: i) language, ii) audio quality, and iii) accent; applying at least one text classifier to each corresponding truth training segment transcript of the plurality of corresponding truth training segment transcripts to generate second metadata classifying each corresponding truth training segment transcript based at least on at least one content category; combining the plurality of training audio segments, the plurality of corresponding truth training segment transcripts, the first metadata, and the second metadata to form at least one benchmark set; testing each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines based on the at least one benchmark set to form a plurality of model result sets; wherein each model result set corresponds to a respective distinct speech-to-text transcription engine; wherein each model result set comprises: i) the at least one benchmark set, ii) at least one model-specific training hypothesis for each training audio segment, iii) at least one confidence value associated with the at least one model-specific training hypothesis, and iv) at least one word error rate (WER) associated with the at least one model-specific training hypothesis; determining a respective set of transcription decisions for each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines, wherein the respective set of transcription decisions defines, for each distinct speech-to-text transcription engine, the value of the at least one pre-transcription evaluation parameter and the value of the at least one post-transcription evaluation parameter; combining each respective set of transcription decisions for each distinct speech-to-text transcription engine of the plurality of distinct speech-to-text transcription engines into the at least one speech recognition model specification for the plurality of distinct speech-to-text transcription engines; receiving at least one audio recording representing at least one speech of at least one person; segmenting the at least one audio recording into a plurality of audio segments; wherein in each audio segment corresponds to a respective single phrase of a respective single person that has been bounded by points of silence in the at least one audio recording; determining, based on the respective value of the at least one pre-transcription evaluation parameter of the respective distinct speech recognition model in the at least one speech recognition model specification, a respective distinct speech-to-text transcription engine from the plurality of distinct speech-to-text transcription engines to be utilized to transcribe a respective audio segment of the plurality of audio segments; submitting the respective audio segment to the respective distinct speech-to-text transcription engine; receiving, from the respective distinct speech-to-text transcription engine, at least one hypothesis for the respective audio segment; accepting the at least one hypothesis for the respective audio segment based on the respective value of the at least one post-transcription evaluation parameter of the respective distinct speech recognition model in the at least one speech recognition model specification to obtain a respective accepted hypothesis for the respective audio segment of the plurality of audio segments of the at least one audio recording; wherein the accepting of the at least one hypothesis for each respective audio segment as the respective accepted hypothesis for the respective audio segment removes a need to submit the respective audio segment to another distinct speech-to-text transcription engine from the plurality of distinct speech-to-text transcription engines resulting in the improved computer speed and the accuracy of automatic speech transcription; generating at least one transcript of the at least one audio recording from respective accepted hypotheses for the plurality of audio segments; and outputting the at least one transcript of the at least one audio recording. 11. The system of claim 10 , wherein the at least one pre-transcription evaluation parameter is at least one of: i) the language, ii) the audio quality, or iii) the accent. | 0.907527 |
8,738,967 | 6 | 7 | 6. A system for testing computing devices, comprising: one or more computer processors; at least one computer memory accessible by at least one of the one or more computer processors; a client application component executed by at least one of the one or more computer processors for generating control instructions for a device under test, wherein the control instructions describe an initial set of test cases for the device under test; and a test case generation component executed by at least one of the one or more computer processors for: obtaining the generated control instructions from the client application component, analyzing the control instructions to determine at least one attribute of the initial set of test cases described by the control instructions for the device under test, generating modified control instructions using the determined attribute of the initial set of control instruction, transmitting the second set of test cases to the device under test, and obtaining at least one output generated by the device under test, wherein the at least one output generated by the device under test is responsive to the second set of test cases described by the modified control instructions; wherein control instructions are analyzed without generation of the initial set of test cases. | 6. A system for testing computing devices, comprising: one or more computer processors; at least one computer memory accessible by at least one of the one or more computer processors; a client application component executed by at least one of the one or more computer processors for generating control instructions for a device under test, wherein the control instructions describe an initial set of test cases for the device under test; and a test case generation component executed by at least one of the one or more computer processors for: obtaining the generated control instructions from the client application component, analyzing the control instructions to determine at least one attribute of the initial set of test cases described by the control instructions for the device under test, generating modified control instructions using the determined attribute of the initial set of control instruction, transmitting the second set of test cases to the device under test, and obtaining at least one output generated by the device under test, wherein the at least one output generated by the device under test is responsive to the second set of test cases described by the modified control instructions; wherein control instructions are analyzed without generation of the initial set of test cases. 7. The system as recited in claim 6 , wherein the control instructions correspond to a test grammar. | 0.801587 |
9,646,634 | 13 | 17 | 13. A non-transitory computer-readable medium for training a deep neural network that comprises a low rank hidden input layer with m nodes and an adjoining hidden layer with o nodes, the low rank hidden input layer comprising a first matrix A and a second matrix B with dimensions i×m and m×o, respectively, to identify a key phrase, the computer-readable medium storing software comprising instructions executable by a speech recognition system that includes one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by the speech recognition system that includes the deep neural network trained to identify the key phrase, a feature vector comprising i values that represent features of an audio signal encoding an utterance; determining an output vector comprising o values using the m nodes in the low rank hidden input layer by combining the feature vector, the first matrix A in the low rank hidden input layer, and the second matrix B included in the low rank hidden input layer using a linear function, wherein m is a smaller number than o; determining, using a non-linear function for the adjoining hidden layer that has the o nodes, another vector using the output vector that comprises the o values; determining a confidence score that indicates whether the utterance includes the key phrase using the other vector; adjusting one or more weights for the low rank hidden input layer based on an accuracy of the confidence score; and providing, by the speech recognition system, the deep neural network with the adjusted one or more weights for use in processing audio. | 13. A non-transitory computer-readable medium for training a deep neural network that comprises a low rank hidden input layer with m nodes and an adjoining hidden layer with o nodes, the low rank hidden input layer comprising a first matrix A and a second matrix B with dimensions i×m and m×o, respectively, to identify a key phrase, the computer-readable medium storing software comprising instructions executable by a speech recognition system that includes one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by the speech recognition system that includes the deep neural network trained to identify the key phrase, a feature vector comprising i values that represent features of an audio signal encoding an utterance; determining an output vector comprising o values using the m nodes in the low rank hidden input layer by combining the feature vector, the first matrix A in the low rank hidden input layer, and the second matrix B included in the low rank hidden input layer using a linear function, wherein m is a smaller number than o; determining, using a non-linear function for the adjoining hidden layer that has the o nodes, another vector using the output vector that comprises the o values; determining a confidence score that indicates whether the utterance includes the key phrase using the other vector; adjusting one or more weights for the low rank hidden input layer based on an accuracy of the confidence score; and providing, by the speech recognition system, the deep neural network with the adjusted one or more weights for use in processing audio. 17. The computer-readable medium of claim 13 wherein combining the feature vector, the first matrix A in the low rank hidden input layer, and the second matrix B included in the low rank hidden input layer using the linear function comprises combining, by the low rank hidden input layer using the m nodes in the low rank hidden input layer, the values of the first matrix A with the second matrix B using a weighted sum. | 0.508178 |
9,323,720 | 1 | 13 | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. 13. The method of claim 1 , further comprising: executing a Web service, that receives the unification command, acquires the content, and adds the acquired content to the root document. | 0.910019 |
10,120,858 | 12 | 15 | 12. A method for analyzing queries, the method comprising: receiving a query from a user; determining, based on the user's natural language, a correct grammatical structure for the query; dissecting the query into a plurality of words; assigning, based on a predetermined ontology and the determined correct grammatical structure, an ontological threshold score to each of the words; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query and the correct grammatical structure; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query and the correct grammatical structure; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis defined by the word, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. | 12. A method for analyzing queries, the method comprising: receiving a query from a user; determining, based on the user's natural language, a correct grammatical structure for the query; dissecting the query into a plurality of words; assigning, based on a predetermined ontology and the determined correct grammatical structure, an ontological threshold score to each of the words; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query and the correct grammatical structure; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query and the correct grammatical structure; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis defined by the word, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. 15. The method of claim 12 , wherein the enabling further comprises displaying, in a vertical drop-down menu orthogonal to the horizontal axis, and directly vertically under the concepts associated with each word, a predetermined list of concepts relating to each word having an assigned ontological threshold score that is at or above the predetermined threshold. | 0.518519 |
8,619,316 | 1 | 2 | 1. A method for processing a document, the method comprising: identifying a text area from a scanned document; extracting symbols from the identified text area; acquiring symbol-related information regarding each extracted symbol by a symbol-related information acquirement unit; dividing the extracted symbols, by a symbol division unit, into a plurality of groups based on a preset reference value regarding the symbol-related information; and generating a key index by a key index generation unit by arranging one group of symbols from among the divided groups, wherein the symbol-related information is information regarding at least one of height, width, and stroke width of the corresponding extracted symbol. | 1. A method for processing a document, the method comprising: identifying a text area from a scanned document; extracting symbols from the identified text area; acquiring symbol-related information regarding each extracted symbol by a symbol-related information acquirement unit; dividing the extracted symbols, by a symbol division unit, into a plurality of groups based on a preset reference value regarding the symbol-related information; and generating a key index by a key index generation unit by arranging one group of symbols from among the divided groups, wherein the symbol-related information is information regarding at least one of height, width, and stroke width of the corresponding extracted symbol. 2. The method according to claim 1 , wherein the dividing of the extracted symbols into several groups comprises dividing the extracted symbols into several groups based on a first reference value indicating a sum of the height and width of the corresponding extracted symbol, and a second reference value indicating the stroke width of the corresponding extracted symbol. | 0.509235 |
10,008,203 | 1 | 4 | 1. A computer-implemented method comprising: receiving data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determining that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, selecting the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, causing an activity associated with the application specified by the generated data structure to be performed on or by the application. | 1. A computer-implemented method comprising: receiving data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determining that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, selecting the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, causing an activity associated with the application specified by the generated data structure to be performed on or by the application. 4. The computer implemented method of claim 1 , wherein the context defines particular software that must be absent from a computing device that provides the spoken utterance that is transcribed. | 0.892265 |
8,049,093 | 9 | 11 | 9. The method of claim 8 further comprising the steps of: determining a distance between the pitch contour from the portion of the song and a pitch contour of a target song starting at a location taken from the plurality of locations; and repeating the step of determining the distance for the plurality of locations of best matched portions, resulting in a plurality of distances. | 9. The method of claim 8 further comprising the steps of: determining a distance between the pitch contour from the portion of the song and a pitch contour of a target song starting at a location taken from the plurality of locations; and repeating the step of determining the distance for the plurality of locations of best matched portions, resulting in a plurality of distances. 11. The method of claim 9 further comprising the step of rank ordering the distances, designating the candidate target song with the least distance as the best candidate target song. | 0.888344 |
9,646,057 | 9 | 10 | 9. The method as set forth in claim 8 , wherein the information related to the message is selected from a group consisting of user information, location information, hyperlink information, and annotation information. | 9. The method as set forth in claim 8 , wherein the information related to the message is selected from a group consisting of user information, location information, hyperlink information, and annotation information. 10. The method as set forth in claim 9 , wherein the location information is obtained from at least one of geo-coordinate information related to the message or location information in a user profile from the online discussion. | 0.922015 |
5,392,419 | 15 | 17 | 15. The system as recited in claim 14 further comprising: means for classifying identified For and Against keys by key type; and weight means for incrementing or decrementing a language vote count by a weight value assigned to each key type, the increment or decrement amount being a signed key type weight value preassigned to the key type each time a said key is determined, said vote value being incremented for For key types and decremented for Against key types. | 15. The system as recited in claim 14 further comprising: means for classifying identified For and Against keys by key type; and weight means for incrementing or decrementing a language vote count by a weight value assigned to each key type, the increment or decrement amount being a signed key type weight value preassigned to the key type each time a said key is determined, said vote value being incremented for For key types and decremented for Against key types. 17. The system as recited in claim 15 wherein said skew for each key type is an initial skew value for a key type modified by a skew modifier, said skew modifier causing said initial skew value to differ for second and subsequent appearances of a key type in a data block. | 0.915998 |
8,473,555 | 1 | 15 | 1. A method of managing a session of electronic communications, the method comprising: determining, using a processor, a language for an incoming electronic communication received from a sender computer in a first session, wherein the language for the incoming electronic communication is determined using a language modeling algorithm, wherein the first session comprises a chat in a messaging system; determining, by the processor, whether the language differs from a desired first display language; responsive to a determination that the language differs from the desired first display language, transmitting, by the processor, the incoming electronic communication to a translation service computer for translation of the incoming electronic communication into the desired first display language using a translation service to form a translated incoming electronic communication; receiving, by the processor, the translated incoming electronic communication from the translation service computer; displaying, by the processor, the translated incoming electronic communication in the first session on a display device in the first display language; wherein the first session and a second session occur simultaneously in the first display language and a second display language respectively on the display device for a multilingual user. | 1. A method of managing a session of electronic communications, the method comprising: determining, using a processor, a language for an incoming electronic communication received from a sender computer in a first session, wherein the language for the incoming electronic communication is determined using a language modeling algorithm, wherein the first session comprises a chat in a messaging system; determining, by the processor, whether the language differs from a desired first display language; responsive to a determination that the language differs from the desired first display language, transmitting, by the processor, the incoming electronic communication to a translation service computer for translation of the incoming electronic communication into the desired first display language using a translation service to form a translated incoming electronic communication; receiving, by the processor, the translated incoming electronic communication from the translation service computer; displaying, by the processor, the translated incoming electronic communication in the first session on a display device in the first display language; wherein the first session and a second session occur simultaneously in the first display language and a second display language respectively on the display device for a multilingual user. 15. The method of claim 1 , wherein the step of determining, using the processor, the language for the incoming electronic communication received from the sender computer in the session comprises: processing a content of the incoming electronic communication using trigram language modeling. | 0.884707 |
8,645,421 | 29 | 42 | 29. A computer program product for providing data records, tangibly embodied in a machine-readable non-transitory storage medium, including instructions configured to cause a data processing system to: access a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identify one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generate an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generate a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receive a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; provide the one or more records from the particular new level to the predictive model; and process the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results. | 29. A computer program product for providing data records, tangibly embodied in a machine-readable non-transitory storage medium, including instructions configured to cause a data processing system to: access a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identify one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generate an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generate a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receive a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; provide the one or more records from the particular new level to the predictive model; and process the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results. 42. The computer program product of claim 29 , wherein the particular new level corresponds to an identified attribute hierarchy field, and wherein the identified hierarchy field corresponds to an input field of the predictive model. | 0.651198 |
7,770,136 | 1 | 13 | 1. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface, a method of suggesting recognized application gesture commands based on the user interaction with the surface in order to give the user various options and/or instructions on how to appropriately use the application for the motion-sensitive display surface, the method comprising: receiving at a motion-sensitive display surface a user-performed gesture, which includes user movement of an object over the surface that recognizes such user interaction therewith; determining that the received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; based on the determination, identifying one or more gesture commands that are similar to the received user-performed gesture that are recognizable by the one or more programs of the motion-sensitive display surface, wherein the one or more gesture commands recognized by the program represent actual commands of the program; and displaying one or more exemplary gesture commands recognized by the one or more programs in order to aid the user in understanding appropriate various defined gestures representing actual program commands, the exemplary gesture commands comprising one or more graphical, non-textual images that depict a series of one or more object motions or movements performable by the user that form a recognized command, recognizable by the motion-sensitive display surface. | 1. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface, a method of suggesting recognized application gesture commands based on the user interaction with the surface in order to give the user various options and/or instructions on how to appropriately use the application for the motion-sensitive display surface, the method comprising: receiving at a motion-sensitive display surface a user-performed gesture, which includes user movement of an object over the surface that recognizes such user interaction therewith; determining that the received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; based on the determination, identifying one or more gesture commands that are similar to the received user-performed gesture that are recognizable by the one or more programs of the motion-sensitive display surface, wherein the one or more gesture commands recognized by the program represent actual commands of the program; and displaying one or more exemplary gesture commands recognized by the one or more programs in order to aid the user in understanding appropriate various defined gestures representing actual program commands, the exemplary gesture commands comprising one or more graphical, non-textual images that depict a series of one or more object motions or movements performable by the user that form a recognized command, recognizable by the motion-sensitive display surface. 13. The method of claim 1 , wherein the gesture recognition tutorial system processes all possible inputs within the context of the detected movement inputs while the gesture is being performed. | 0.572687 |
8,185,519 | 10 | 11 | 10. The method of claim 1 , further comprising: obtaining previously executed queries; and mapping a new query to an existing group. | 10. The method of claim 1 , further comprising: obtaining previously executed queries; and mapping a new query to an existing group. 11. The method of claim 10 , further comprising: defining essential sets for the existing group; and ordering of the expressions in the unordered subset of the set of relevant expressions to give priority to those expressions contained in the essential sets. | 0.923578 |
8,781,837 | 13 | 19 | 13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications. | 13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications. 19. The method according to claim 13 , wherein speech recognition data on processing of a speech recognition process common to the applications and data on processing of the speech recognition process that is different according to each application are stored and held in a storage device; and wherein the step of generating recognition result hypotheses includes: extracting a feature of the speech supplied from the one speech input unit; and generating the recognition result hypotheses for the extracted feature, using the speech recognition data on the common processing stored in the storage device; and the step of receiving the recognition result hypotheses and generating and outputting recognition results includes: obtaining the speech recognition data from the storage device, obtaining data on adaptation processing for the each application from the storage device, and generating data corresponding to the application of an adaptation destination and the adaptation processing for the application of the adaptation destination; and receiving the recognition result hypotheses, executing the adaptation processing on the recognition result hypotheses, based on the generated data corresponding to the adaptation processing, and supplying the recognition results to the applications, respectively. | 0.628758 |
8,121,904 | 31 | 32 | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. 32. The system of claim 31 wherein the processing system is further configured to provide a user interface to present the single composite output as a visual output to a user of the computer system. | 0.788462 |
8,078,633 | 1 | 2 | 1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. | 1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. 2. The method of claim 1 , wherein a frequency with which a candidate word group occurs in the corpus is based upon a combination of frequencies of one or more of the words from the candidate word group in the corpus. | 0.606884 |
9,953,176 | 12 | 13 | 12. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of the plurality of target entities is metadata related to the user activity and requires anonymization; assigning an anonymized identity to each unique target entity of the plurality of target entities; generating dictionary entries for the plurality of target entities, wherein each dictionary entry comprises a target entity and a corresponding anonymized identifier comprising the anonymized identity for the target entity; generating, by the computing system, an equivalence map, by: making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; storing, in the equivalence map, an identity relationship specifying that the subset of the target entities is associated with the resource; anonymizing user activity, based on the anonymization dictionary previously generated by the computing system, by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized record. | 12. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of the plurality of target entities is metadata related to the user activity and requires anonymization; assigning an anonymized identity to each unique target entity of the plurality of target entities; generating dictionary entries for the plurality of target entities, wherein each dictionary entry comprises a target entity and a corresponding anonymized identifier comprising the anonymized identity for the target entity; generating, by the computing system, an equivalence map, by: making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; storing, in the equivalence map, an identity relationship specifying that the subset of the target entities is associated with the resource; anonymizing user activity, based on the anonymization dictionary previously generated by the computing system, by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized record. 13. The method of claim 12 , wherein generating the equivalence map may be performed prior to storing the anonymized record. | 0.843829 |
7,904,461 | 39 | 42 | 39. The method of claim 38 , further comprising determining label weights for a portion of the nodes, the determination comprising, for each node of the portion, adding the node's label weight to a label weight of a neighboring node's label, for each neighboring node. | 39. The method of claim 38 , further comprising determining label weights for a portion of the nodes, the determination comprising, for each node of the portion, adding the node's label weight to a label weight of a neighboring node's label, for each neighboring node. 42. The method of claim 39 , wherein the label weights for each node of the portion of the nodes are initialized to a starting value before the determination of the label weights for the node. | 0.908222 |
4,178,472 | 8 | 11 | 8. A voiced instruction identification system, particularly for controlling a powered device by voiced instructions of a source person, comprising: means including a microphone and band pass filter for passing a limited frequency band of electrical signals corresponding to spoken moras; Schmidt trigger means for converting said limited frequency band of electrical signals from sine wave form to square wave pulses with several Schmidt pulses per mora; means for eliminating the initial unstable portion of the Schmidt pulses for each mora; a clock pulse source of frequency greater than frequencies in said band, and counter means responsive in each mora to Schmidt pulses occurring subsequent to said initial unstable portion for counting the number of clock pulses in each of a selected number of said subsequent Schmidt pulses so as to produce a selected number of clock pulse totals for each mora; symbolic value sampling means for selecting a representative one of said clock pulse totals and producing an output corresponding quantatively to said representative total, for each mora; tonal pattern change detecting means for detecting a change in said symbolic value sampling means output between consecutively occurring ones of said moras, such that the detected changes provide a tonal change pattern usable to identify the spoken command comprising said moras. | 8. A voiced instruction identification system, particularly for controlling a powered device by voiced instructions of a source person, comprising: means including a microphone and band pass filter for passing a limited frequency band of electrical signals corresponding to spoken moras; Schmidt trigger means for converting said limited frequency band of electrical signals from sine wave form to square wave pulses with several Schmidt pulses per mora; means for eliminating the initial unstable portion of the Schmidt pulses for each mora; a clock pulse source of frequency greater than frequencies in said band, and counter means responsive in each mora to Schmidt pulses occurring subsequent to said initial unstable portion for counting the number of clock pulses in each of a selected number of said subsequent Schmidt pulses so as to produce a selected number of clock pulse totals for each mora; symbolic value sampling means for selecting a representative one of said clock pulse totals and producing an output corresponding quantatively to said representative total, for each mora; tonal pattern change detecting means for detecting a change in said symbolic value sampling means output between consecutively occurring ones of said moras, such that the detected changes provide a tonal change pattern usable to identify the spoken command comprising said moras. 11. The apparatus of claim 8, in which said tonal pattern change detecting means includes a pitch data stack for sequentially storing said symbolic value sampling means outputs each quantatively corresponding to a respective clock pulse total, said apparatus further including a rhythm counter and means supplying same with further clock pulses for counting the time interval during which the sound for each mora is present, and a rhythm data stack for receiving count data from said rhythm counter for each of the desired number of moras. | 0.500926 |
8,732,127 | 12 | 13 | 12. The system of claim 11 wherein a first argument of the vFunction includes a version identifier, and wherein the query handler is further configured to identify the first vNode by comparing the version identifier included in the versioning information of the matching vNode to the version identifier of the first argument of the vFunction, and determining that the matching vNode is the first vNode when the version identifier of the matching vNode matches the first argument of the vFunction included in the query. | 12. The system of claim 11 wherein a first argument of the vFunction includes a version identifier, and wherein the query handler is further configured to identify the first vNode by comparing the version identifier included in the versioning information of the matching vNode to the version identifier of the first argument of the vFunction, and determining that the matching vNode is the first vNode when the version identifier of the matching vNode matches the first argument of the vFunction included in the query. 13. The system of claim 12 wherein when the matching vNode's version identifier does not match the first argument of the vFunction, the query handler is configured to determine that the matching vNode is the first vNode when the matching vNode's version identifier refers to an earlier version of the structured document that is before the version identified by the version identifier in the first argument of the vFunction, and when the matching vNode's end date refers to another version of the structured document that is after the version identified by the version identifier in the first argument of the vFunction. | 0.843687 |
8,261,145 | 3 | 4 | 3. An apparatus for transmitting/receiving a signal in a communication system, the apparatus comprising: a first encoder for inputting an information word during an initial transmission, and for generating a first code word by encoding the input information word using a first parity check matrix, the first code word having a first coding ratio includes the information word and first parity bits; a second encoder for inputting the first code word during a first retransmission, and for generating a second code word by encoding the inputted first code word using a second parity check matrix, the second code word having a second coding ratio includes the information word, the first parity bits and second parity bits; a third encoder for inputting the second code word during a second retransmission, and for generating a third code word by encoding the inputted second code word using a third parity check matrix, the third code word having a third coding ratio includes the information word, the first parity bits, the second parity bits and third parity bits; and a controller of a transmitter for transmitting the first code word to a receiver during the initial transmission, for transmitting the second parity bits to the receiver during the first retransmission, and for transmitting the third parity bits to the receiver during the second retransmission, wherein the second parity check matrix is generated by extending the first parity check matrix using a density evolution, the third parity check matrix is generated by extending the second parity check matrix using the density evolution, and wherein a mother code of the density evolution is the first coding ratio, the density evolution represents an extension scheme adding new parity bits to the first parity check matrix. | 3. An apparatus for transmitting/receiving a signal in a communication system, the apparatus comprising: a first encoder for inputting an information word during an initial transmission, and for generating a first code word by encoding the input information word using a first parity check matrix, the first code word having a first coding ratio includes the information word and first parity bits; a second encoder for inputting the first code word during a first retransmission, and for generating a second code word by encoding the inputted first code word using a second parity check matrix, the second code word having a second coding ratio includes the information word, the first parity bits and second parity bits; a third encoder for inputting the second code word during a second retransmission, and for generating a third code word by encoding the inputted second code word using a third parity check matrix, the third code word having a third coding ratio includes the information word, the first parity bits, the second parity bits and third parity bits; and a controller of a transmitter for transmitting the first code word to a receiver during the initial transmission, for transmitting the second parity bits to the receiver during the first retransmission, and for transmitting the third parity bits to the receiver during the second retransmission, wherein the second parity check matrix is generated by extending the first parity check matrix using a density evolution, the third parity check matrix is generated by extending the second parity check matrix using the density evolution, and wherein a mother code of the density evolution is the first coding ratio, the density evolution represents an extension scheme adding new parity bits to the first parity check matrix. 4. The apparatus as claimed in claim 3 , wherein the first coding ratio exceeds the second coding ratio and the second coding ratio exceeds the third coding ratio. | 0.503049 |
8,112,454 | 1 | 20 | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 20. The method of claim 1 , wherein the display constrained device is at least one of a telephone, a PDA, and a remote control. | 0.934401 |
9,122,484 | 5 | 6 | 5. An information processing system for mashing up web applications, comprising: a memory; a processor communicatively coupled to the memory; and an apparatus for mashing up web applications communicatively coupled to the memory and the processor, the apparatus configured to perform a method comprising: accessing a first web page corresponding to a first web application executing on a server; accessing at least a second web page corresponding to at least a second web application executing on a server, wherein the first web application is separate and distinct from the second web application; generating, based on the first and second web pages that have been accessed, at least two document object models (DOM) corresponding to the first and second web applications respectively; searching each of the at least two DOMs for nodes of a given type; merging, based on the searching, nodes a first set of nodes of the given type from a first document object model of the at least two document object models and at least a second set of nodes of the given type from at least a second DOM of the at least two document object models to obtain a new document object model, wherein the new document object model comprises both the first set of nodes and the second set of nodes; connecting, on the new document object model, the nodes belonging respectively to the at least two document object models, where the connecting comprises establishing code within the new document object model configuring a function of the first web application represented by one of the first set of nodes as a source function and configuring a function of the second web application represented by one of the second set of nodes as a target function of the source function; and obtaining a new web application from the new document object model after connection, wherein the new web application comprises functions associated with the first web application and the at least second web application in response to the first set of nodes and the at least second set of nodes being merged. | 5. An information processing system for mashing up web applications, comprising: a memory; a processor communicatively coupled to the memory; and an apparatus for mashing up web applications communicatively coupled to the memory and the processor, the apparatus configured to perform a method comprising: accessing a first web page corresponding to a first web application executing on a server; accessing at least a second web page corresponding to at least a second web application executing on a server, wherein the first web application is separate and distinct from the second web application; generating, based on the first and second web pages that have been accessed, at least two document object models (DOM) corresponding to the first and second web applications respectively; searching each of the at least two DOMs for nodes of a given type; merging, based on the searching, nodes a first set of nodes of the given type from a first document object model of the at least two document object models and at least a second set of nodes of the given type from at least a second DOM of the at least two document object models to obtain a new document object model, wherein the new document object model comprises both the first set of nodes and the second set of nodes; connecting, on the new document object model, the nodes belonging respectively to the at least two document object models, where the connecting comprises establishing code within the new document object model configuring a function of the first web application represented by one of the first set of nodes as a source function and configuring a function of the second web application represented by one of the second set of nodes as a target function of the source function; and obtaining a new web application from the new document object model after connection, wherein the new web application comprises functions associated with the first web application and the at least second web application in response to the first set of nodes and the at least second set of nodes being merged. 6. The apparatus according to claim 5 , wherein the method further comprises: prior to the merging, searching the at least two document object models to find the nodes. | 0.710345 |
10,083,237 | 6 | 8 | 6. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform actions comprising: receiving a search query; obtaining a candidate set of search results that correspond to the search query; obtaining an indication that the search query is classified as including query terms that (i) do not likely relate to a particular class of people, (ii) likely relate to the particular class of people, or (iii) likely relate to the particular class of people and include sensitive or offensive terms; obtaining, for each search result in the candidate set of search results, an indication that the search result is classified as likely including (i) non-sensitive and non-offensive content, or (ii) sensitive or offensive content; selecting, from among the candidate set of search results, a presentation set of search results based at least on (I) the indication that the search query is classified as including query terms that (i) are not likely related to the particular class of people, (ii) are likely related to the particular class of people, or (iii) are likely related to the particular class of people and include sensitive or offensive terms, and (II) the indication that the search result is classified as likely including (i) non-sensitive and non-offensive content, or (ii) sensitive or offensive content, wherein selecting, from among the candidate set of search results, the presentation set of search results comprises one or more of: reducing a ranking of a search result in the candidate set of search results based on (i) obtaining the indication that the search query used to obtain the search result is classified as likely related to the particular class of people, and (ii) obtaining the indication that the search result is classified as likely including sensitive or offensive content; filtering a search result in the candidate set of search results to remove the search result from the presentation set of search results based on (i) obtaining the indication that the search query used to obtain the search result is classified as likely related to the particular class of people and including sensitive or offensive terms, and (ii) obtaining the indication that the search result is classified as likely including sensitive or offensive content; and selecting a search result in the candidate set of search results to be included in the presentation set of search results without modifying a ranking of the search result or filtering the search result based on obtaining the indication that the search query used to obtain the search result is classified as not likely related to a particular class of people and as likely including non-sensitive and non-offensive terms; and providing one or more search results of the presentation set of search results for output in response to the search query. | 6. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform actions comprising: receiving a search query; obtaining a candidate set of search results that correspond to the search query; obtaining an indication that the search query is classified as including query terms that (i) do not likely relate to a particular class of people, (ii) likely relate to the particular class of people, or (iii) likely relate to the particular class of people and include sensitive or offensive terms; obtaining, for each search result in the candidate set of search results, an indication that the search result is classified as likely including (i) non-sensitive and non-offensive content, or (ii) sensitive or offensive content; selecting, from among the candidate set of search results, a presentation set of search results based at least on (I) the indication that the search query is classified as including query terms that (i) are not likely related to the particular class of people, (ii) are likely related to the particular class of people, or (iii) are likely related to the particular class of people and include sensitive or offensive terms, and (II) the indication that the search result is classified as likely including (i) non-sensitive and non-offensive content, or (ii) sensitive or offensive content, wherein selecting, from among the candidate set of search results, the presentation set of search results comprises one or more of: reducing a ranking of a search result in the candidate set of search results based on (i) obtaining the indication that the search query used to obtain the search result is classified as likely related to the particular class of people, and (ii) obtaining the indication that the search result is classified as likely including sensitive or offensive content; filtering a search result in the candidate set of search results to remove the search result from the presentation set of search results based on (i) obtaining the indication that the search query used to obtain the search result is classified as likely related to the particular class of people and including sensitive or offensive terms, and (ii) obtaining the indication that the search result is classified as likely including sensitive or offensive content; and selecting a search result in the candidate set of search results to be included in the presentation set of search results without modifying a ranking of the search result or filtering the search result based on obtaining the indication that the search query used to obtain the search result is classified as not likely related to a particular class of people and as likely including non-sensitive and non-offensive terms; and providing one or more search results of the presentation set of search results for output in response to the search query. 8. The non-transitory computer-readable storage medium of claim 6 , wherein the particular class of people include (i) people under the age of eighteen, (ii) people under the age of thirteen, or (iii) people under the age of nine, wherein the sensitive or offensive terms include terms associated with one or more of pornography, violence, gore, and spoof, and wherein the sensitive or offensive content includes images, video, or data associated with one or more of pornography, violence, gore, and spoof. | 0.500986 |
7,689,527 | 7 | 8 | 7. The method of claim 1 , wherein for each sequence of the plurality of attribute determination sequences in the training set, receiving the subset of attribute determinations in the attribute determination sequence that is likely to be a false positive comprises a machine learning mechanism receiving, for each input text in a training set of input texts: first data that indicates attribute determinations made by an attribute extractor based on attribute value dictionaries; and second data that indicates accurate attribute determinations or false positive attribute determinations. | 7. The method of claim 1 , wherein for each sequence of the plurality of attribute determination sequences in the training set, receiving the subset of attribute determinations in the attribute determination sequence that is likely to be a false positive comprises a machine learning mechanism receiving, for each input text in a training set of input texts: first data that indicates attribute determinations made by an attribute extractor based on attribute value dictionaries; and second data that indicates accurate attribute determinations or false positive attribute determinations. 8. The method of claim 7 , wherein the machine learning mechanism further receives, for each input text in a training set of input texts, information relating to a category. | 0.912802 |
7,580,929 | 1 | 4 | 1. A method of personalizing a search of a document collection to a user, the method comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. | 1. A method of personalizing a search of a document collection to a user, the method comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. 4. The method of claim 1 , wherein a document accessed by the user comprises a document stored as a favorite or link. | 0.945883 |
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