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8,438,149 | 4 | 8 | 4. A system, comprising: at least one computing device; and a network page generation application executable in the at least one computing device, the network page generation application comprising: logic that extracts a portion of data from a corpus of data that is protected from crawling by a network site crawler; and logic that generates a first network page based at least in part on the portion of data, the first network page being configured for the network site crawler to index the portion of data, the first network page omitting a context for the portion of data from the corpus of data, the first network page including at least one link to a second network page that is protected from crawling by the network site crawler, the second network page providing access to the corpus of data. | 4. A system, comprising: at least one computing device; and a network page generation application executable in the at least one computing device, the network page generation application comprising: logic that extracts a portion of data from a corpus of data that is protected from crawling by a network site crawler; and logic that generates a first network page based at least in part on the portion of data, the first network page being configured for the network site crawler to index the portion of data, the first network page omitting a context for the portion of data from the corpus of data, the first network page including at least one link to a second network page that is protected from crawling by the network site crawler, the second network page providing access to the corpus of data. 8. The system of claim 4 , wherein the second network page includes a noindex attribute. | 0.891892 |
8,887,291 | 1 | 2 | 1. A computer-implemented method for data loss prevention for text fields, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a form submission sent from a client system, the form submission comprising a textual field; storing, by the computing device, at least one characteristic of a value of the textual field within the form submission in connection with an identifier of a form used to generate the form submission; determining, by the computing device and based at least in part on the characteristic of the value of the textual field, that the textual field comprises user-generated content; storing, by the computing device an additional characteristic of an additional value of an additional textual field within the form submission in connection with the identifier of the form; determining, by the computing device and based at least in part on the additional characteristic, that the additional textual field does not comprise user-generated content; intercepting, by the computing device and a subsequent form submission derived from the form; subjecting, by the computing device, the textual field within the subsequent form submission to a data-loss-prevention analysis based at least in part on determining that the textual field comprises user-generated content; omitting, by the computing device, the additional textual field from the data-loss-prevention analysis based at least in part on determining that the additional textual field does not comprise user-generated content; performing, by the computing device, a data-loss-prevention action based on the data-loss-prevention analysis. | 1. A computer-implemented method for data loss prevention for text fields, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a form submission sent from a client system, the form submission comprising a textual field; storing, by the computing device, at least one characteristic of a value of the textual field within the form submission in connection with an identifier of a form used to generate the form submission; determining, by the computing device and based at least in part on the characteristic of the value of the textual field, that the textual field comprises user-generated content; storing, by the computing device an additional characteristic of an additional value of an additional textual field within the form submission in connection with the identifier of the form; determining, by the computing device and based at least in part on the additional characteristic, that the additional textual field does not comprise user-generated content; intercepting, by the computing device and a subsequent form submission derived from the form; subjecting, by the computing device, the textual field within the subsequent form submission to a data-loss-prevention analysis based at least in part on determining that the textual field comprises user-generated content; omitting, by the computing device, the additional textual field from the data-loss-prevention analysis based at least in part on determining that the additional textual field does not comprise user-generated content; performing, by the computing device, a data-loss-prevention action based on the data-loss-prevention analysis. 2. The computer-implemented method of claim 1 , wherein determining that the textual field comprises user-generated content is based at least in part on a plurality of characteristics of a plurality of values of the textual field collected from a plurality of form submissions. | 0.600865 |
8,560,456 | 15 | 19 | 15. A computer-implemented method for exchanging consumer information, comprising the steps of: registering a plurality of data providers and a plurality of data buyers; building, by the computer, a searchable index for each of the data buyers based on at least one index of consumer information for sale provided from one or more of the data providers; for each searchable index of each of the data buyers, encrypting and decrypting the searchable index by a public key unique to a respective one of the data buyers, when building the searchable index; receiving a query and a legal representation from a data buyer of the plurality of data buyers, the query defining a purchase request for consumer information and the legal representation indicating that the data buyer will use the consumer information requested only in accordance with stated permissible uses; retrieving the searchable index associated with the data buyer; determining, by the computer, whether at least one of the data providers maintains the consumer information requested by the data buyer by comparing the purchase request to the searchable index associated with the data buyer; encrypting and decrypting the searchable index associated with the data buyer by a private key unique to the data buyer, when determining whether at least one of the data providers maintains the consumer information requested; in response to determining that at least one of the data providers maintains the consumer information requested, arranging for an exchange of the consumer information requested with the data buyer; and arranging, by the computer, for delivery of a payment from the data buyer. | 15. A computer-implemented method for exchanging consumer information, comprising the steps of: registering a plurality of data providers and a plurality of data buyers; building, by the computer, a searchable index for each of the data buyers based on at least one index of consumer information for sale provided from one or more of the data providers; for each searchable index of each of the data buyers, encrypting and decrypting the searchable index by a public key unique to a respective one of the data buyers, when building the searchable index; receiving a query and a legal representation from a data buyer of the plurality of data buyers, the query defining a purchase request for consumer information and the legal representation indicating that the data buyer will use the consumer information requested only in accordance with stated permissible uses; retrieving the searchable index associated with the data buyer; determining, by the computer, whether at least one of the data providers maintains the consumer information requested by the data buyer by comparing the purchase request to the searchable index associated with the data buyer; encrypting and decrypting the searchable index associated with the data buyer by a private key unique to the data buyer, when determining whether at least one of the data providers maintains the consumer information requested; in response to determining that at least one of the data providers maintains the consumer information requested, arranging for an exchange of the consumer information requested with the data buyer; and arranging, by the computer, for delivery of a payment from the data buyer. 19. The computer-implemented method recited by claim 15 , wherein the registering comprises: receiving registration form data entered by each of the data providers and the data buyers via an on-line registration form, the legal representation from each data buyer being received as part of the registration form data; validating the registration form data; and registering the data providers and data buyers based on an outcome of the validating. | 0.753591 |
6,112,304 | 43 | 45 | 43. The computer system of claim 26, further comprising an administration denizen. | 43. The computer system of claim 26, further comprising an administration denizen. 45. The computer system of claim 43, wherein the administration denizen supports interactive management of denizens in the operational environment. | 0.933544 |
7,848,617 | 1 | 3 | 1. A non-transitory recording medium for storing a data structure, the data structure comprising: at least one text subtitle stream, the text subtitle stream including a style segment and one or more presentation segments, the style segment defining at least one region style and the presentation segment containing at least one region of text linked to one of the at least one region style defined in the style segment by an identifier, wherein the presentation segment recorded or reproduced by a recording/reproducing device contains a continuous presentation flag to indicate that whether continuous presentation is required or not between a current presentation segment and a previous presentation segment, and a presentation time information indicating a start time of the presentation segment and an end time of the presentation segment, wherein the at least one region of text included in the presentation segment is linked to the at least one region style specifying a same text flow, wherein if the continuous presentation flag indicates that continuation presentation is required between the current presentation segment and the previous presentation segment, presentation of the at least one region of text in the previous presentation segment is preserved by the recording/reproducing device for presentation of the current presentation segment, wherein the at least one region of text including text data in which one of the at least one region style applied. | 1. A non-transitory recording medium for storing a data structure, the data structure comprising: at least one text subtitle stream, the text subtitle stream including a style segment and one or more presentation segments, the style segment defining at least one region style and the presentation segment containing at least one region of text linked to one of the at least one region style defined in the style segment by an identifier, wherein the presentation segment recorded or reproduced by a recording/reproducing device contains a continuous presentation flag to indicate that whether continuous presentation is required or not between a current presentation segment and a previous presentation segment, and a presentation time information indicating a start time of the presentation segment and an end time of the presentation segment, wherein the at least one region of text included in the presentation segment is linked to the at least one region style specifying a same text flow, wherein if the continuous presentation flag indicates that continuation presentation is required between the current presentation segment and the previous presentation segment, presentation of the at least one region of text in the previous presentation segment is preserved by the recording/reproducing device for presentation of the current presentation segment, wherein the at least one region of text including text data in which one of the at least one region style applied. 3. The recording medium of claim 1 , wherein the continuous presentation flag is set to “0” to indicate that continuous presentation is not required for the presentation segment with previous one. | 0.718391 |
7,937,715 | 15 | 16 | 15. The computer program product of claim 14 , where the computer useable program code for placing the contents of the include file in-line within the parsed information comprises the computer useable program code for expanding a substitution tag associated with the contents of the include file within the parsed information. | 15. The computer program product of claim 14 , where the computer useable program code for placing the contents of the include file in-line within the parsed information comprises the computer useable program code for expanding a substitution tag associated with the contents of the include file within the parsed information. 16. The computer program product of claim 15 , where the computer useable program code for placing the contents of the include file in-line within the parsed information and for expanding the substitution tag associated with the contents of the include file within the parsed information comprises computer useable program code for placing the in-line contents of the include file and the expanded substitution tag within a <style> element within the parsed information. | 0.885366 |
9,928,267 | 6 | 7 | 6. A computer program product for hierarchical database compression, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: apply a first level of a first type of compression to a first partition of a column of a database and store data generated from an application of the first level of the first type of compression to the first partition in a memory buffer external to the database; and apply a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein to apply the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. | 6. A computer program product for hierarchical database compression, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: apply a first level of a first type of compression to a first partition of a column of a database and store data generated from an application of the first level of the first type of compression to the first partition in a memory buffer external to the database; and apply a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein to apply the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. 7. The computer program product of claim 6 , further comprising: applying a first level of a second type of compression to a second partition of the column of the database; applying a second level of the second type of compression to a subset of the second partition, wherein the first level of the second type of compression comprises a second first-level dictionary and the second level of the second type of compression comprises a second second-level dictionary, and wherein a code size of the second first-level dictionary is larger than a code size of the second second-level dictionary. | 0.608322 |
4,884,972 | 22 | 25 | 22. A method of instruction for teaching language skills or the like comprising the steps of: displaying a plurality of first animated images on a screen, each of said first animated images having at least one of a plurality of graphic symbols inscribed thereon, each of said plurality of symbols associated with speech sound; receiving an input signal and selecting at least one of said first animated images in response to said input signal; generating electronically a voice sound pronouncing the associated speech sound of the symbols inscribed on said selected one of said first animated images; and displaying a second animated image on said screen, said second animated image including a talking head having facial features, said second animated image responsive to said input signal for displaying an animated sequence of body movements including movements of head and facial features simulating the speaking of said associated speech sound in synchrony with said voice sound. | 22. A method of instruction for teaching language skills or the like comprising the steps of: displaying a plurality of first animated images on a screen, each of said first animated images having at least one of a plurality of graphic symbols inscribed thereon, each of said plurality of symbols associated with speech sound; receiving an input signal and selecting at least one of said first animated images in response to said input signal; generating electronically a voice sound pronouncing the associated speech sound of the symbols inscribed on said selected one of said first animated images; and displaying a second animated image on said screen, said second animated image including a talking head having facial features, said second animated image responsive to said input signal for displaying an animated sequence of body movements including movements of head and facial features simulating the speaking of said associated speech sound in synchrony with said voice sound. 25. The method of claim 22 including the steps of moving said selected first animated image from a first location to a second location on said screen; and selecting at least one additional first animated image in response to at least one additional input signal and moving said additional selected first animated image to a third location adjacent said second location to form a combination of said symbols. | 0.739437 |
8,583,284 | 1 | 3 | 1. A decision making mechanism of an active perception module of a robot, the active perception module including at least one processing unit executing one or more instructions from a non-transitory machine-readable medium, said decision making mechanism being operable to decide on at least one prospective action of a robot from a set of actions of said robot by: the active perception module computing a prior probabilistic representation of a prior environment state; the active perception module updating of said prior probabilistic representation with targets of a new observation following the at least one prospective action after an action period, the action period comprising a period for incorporating an action observation pair into an update of an environment state, thereby reducing at least one uncertainty in a posterior probabilistic representation of a posterior environment state to be reached after an appliance of said at least one prospective action, wherein said posterior probabilistic representation is a probabilistic representation resulting from said updating; the active perception module determining an information gain between said prior probabilistic representation and said posterior probabilistic representation by use of at least one information theoretic measure; and the active perception module evaluating said at least one prospective action by estimating the costs of executing said at least one prospective action during the action period and estimating said information gain at the end of the action period. | 1. A decision making mechanism of an active perception module of a robot, the active perception module including at least one processing unit executing one or more instructions from a non-transitory machine-readable medium, said decision making mechanism being operable to decide on at least one prospective action of a robot from a set of actions of said robot by: the active perception module computing a prior probabilistic representation of a prior environment state; the active perception module updating of said prior probabilistic representation with targets of a new observation following the at least one prospective action after an action period, the action period comprising a period for incorporating an action observation pair into an update of an environment state, thereby reducing at least one uncertainty in a posterior probabilistic representation of a posterior environment state to be reached after an appliance of said at least one prospective action, wherein said posterior probabilistic representation is a probabilistic representation resulting from said updating; the active perception module determining an information gain between said prior probabilistic representation and said posterior probabilistic representation by use of at least one information theoretic measure; and the active perception module evaluating said at least one prospective action by estimating the costs of executing said at least one prospective action during the action period and estimating said information gain at the end of the action period. 3. The decision making mechanism according to claim 1 , wherein said at least one prospective action is a robot actuation command demanding a change of position of a sensor of said robot. | 0.763291 |
9,853,876 | 8 | 9 | 8. A system for identifying a network application, comprising: a processor of a computer system; memory comprising instructions executable by the processor, wherein the instructions comprises: a network application analyzer configured to: analyze a source code of a network application, among a plurality of network applications, to extract a plurality of source code tokens; generate an index document of the network application based on the plurality of source code tokens, wherein the index document is included in a plurality of index documents corresponding to the plurality of network applications, the plurality of index documents being loaded as a corpus into a search engine; a flow analyzer configured to: extract a plurality of packet header tokens from a packet header of a packet in a flow to generate one or more query documents; and a correlation analyzer configured to: compare, using the search engine, the plurality of packet header tokens of the one or more query documents to the plurality of index documents to generate a plurality of match scores, wherein each of the plurality of match scores represents a similarity measure between the plurality of packet header tokens and one of the plurality of index documents; and determine, based at least on a match score of the plurality of match scores and corresponding to the network application, that the flow is generated by the network application; and a repository configured to store the plurality of index documents. | 8. A system for identifying a network application, comprising: a processor of a computer system; memory comprising instructions executable by the processor, wherein the instructions comprises: a network application analyzer configured to: analyze a source code of a network application, among a plurality of network applications, to extract a plurality of source code tokens; generate an index document of the network application based on the plurality of source code tokens, wherein the index document is included in a plurality of index documents corresponding to the plurality of network applications, the plurality of index documents being loaded as a corpus into a search engine; a flow analyzer configured to: extract a plurality of packet header tokens from a packet header of a packet in a flow to generate one or more query documents; and a correlation analyzer configured to: compare, using the search engine, the plurality of packet header tokens of the one or more query documents to the plurality of index documents to generate a plurality of match scores, wherein each of the plurality of match scores represents a similarity measure between the plurality of packet header tokens and one of the plurality of index documents; and determine, based at least on a match score of the plurality of match scores and corresponding to the network application, that the flow is generated by the network application; and a repository configured to store the plurality of index documents. 9. The system of claim 8 , wherein generating the match score of the plurality of match scores comprising: comparing the plurality of packet header tokens to the plurality of source code tokens, wherein the match score represents the similarity measure of the plurality of packet header tokens as compared to the plurality of source code tokens. | 0.758403 |
4,817,156 | 21 | 22 | 21. The method of claim 20, wherein the step of producing the smoothed probabilities further comprises the step of: (v) computing: ##EQU30## wherein .lambda..sub.m is a selectable weighting factor and wherein A.sub.ij represents a transition from a state i to a state j in a phone machine. | 21. The method of claim 20, wherein the step of producing the smoothed probabilities further comprises the step of: (v) computing: ##EQU30## wherein .lambda..sub.m is a selectable weighting factor and wherein A.sub.ij represents a transition from a state i to a state j in a phone machine. 22. The method of claim 21, comprising the further steps of: (w) computing basic transition probabilities and label output probabilities for the phone machines of the subsequent speaker which includes the steps of applying a forward-backward algorithm to the short string of labels to compute basic counts and normalizing the basic counts; (x) producing, in response to the entry of (i) smoothed transition probabilities and smoothed label output probabilities (ii) basic transition probabilities and basic label output probabilities, and (iii) the short string of labels into a deleted estimation processor, final label output probabilities which are linearly averaged between the smoothed label output probabilities and the basic label output probabilities. | 0.877264 |
8,103,613 | 29 | 30 | 29. The system of claim 1 , wherein said objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user comprises: an objective occurrence data solicitation module configured to solicit the data indicating incidence of at least one objective occurrence in response, at least in part, to a subjective user state data reception module receiving data indicating incidence of the at least one subjective user state associated with the user. | 29. The system of claim 1 , wherein said objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user comprises: an objective occurrence data solicitation module configured to solicit the data indicating incidence of at least one objective occurrence in response, at least in part, to a subjective user state data reception module receiving data indicating incidence of the at least one subjective user state associated with the user. 30. The system of claim 29 , wherein said objective occurrence data solicitation module configured to solicit the data indicating incidence of at least one objective occurrence in response, at least in part, to a subjective user state data reception module receiving data indicating incidence of the at least one subjective user state associated with the user comprises: an objective occurrence data solicitation module configured to solicit the data indicating incidence of at least one objective occurrence in response, at least in part, to a subjective user state data reception module receiving, via one or more blog entries, the data indicating incidence of the at least one subjective user state associated with the user. | 0.598343 |
8,285,721 | 10 | 13 | 10. A system comprising: an item database; a hardware-implemented analysis module communicatively coupled to the item database, the analysis module being configured to: access a seller-generated item description received from a seller of an item, the item description being descriptive of the item; infer an attribute and an attribute value based on the item description; and include the attribute and the attribute value in an item record for the item, the item record being stored in an item database; and a hardware-implemented mapping module communicatively coupled to the item database, the mapping module being configured to: present a product record stored in a product database to the seller as a proposed record to be mapped to the item record; receive an acceptance of the proposed record from the seller; increment an acceptance count corresponding to the product record; and map the item record to the product record by including a reference to the product record in the item record based on the attribute and on the attribute value. | 10. A system comprising: an item database; a hardware-implemented analysis module communicatively coupled to the item database, the analysis module being configured to: access a seller-generated item description received from a seller of an item, the item description being descriptive of the item; infer an attribute and an attribute value based on the item description; and include the attribute and the attribute value in an item record for the item, the item record being stored in an item database; and a hardware-implemented mapping module communicatively coupled to the item database, the mapping module being configured to: present a product record stored in a product database to the seller as a proposed record to be mapped to the item record; receive an acceptance of the proposed record from the seller; increment an acceptance count corresponding to the product record; and map the item record to the product record by including a reference to the product record in the item record based on the attribute and on the attribute value. 13. The system of claim 10 , wherein: the product database is representative of a decision tree having a plurality of end nodes; the product record represents one of the plurality of end nodes and includes the attribute and a reference value; and the mapping module is to identify the product record by comparing the reference value to the attribute value. | 0.592677 |
9,607,029 | 2 | 3 | 2. The apparatus of claim 1 , wherein the tokens contained in the documents in the document corpus are identified through adaptive tokenization of the documents in the document corpus. | 2. The apparatus of claim 1 , wherein the tokens contained in the documents in the document corpus are identified through adaptive tokenization of the documents in the document corpus. 3. The apparatus of claim 2 , wherein the documents in the document corpus comprise one or more attributes, and wherein adaptive tokenization comprises: selecting one or more tokenization techniques based upon the attributes; and applying the selected tokenization techniques to the attributes of the documents to identify the tokens contained in the documents. | 0.872528 |
8,670,618 | 1 | 5 | 1. A computer-implemented method for extracting personal information from a family history document, comprising: applying optical character recognition (OCR) to a digital image of a family history document to create an OCR copy; identifying a person's name in the digital image; extracting name data from the OCR copy representing the name; confirming accuracy of the extracted name data; publishing the extracted name data in a searchable format; identifying a family relationship indicator corresponding to the identified person's name in the digital image, and extracting relationship data from the OCR copy representing the family relationship indicator. | 1. A computer-implemented method for extracting personal information from a family history document, comprising: applying optical character recognition (OCR) to a digital image of a family history document to create an OCR copy; identifying a person's name in the digital image; extracting name data from the OCR copy representing the name; confirming accuracy of the extracted name data; publishing the extracted name data in a searchable format; identifying a family relationship indicator corresponding to the identified person's name in the digital image, and extracting relationship data from the OCR copy representing the family relationship indicator. 5. The method of claim 1 , wherein extracting name data includes highlighting the identified name, manually selecting the highlighted name, and mapping to data in the OCR copy representing the identified name. | 0.781381 |
9,819,765 | 1 | 7 | 1. A method, comprising: scanning, by a computer, a set of messages of a user sent to or received from a plurality of persons, the messages comprising a first message from a first person; generating a plurality of profiles for the persons, each profile comprising a name of a respective person from one of the messages, and at least one of a social network profile name or a link to a social network profile for the respective person, the plurality of profiles including a first profile for the first person; extracting information from the messages to form search queries, the extracted information comprising a domain obtained from an address of the first message, the domain corresponding to a first website, the search queries including a first query, and the first query comprising search criteria including the domain; communicating, over a network, with a plurality of servers in an automated way to extract data from the servers, the extracting data comprising querying the servers using the search queries, the extracted data comprising first data obtained from the first website; storing a respective portion of the data extracted from the servers in each profile of the plurality of profiles, the storing comprising storing the first data in the first profile; in response to an incomplete input in an input field for a new address of a new message being composed by the user, identifying a set of persons in the plurality of profiles that match the incomplete input, the set of persons including the first person; determining, using the plurality of profiles, a relevancy score for each person of the set of persons based on a type of communication of the new message, wherein an address for a same type of communication as the new address is given more weight than an address for another type of communication, and the relevancy score further based on types of fields in which addresses of senders and recipients of the messages appear, wherein a weight given for an address in a From field is greater than a weight given for an address in a CC or BCC field; and presenting to the user a plurality of suggestions to complete the incomplete input based on the set of persons, wherein the suggestions are presented in an order based on the respective relevancy score for each person of the set of persons. | 1. A method, comprising: scanning, by a computer, a set of messages of a user sent to or received from a plurality of persons, the messages comprising a first message from a first person; generating a plurality of profiles for the persons, each profile comprising a name of a respective person from one of the messages, and at least one of a social network profile name or a link to a social network profile for the respective person, the plurality of profiles including a first profile for the first person; extracting information from the messages to form search queries, the extracted information comprising a domain obtained from an address of the first message, the domain corresponding to a first website, the search queries including a first query, and the first query comprising search criteria including the domain; communicating, over a network, with a plurality of servers in an automated way to extract data from the servers, the extracting data comprising querying the servers using the search queries, the extracted data comprising first data obtained from the first website; storing a respective portion of the data extracted from the servers in each profile of the plurality of profiles, the storing comprising storing the first data in the first profile; in response to an incomplete input in an input field for a new address of a new message being composed by the user, identifying a set of persons in the plurality of profiles that match the incomplete input, the set of persons including the first person; determining, using the plurality of profiles, a relevancy score for each person of the set of persons based on a type of communication of the new message, wherein an address for a same type of communication as the new address is given more weight than an address for another type of communication, and the relevancy score further based on types of fields in which addresses of senders and recipients of the messages appear, wherein a weight given for an address in a From field is greater than a weight given for an address in a CC or BCC field; and presenting to the user a plurality of suggestions to complete the incomplete input based on the set of persons, wherein the suggestions are presented in an order based on the respective relevancy score for each person of the set of persons. 7. The method of claim 1 , wherein the one or more suggestions are a first set of suggestions, and the method further comprises: obtaining a second set of suggestions from a message compose window; and presenting the first and second sets of suggestions in a window. | 0.634615 |
8,734,158 | 7 | 14 | 7. A method of teaching a person to do basic math operations comprised of teaching the person to manipulate a plurality of unique geometric shapes; each unique geometric shape having a specific value ranging 1-10, wherein the unique geometric shape having a value of 10 is formed by manipulating any combination of unique geometric shapes that when their specific values are added together equals the value of 10; wherein the plurality of geometric shapes are comprised of physical, written or digitized substrates, and wherein teaching the person to manipulate a plurality of unique geometric shapes is comprised of teaching the person to manipulate small triangles with a value of 1 forming larger unique geometric shapes, each larger unique geometric shape representing a specific value from 2 to 10; wherein a large square having a value of 10 is comprised by manipulating any combination of unique geometric shapes that when their specific values are added together equals the value of 10. | 7. A method of teaching a person to do basic math operations comprised of teaching the person to manipulate a plurality of unique geometric shapes; each unique geometric shape having a specific value ranging 1-10, wherein the unique geometric shape having a value of 10 is formed by manipulating any combination of unique geometric shapes that when their specific values are added together equals the value of 10; wherein the plurality of geometric shapes are comprised of physical, written or digitized substrates, and wherein teaching the person to manipulate a plurality of unique geometric shapes is comprised of teaching the person to manipulate small triangles with a value of 1 forming larger unique geometric shapes, each larger unique geometric shape representing a specific value from 2 to 10; wherein a large square having a value of 10 is comprised by manipulating any combination of unique geometric shapes that when their specific values are added together equals the value of 10. 14. The method of claim 7 further comprising of teaching the person to manipulate a plurality of unique geometric shapes using the direct representation system. | 0.912184 |
7,734,559 | 7 | 8 | 7. A computer system, comprising: a memory to store executable instructions including at least executable instructions to represent a rule using a zero-suppressed binary decision diagram (ZDD) rule model; and a processor configured to execute the executable instructions stored in the memory to: obtain at least one Exclude ZDD rule component from the ZDD rule model; identify covers in the at least one Exclude ZDD rule component; remove the identified covers from the at least one Exclude ZDD rule component to generate at least one abridged Exclude ZDD rule component by: expanding nodes in the at least one Exclude ZDD rule component to include all attributes specified in the rule; identifying covers within the expanded nodes in the at least one Exclude ZDD rule component; marking nodes associated with the identified covers in the at least one Exclude ZDD rule component; and removing identified covers and marked nodes from the at least one Exclude ZDD rule component to produce the at least one abridged Exclude ZDD rule component; determine satisfiability of the ZDD rule model according to the at least one abridged Exclude ZDD rule component; and provide graphical conflict information based on the determination of satisfiability of the ZDD rule model to achieve satisfiability of the rule represented by the ZDD rule model. | 7. A computer system, comprising: a memory to store executable instructions including at least executable instructions to represent a rule using a zero-suppressed binary decision diagram (ZDD) rule model; and a processor configured to execute the executable instructions stored in the memory to: obtain at least one Exclude ZDD rule component from the ZDD rule model; identify covers in the at least one Exclude ZDD rule component; remove the identified covers from the at least one Exclude ZDD rule component to generate at least one abridged Exclude ZDD rule component by: expanding nodes in the at least one Exclude ZDD rule component to include all attributes specified in the rule; identifying covers within the expanded nodes in the at least one Exclude ZDD rule component; marking nodes associated with the identified covers in the at least one Exclude ZDD rule component; and removing identified covers and marked nodes from the at least one Exclude ZDD rule component to produce the at least one abridged Exclude ZDD rule component; determine satisfiability of the ZDD rule model according to the at least one abridged Exclude ZDD rule component; and provide graphical conflict information based on the determination of satisfiability of the ZDD rule model to achieve satisfiability of the rule represented by the ZDD rule model. 8. The system of claim 7 , wherein the processor is further configured to NOR the at least one abridged Exclude ZDD rule component with an Include ZDD of the rule to generate overall results. | 0.502604 |
5,404,528 | 32 | 39 | 32. An apparatus according to claim 31, wherein said memory stores a library list which includes the entry point for the exported functionality of the application program. | 32. An apparatus according to claim 31, wherein said memory stores a library list which includes the entry point for the exported functionality of the application program. 39. An apparatus according to claim 32, wherein the library list includes entry points for a function from a second application program. | 0.954332 |
9,361,375 | 1 | 6 | 1. A method implemented on at least one machine each of which has at least one processor, storage, and a communication platform connected to a network for generating a document, comprising: obtaining first information related to one or more queries submitted by a user; obtaining second information related to behavior of the user with respect to one or more documents accessed by the user and identified in response to the one or more queries; identifying a research topic based on the first information; identifying at least one of the one or more documents related to the research topic based on the second information; estimating an amount of time that a user spends reviewing the at least one of the one or more documents; generating a research document including information associated with the research topic and the at least one document, wherein generating the research document comprises including, based on the estimated time, each document in the one or more documents in either a first set of documents, or a second set of documents, and the research document is provided to the user by providing a display area comprising a link for the user to review information about the second set of documents, and in a separate display area by providing the user access to information about the first set of documents via a plurality of user interface elements. | 1. A method implemented on at least one machine each of which has at least one processor, storage, and a communication platform connected to a network for generating a document, comprising: obtaining first information related to one or more queries submitted by a user; obtaining second information related to behavior of the user with respect to one or more documents accessed by the user and identified in response to the one or more queries; identifying a research topic based on the first information; identifying at least one of the one or more documents related to the research topic based on the second information; estimating an amount of time that a user spends reviewing the at least one of the one or more documents; generating a research document including information associated with the research topic and the at least one document, wherein generating the research document comprises including, based on the estimated time, each document in the one or more documents in either a first set of documents, or a second set of documents, and the research document is provided to the user by providing a display area comprising a link for the user to review information about the second set of documents, and in a separate display area by providing the user access to information about the first set of documents via a plurality of user interface elements. 6. The method of claim 1 , wherein generating the research document comprises including each query in the one or more queries in either a first set of queries deemed related to the research topic or in a second set of queries deemed unrelated to the research topic, and the research document is provided to the user by providing a display area for the user to review the first set of queries and a user interface element for providing the user access to the second set of queries. | 0.736264 |
9,092,483 | 1 | 5 | 1. A computer-implemented method for user query reformulation, the method comprising: creating, using a processor, a graph that represents a relationship between previous user query terms, the graph comprising nodes that represent the previous user query terms, each of the nodes comprising an n-gram, and edges connecting the nodes; wherein creating the graph comprises performing a random walk analysis to quantify relationships between nodes of the graph, wherein performing the random walk analysis comprises: generating parallel corpora of paired phrases based on a plurality of different fields comprising a plurality of content fields and one or more a popularity fields such that a plurality of edge types occur between at least two nodes; extracting a plurality of aligned n-grams based on alignment probabilities between different n-grams; generating the edges between the aligned n-grams based on the alignment probability of each corresponding edge type; and determining whether to reformulate a user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph taking into account a relationship between the user search term and the graphed search term. | 1. A computer-implemented method for user query reformulation, the method comprising: creating, using a processor, a graph that represents a relationship between previous user query terms, the graph comprising nodes that represent the previous user query terms, each of the nodes comprising an n-gram, and edges connecting the nodes; wherein creating the graph comprises performing a random walk analysis to quantify relationships between nodes of the graph, wherein performing the random walk analysis comprises: generating parallel corpora of paired phrases based on a plurality of different fields comprising a plurality of content fields and one or more a popularity fields such that a plurality of edge types occur between at least two nodes; extracting a plurality of aligned n-grams based on alignment probabilities between different n-grams; generating the edges between the aligned n-grams based on the alignment probability of each corresponding edge type; and determining whether to reformulate a user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph taking into account a relationship between the user search term and the graphed search term. 5. The computer-implemented method recited in claim 1 , comprising optimizing a model that is used to determine whether to reformulate the user query. | 0.878837 |
9,477,759 | 1 | 3 | 1. A computer-implemented method comprising the following operations performed by at least one processor: receiving a query, wherein the query is associated at least in part with a type of entity; generating search results based at least in part on the query; ranking the search results based on relevance to the query; retrieving previously generated data associated with at least one search result of the search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity; determining, based on the relevance to the query, a subset of the ranked search results that are above a first predetermined ranking threshold; determining, for each entity reference, a weighted sum of the frequencies of occurrence of the entity reference in each search result in the subset of ranked search results, wherein the weighted sum normalizes the frequency of occurrence of each respective entity reference for each previously generated data; ranking the one or more entity references based on the respective weighted sums; selecting an entity result from the one or more entity references based at least in part on the ranking of the one or more entity references; and providing an answer to the query based at least in part on the entity result. | 1. A computer-implemented method comprising the following operations performed by at least one processor: receiving a query, wherein the query is associated at least in part with a type of entity; generating search results based at least in part on the query; ranking the search results based on relevance to the query; retrieving previously generated data associated with at least one search result of the search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity; determining, based on the relevance to the query, a subset of the ranked search results that are above a first predetermined ranking threshold; determining, for each entity reference, a weighted sum of the frequencies of occurrence of the entity reference in each search result in the subset of ranked search results, wherein the weighted sum normalizes the frequency of occurrence of each respective entity reference for each previously generated data; ranking the one or more entity references based on the respective weighted sums; selecting an entity result from the one or more entity references based at least in part on the ranking of the one or more entity references; and providing an answer to the query based at least in part on the entity result. 3. The method of claim 1 , wherein the type of the entity is a person type. | 0.954545 |
9,135,350 | 12 | 17 | 12. A non-transitory computer program embodied on a computer readable medium for generating a searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: instructions for harvesting information relevant to each of said items and an age of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the age of said harvested information; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute. | 12. A non-transitory computer program embodied on a computer readable medium for generating a searchable knowledge base for a plurality of items in a choice set, each of said items having an associated set of attributes including at least one subjective attribute, comprising: instructions for harvesting information relevant to each of said items and an age of said harvested information from the Internet; instructions for extracting a set of normalized representations from a corresponding set of statements in one or more texts of said harvested information; instructions for analyzing the normalized representations to derive a set of scores for each attribute in said associated set of attributes for each of said items; instructions for aggregating said derived scores, for said each attribute in said associated set of attributes, by assigning a weight to each of the scores based on at least the age of said harvested information; and instructions for incorporating attributes in said associated set of attributes and their corresponding aggregated scores, for each of said items, into said searchable knowledge base for said choice set, wherein a computer processor is utilized to automatically perform each of said instructions, the incorporating including: annotating a first statement harvested for a first item of the plurality of items with a first set of attributes and a corresponding first set of scores to generate a first annotation, the first set of attributes associated with the first item and determined based on an analysis of text in the first statement, the first statement being one of multiple statements harvested for the first item, the first annotation being one of multiple annotations in the searchable knowledge base, the first annotation including a link to the first statement, and indexing the annotations in the searchable knowledge base to facilitate retrieval of a statement of the statements that corresponds to an input attribute. 17. A computer program as recited in claim 12 , wherein said instructions for extracting comprises instructions for applying a predefined set of rules. | 0.903329 |
7,882,462 | 7 | 9 | 7. A computer-implemented system for generating hardware description language (HDL) code for an executable model of a hardware system, said computer-implemented system comprising: a model comprising a first component that accepts frame-based input data, the first component representing a computational element of the hardware system, wherein a frame is a temporal collection of data samples acquired over a predetermined time period; and generated HDL code for the model, the generated HDL code serializing the first component wherein the generated HDL code serializing the first component further comprises: HDL code for a buffer storing at least a portion of the frame-based input data to the first component; and HDL code for at least one delay unit delaying processing of the at least a portion of the frame-based input data to the first component. | 7. A computer-implemented system for generating hardware description language (HDL) code for an executable model of a hardware system, said computer-implemented system comprising: a model comprising a first component that accepts frame-based input data, the first component representing a computational element of the hardware system, wherein a frame is a temporal collection of data samples acquired over a predetermined time period; and generated HDL code for the model, the generated HDL code serializing the first component wherein the generated HDL code serializing the first component further comprises: HDL code for a buffer storing at least a portion of the frame-based input data to the first component; and HDL code for at least one delay unit delaying processing of the at least a portion of the frame-based input data to the first component. 9. The computer-implemented system of claim 7 , further comprising: generated HDL code linearizing the at least a portion of the frame-based input data to the first component. | 0.839154 |
8,639,552 | 5 | 6 | 5. The method of claim 1 , wherein the e-mail message is sent to a plurality of users who are all associated with the task. | 5. The method of claim 1 , wherein the e-mail message is sent to a plurality of users who are all associated with the task. 6. The method of claim 5 , wherein the system receiving the e-mail message updates stored task information with recipient information specific to the recipient of the electronic message. | 0.920445 |
9,201,959 | 4 | 6 | 4. A system, comprising: at least one computing device; and a video content analysis application executable in the at least one computing device, the video content analysis application comprising: logic that extracts closed captioning data from a video content feature; logic that performs an analysis of text from the closed captioning data; and logic that ranks a plurality of scenes of the video content feature based at least in part upon the analysis of text from the closed captioning data. | 4. A system, comprising: at least one computing device; and a video content analysis application executable in the at least one computing device, the video content analysis application comprising: logic that extracts closed captioning data from a video content feature; logic that performs an analysis of text from the closed captioning data; and logic that ranks a plurality of scenes of the video content feature based at least in part upon the analysis of text from the closed captioning data. 6. The system of claim 4 , wherein the logic that ranks the plurality of scenes based at least in part upon the analysis of text from the closed captioning data further comprises logic that ranks the plurality of scenes based at least in part upon an amount of dialog occurring within individual ones of the plurality of scenes. | 0.662551 |
7,991,806 | 6 | 8 | 6. A computer implemented method comprising: storing, at a network entity, a first taxonomy associated with at least one content publisher, for classifying content for use in delivering advertisements from said network entity, said first taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said content; storing, at said network entity, a second taxonomy associated with at least one advertiser entity, for classifying advertisements delivered from said network entity, said second taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said advertisements; associating, using a computer, each of the categories of the nodes of the first taxonomy with a plurality of content themes; generating mapping information, in a computer, correlating a node of said first taxonomy to a plurality of nodes of said second taxonomy, wherein a first category corresponding to said node of said first taxonomy is related to a plurality of second categories corresponding to said nodes of said second taxonomy based on a logical association between content themes of said first category and said second categories. | 6. A computer implemented method comprising: storing, at a network entity, a first taxonomy associated with at least one content publisher, for classifying content for use in delivering advertisements from said network entity, said first taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said content; storing, at said network entity, a second taxonomy associated with at least one advertiser entity, for classifying advertisements delivered from said network entity, said second taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said advertisements; associating, using a computer, each of the categories of the nodes of the first taxonomy with a plurality of content themes; generating mapping information, in a computer, correlating a node of said first taxonomy to a plurality of nodes of said second taxonomy, wherein a first category corresponding to said node of said first taxonomy is related to a plurality of second categories corresponding to said nodes of said second taxonomy based on a logical association between content themes of said first category and said second categories. 8. The computer implemented method according to claim 6 , further comprising: storing said mapping information in a data storage module. | 0.875229 |
7,853,557 | 50 | 51 | 50. The computer-implemented method of claim 46 , wherein the query is received from a first computer system, the method comprising: generating a response to the query, wherein the generating the response comprises the populating the first and second fields; and transmitting the response to the first computer system. | 50. The computer-implemented method of claim 46 , wherein the query is received from a first computer system, the method comprising: generating a response to the query, wherein the generating the response comprises the populating the first and second fields; and transmitting the response to the first computer system. 51. The computer-implemented method of claim 50 , wherein the generating the response comprises generating a response that answers the query. | 0.957324 |
8,023,636 | 8 | 13 | 8. A computer readable medium for storing a computer program for interactive training based on a simulated customer interaction, the computer readable medium comprising: a dialog code segment that provides a predetermined customer portion of a dialog segment from the simulated customer interaction to a trainee, the dialog segment comprising the customer portion and at least one predetermined keyword associated with the customer portion; a response code segment that receives a response to the customer portion from the trainee; and a determining code segment that determines whether the response includes the at least one keyword. | 8. A computer readable medium for storing a computer program for interactive training based on a simulated customer interaction, the computer readable medium comprising: a dialog code segment that provides a predetermined customer portion of a dialog segment from the simulated customer interaction to a trainee, the dialog segment comprising the customer portion and at least one predetermined keyword associated with the customer portion; a response code segment that receives a response to the customer portion from the trainee; and a determining code segment that determines whether the response includes the at least one keyword. 13. The computer readable medium according to claim 8 , further comprising: a recording code segment that records the response as an audio file; and a playback code segment that plays the audio file in response to a request. | 0.814262 |
8,923,490 | 19 | 20 | 19. The system of claim 17 , wherein the stored instructions configure the one or more processors to perform further operations comprising: determining search results from the one or more indexes responsive to a search query based at least one of the first set of identified one or more keywords and stress features and the second set of identified one or more keywords and stress features. | 19. The system of claim 17 , wherein the stored instructions configure the one or more processors to perform further operations comprising: determining search results from the one or more indexes responsive to a search query based at least one of the first set of identified one or more keywords and stress features and the second set of identified one or more keywords and stress features. 20. The system of claim 19 , wherein the stored instructions configure the one or more processors to perform further operations comprising: receiving a selection of at least one call characteristic; and updating the search results based on the received selection to narrow the search results according to the selected at least one of the call characteristics. | 0.894783 |
7,692,573 | 1 | 2 | 1. A computer readable storage medium having a method encoded thereon, the method represented by computer readable programming code, executed by a computer to perform the method comprising the steps of: classifying input sensor data by comparing one or more measured target attributes with one or more known attributes of a finite set of uniquely identified targets; generating an initial set of one or more candidate targets based upon a comparison of the classified input sensor data with the known attributes of the finite set of uniquely identified targets; calculating a minimum required speed for each candidate target to travel between a geolocation history location and a location provided by the input sensor data, the minimum required speed subject to both obstacle avoidance and status transition time constraints; assigning a statistical weight to each candidate target based upon its calculated minimum required speed; calculating a data association probability of each candidate target with the classified input sensor data; and generating a final set of candidate targets by selecting the candidate targets from the initial set of candidate targets having calculated data association probabilities that exceed a predetermined threshold value. | 1. A computer readable storage medium having a method encoded thereon, the method represented by computer readable programming code, executed by a computer to perform the method comprising the steps of: classifying input sensor data by comparing one or more measured target attributes with one or more known attributes of a finite set of uniquely identified targets; generating an initial set of one or more candidate targets based upon a comparison of the classified input sensor data with the known attributes of the finite set of uniquely identified targets; calculating a minimum required speed for each candidate target to travel between a geolocation history location and a location provided by the input sensor data, the minimum required speed subject to both obstacle avoidance and status transition time constraints; assigning a statistical weight to each candidate target based upon its calculated minimum required speed; calculating a data association probability of each candidate target with the classified input sensor data; and generating a final set of candidate targets by selecting the candidate targets from the initial set of candidate targets having calculated data association probabilities that exceed a predetermined threshold value. 2. The computer readable storage medium of claim 1 , wherein the step of generating an initial set of one or more candidate targets includes selecting, from the finite set of uniquely identified targets, a subset of uniquely identified targets having attributes consistent with the classified input sensor data. | 0.921186 |
8,185,376 | 1 | 3 | 1. A method for determining a language of origin of a word comprising analyzing non-uniform letter sequence portions of the word, wherein analyzing comprises: using one or more processors of a computing system, segmenting the word into strings of letter chunks based on different criteria, the letter chunks being of non-uniform length of one or more letters; using one or more processors of a computing system, ascertaining a probability of the word belonging to a selected language by using a plurality of N-gram models based directly on the letter chunks segmented with the different criteria for each of a plurality of different languages, and providing results from using the plurality of N-gram models based directly on letter chunks extracted with the different criteria to a combined classifier that merges the results from the plurality of N-gram models to provide a hypothesis of the language of origin, wherein the combined classifier comprises a plurality of Gaussian mixture models wherein scores from multiple letter chunks models are treated as an eigenvector of a word and a Gaussian mixture model is provided for each of the plurality of different languages, and wherein the results from the plurality of N-gram models are scored by each of the Gaussian mixture models; and outputting the hypothesis of the language of origin of the word provided by the combined classifier. | 1. A method for determining a language of origin of a word comprising analyzing non-uniform letter sequence portions of the word, wherein analyzing comprises: using one or more processors of a computing system, segmenting the word into strings of letter chunks based on different criteria, the letter chunks being of non-uniform length of one or more letters; using one or more processors of a computing system, ascertaining a probability of the word belonging to a selected language by using a plurality of N-gram models based directly on the letter chunks segmented with the different criteria for each of a plurality of different languages, and providing results from using the plurality of N-gram models based directly on letter chunks extracted with the different criteria to a combined classifier that merges the results from the plurality of N-gram models to provide a hypothesis of the language of origin, wherein the combined classifier comprises a plurality of Gaussian mixture models wherein scores from multiple letter chunks models are treated as an eigenvector of a word and a Gaussian mixture model is provided for each of the plurality of different languages, and wherein the results from the plurality of N-gram models are scored by each of the Gaussian mixture models; and outputting the hypothesis of the language of origin of the word provided by the combined classifier. 3. The method of claim 1 wherein the step of ascertaining includes using a list of selected syllables for the selected language. | 0.842752 |
7,750,911 | 1 | 5 | 1. A drawing system, comprising: a computer system having a display and a pen input device having a pen stylus; the computer system having curve model generation software running thereon; the curve model generation software responsive to one or more strokes of made with the pen stylus to sketch a first 2D curve and generating a first 2D vector curve therefrom; the curve model generation software displaying a guide on the display to guide the user in sketching a second curve; the curve model generation software responsive to one or more strokes made by the user with the pen stylus to sketch a second 2D curve and generating a second 2D vector curve therefrom; and the curve model generation software generating a pair of mirror symmetric 3D vector curves from the first and second 2D vector curves which are displayed on a canvas displayed on the display; wherein the generation of the pair of the mirror symmetric 3D curves by the curve model generation software generates the pair of mirror symmetric 3D includes the curve model generation software: calculating 3D curve c 1 on the display from the first 2D vector curve; creating a ray surface R starting from an eye position e and containing c 1 ; creating a mirrored ray surface R M of R where R M starts from a mirrored eye position e M ; displaying R M on the display where R M converges to a vanishing point and provides the guide for the sketching of the second 2D curve; calculating a second 3D curve c 2 from the second 2D vector curve; creating a 3D curve C 2 by projecting C 2 onto R M ; and creating 3D curve C 1 by mirroring C 2 where 3D curves C 1 and C 2 are the pair of mirror symmetric 3D curves. | 1. A drawing system, comprising: a computer system having a display and a pen input device having a pen stylus; the computer system having curve model generation software running thereon; the curve model generation software responsive to one or more strokes of made with the pen stylus to sketch a first 2D curve and generating a first 2D vector curve therefrom; the curve model generation software displaying a guide on the display to guide the user in sketching a second curve; the curve model generation software responsive to one or more strokes made by the user with the pen stylus to sketch a second 2D curve and generating a second 2D vector curve therefrom; and the curve model generation software generating a pair of mirror symmetric 3D vector curves from the first and second 2D vector curves which are displayed on a canvas displayed on the display; wherein the generation of the pair of the mirror symmetric 3D curves by the curve model generation software generates the pair of mirror symmetric 3D includes the curve model generation software: calculating 3D curve c 1 on the display from the first 2D vector curve; creating a ray surface R starting from an eye position e and containing c 1 ; creating a mirrored ray surface R M of R where R M starts from a mirrored eye position e M ; displaying R M on the display where R M converges to a vanishing point and provides the guide for the sketching of the second 2D curve; calculating a second 3D curve c 2 from the second 2D vector curve; creating a 3D curve C 2 by projecting C 2 onto R M ; and creating 3D curve C 1 by mirroring C 2 where 3D curves C 1 and C 2 are the pair of mirror symmetric 3D curves. 5. The system of claim 1 wherein the curve model generation software in response to a first sketch curve intersecting an existing 3D curve of a pair of existing 3D curves displays on the canvas a mark to provide a perspective drawing hint for where a second sketch curve passes so that a pair of 3D curves generated from the first and second sketch curves will meet the existing pair of 3D curves. | 0.628972 |
9,390,173 | 5 | 6 | 5. A system for assigning a score to an electronic document, the system comprising: a network-connected electronic document rating server computer comprising at least a memory and a processor and further comprising programmable instructions stored in the memory and operating on the processor, the instructions operative for: receiving a plurality of connections from a plurality of user devices, each user device associated to a corresponding member object of the plurality of member objects; receiving a first member rating value for a first member object by a second user device associated to a second member object; storing the first member rating value in a first user rating object associated to the first member object; receiving a second member rating value for a first member object by a third user device associated to a third member object; storing the second member rating value in a second user rating object associated to the first member object; iteratively solving a weighted factor function to determine a first weight factor for the first member object, the first weight factor based on a sum of a weighted first member rating value and a weighted second member rating value divided by a sum of a second weight factor associated to the second member object and the third weight factor associated to the third member object, wherein the weighted first member rating value is calculated by multiplying the first member rating value by the second weight factor of the second member object and a weighted second member rating value being multiplied by a third weight factor of the third member object; storing the first weight factor in the first member object; receiving a first document rating value for an electronic document corresponding to a document object from a first user device corresponding to the first member object; storing the first document rating value in a first document rating object associated to the document object; receiving a second document rating value for the electronic document from the second user device corresponding the second member object; storing the second document rating value in a second document rating object associated to the document object; iteratively solving a weighted score function for a weight score for the document object, the weight score based on a sum of a weighted first document rating value and a weighted second document rating value divided by a sum of the first weight factor and the second weight factor, wherein the weighted first document rating value is calculated by multiplying the first document rating value by the first weight factor, and the weighted second document rating value is calculated by multiplying the second document rating value by the second weight factor; wherein the first member rating value and the second member rating value are within a preconfigured standardized numeric range; wherein the first document rating value and the second document rating value are within a preconfigured standardized numeric range. | 5. A system for assigning a score to an electronic document, the system comprising: a network-connected electronic document rating server computer comprising at least a memory and a processor and further comprising programmable instructions stored in the memory and operating on the processor, the instructions operative for: receiving a plurality of connections from a plurality of user devices, each user device associated to a corresponding member object of the plurality of member objects; receiving a first member rating value for a first member object by a second user device associated to a second member object; storing the first member rating value in a first user rating object associated to the first member object; receiving a second member rating value for a first member object by a third user device associated to a third member object; storing the second member rating value in a second user rating object associated to the first member object; iteratively solving a weighted factor function to determine a first weight factor for the first member object, the first weight factor based on a sum of a weighted first member rating value and a weighted second member rating value divided by a sum of a second weight factor associated to the second member object and the third weight factor associated to the third member object, wherein the weighted first member rating value is calculated by multiplying the first member rating value by the second weight factor of the second member object and a weighted second member rating value being multiplied by a third weight factor of the third member object; storing the first weight factor in the first member object; receiving a first document rating value for an electronic document corresponding to a document object from a first user device corresponding to the first member object; storing the first document rating value in a first document rating object associated to the document object; receiving a second document rating value for the electronic document from the second user device corresponding the second member object; storing the second document rating value in a second document rating object associated to the document object; iteratively solving a weighted score function for a weight score for the document object, the weight score based on a sum of a weighted first document rating value and a weighted second document rating value divided by a sum of the first weight factor and the second weight factor, wherein the weighted first document rating value is calculated by multiplying the first document rating value by the first weight factor, and the weighted second document rating value is calculated by multiplying the second document rating value by the second weight factor; wherein the first member rating value and the second member rating value are within a preconfigured standardized numeric range; wherein the first document rating value and the second document rating value are within a preconfigured standardized numeric range. 6. The system of claim 5 wherein the electronic document is on the Internet. | 0.885542 |
10,127,569 | 1 | 5 | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. 5. The non-transitory computer-readable medium of claim 1 , wherein the designing the instance of the child entity is performed recursively for each child entity. | 0.898876 |
9,195,648 | 9 | 16 | 9. A system for managing multi-lingual knowledge bases, comprising: a database housed on a server, the server having a processor system including at least one processor; and a memory system including a machine readable medium having stored thereon one or more sequences of instructions which, when executed, cause a method to be carried out, the method comprising: receiving, by a host system on the server, a request for a language translation to one or more languages of an article available in a first language in a knowledge base, the request being initiated through a user interface having at least one input area; determining that the article is not available in the knowledge base in the requested one or more languages; determining, based at least in part on both a predicted return on investment (ROI) associated with translating the article and a frequency of the article being referenced by other articles within a designated time period, that a translation request should be sent; sending, from the host system, responsive to determining that the translation request should be sent, the translation request; receiving, by the host system, one or more language translations of the article from a source other than the knowledge base; storing the one or more language translations in the knowledge base; and publishing the translations using a process workflow to define a versioned life cycle for the one or more language translations as the one or more language translations move between draft, online and archived states, to provide the one or more language translations to users of the knowledge base. | 9. A system for managing multi-lingual knowledge bases, comprising: a database housed on a server, the server having a processor system including at least one processor; and a memory system including a machine readable medium having stored thereon one or more sequences of instructions which, when executed, cause a method to be carried out, the method comprising: receiving, by a host system on the server, a request for a language translation to one or more languages of an article available in a first language in a knowledge base, the request being initiated through a user interface having at least one input area; determining that the article is not available in the knowledge base in the requested one or more languages; determining, based at least in part on both a predicted return on investment (ROI) associated with translating the article and a frequency of the article being referenced by other articles within a designated time period, that a translation request should be sent; sending, from the host system, responsive to determining that the translation request should be sent, the translation request; receiving, by the host system, one or more language translations of the article from a source other than the knowledge base; storing the one or more language translations in the knowledge base; and publishing the translations using a process workflow to define a versioned life cycle for the one or more language translations as the one or more language translations move between draft, online and archived states, to provide the one or more language translations to users of the knowledge base. 16. The system of claim 9 , where the article available in the first language is exported for translation, a copy of the article in the first language is sent directly to a translator or to a storage area to which a queue of translators of the assignment queue have access, and any one translator from the queue of translators may view, copy, and download the article, thereby allowing the translator to translate the article. | 0.501171 |
8,838,434 | 1 | 2 | 1. A computer-implemented method for generating training data for call routing, the computer-implemented method comprising: accessing a first text corpus, the first text corpus including transcribed utterances that have been transcribed from spoken queries spoken in a first natural language, each transcribed utterance linked to a semantic tag that a first speech recognition call router uses to route telephone calls; translating the transcribed utterances from the first natural language to a second natural language via a machine translation process, the machine translation process generating an N-best list of possible translations for each transcribed utterance that is processed by the machine translation process, each possible translation having a machine translation score that indicates a probability of being a correct translation, each possible translation being linked to a semantic tag from a corresponding transcribed utterance; from each N-best list, selecting a 1-best possible translation and adding the 1-best translation to a second text corpus, each selected 1-best translation having a highest machine translation score as compared to machine translation scores of other possible translations within a respective N-best list; from each N-best list, selecting a second possible translation and adding the second possible translation to the second text corpus, each selected second possible translation being selected based on a measure of individual words from each possible translation that match individual words from at least one possible translation that has been added to the second text corpus and that has been selected from a same N-best list; and training a second speech recognition call router using the second text corpus, the second speech recognition call router configured to recognize spoken queries that are spoken in the second natural language, the second speech recognition call router using a speech classification system based on the first speech recognition call router. | 1. A computer-implemented method for generating training data for call routing, the computer-implemented method comprising: accessing a first text corpus, the first text corpus including transcribed utterances that have been transcribed from spoken queries spoken in a first natural language, each transcribed utterance linked to a semantic tag that a first speech recognition call router uses to route telephone calls; translating the transcribed utterances from the first natural language to a second natural language via a machine translation process, the machine translation process generating an N-best list of possible translations for each transcribed utterance that is processed by the machine translation process, each possible translation having a machine translation score that indicates a probability of being a correct translation, each possible translation being linked to a semantic tag from a corresponding transcribed utterance; from each N-best list, selecting a 1-best possible translation and adding the 1-best translation to a second text corpus, each selected 1-best translation having a highest machine translation score as compared to machine translation scores of other possible translations within a respective N-best list; from each N-best list, selecting a second possible translation and adding the second possible translation to the second text corpus, each selected second possible translation being selected based on a measure of individual words from each possible translation that match individual words from at least one possible translation that has been added to the second text corpus and that has been selected from a same N-best list; and training a second speech recognition call router using the second text corpus, the second speech recognition call router configured to recognize spoken queries that are spoken in the second natural language, the second speech recognition call router using a speech classification system based on the first speech recognition call router. 2. The computer-implemented method of claim 1 , wherein selecting the second possible translation includes selecting each second possible translation based on evaluating individual words from each possible translation as compared to a measure of matching individual words from the second text corpus being linked to different semantic tags. | 0.847807 |
6,134,541 | 21 | 23 | 21. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for performing an exact search for specified data using the one or more indexes, said method steps comprising: associating specified data to a data cluster based on clustering information, said data cluster being a partition of an original data input set; reducing a dimensionality of the specified data, based on dimensionality reduction information for a reduced dimensionality version of the cluster; recursively applying said associating and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; and searching, using low dimensional indexes to said lowest level and a reduced dimensionality specified data, for cluster elements of the reduced dimensionality version of the cluster matching the specified data. | 21. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for performing an exact search for specified data using the one or more indexes, said method steps comprising: associating specified data to a data cluster based on clustering information, said data cluster being a partition of an original data input set; reducing a dimensionality of the specified data, based on dimensionality reduction information for a reduced dimensionality version of the cluster; recursively applying said associating and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; and searching, using low dimensional indexes to said lowest level and a reduced dimensionality specified data, for cluster elements of the reduced dimensionality version of the cluster matching the specified data. 23. The program storage device of claim 21, wherein said reducing step comprises a singular value decomposition, said searching further comprising the step of: searching an index for a matching reduced dimensionality cluster, based on decomposed specified data. | 0.874156 |
8,005,294 | 23 | 28 | 23. A method for determining a sequence of segments of a segmented image of a cursive written word processed in a word recognition system, comprising: finding the number of segments, wherein the finding step includes locating a first segment and a last segment in the imaged word; and determining the sequence of segments using an over-segmentation-relabeling algorithm, wherein the over-segmentation-relabeling algorithm includes: characterizing segments as either situated segments or unsituated segments, wherein situated segments include the first and last segments, segments having an X-coordinate or Y-coordinate coverage that exceed a threshold value, and small segments that are cursively connected to segments on each side, and wherein unsituated segments are segments not characterized as situated segments; and placing each unsituated segment having a situated segment above or below so as to either immediately precede or follow the situated segment in the sequence of segments. | 23. A method for determining a sequence of segments of a segmented image of a cursive written word processed in a word recognition system, comprising: finding the number of segments, wherein the finding step includes locating a first segment and a last segment in the imaged word; and determining the sequence of segments using an over-segmentation-relabeling algorithm, wherein the over-segmentation-relabeling algorithm includes: characterizing segments as either situated segments or unsituated segments, wherein situated segments include the first and last segments, segments having an X-coordinate or Y-coordinate coverage that exceed a threshold value, and small segments that are cursively connected to segments on each side, and wherein unsituated segments are segments not characterized as situated segments; and placing each unsituated segment having a situated segment above or below so as to either immediately precede or follow the situated segment in the sequence of segments. 28. The method of claim 23 , wherein the situated segments further include any special diacritic present in the imaged word, wherein a special diacritic includes a double consonant or a shadda. | 0.923715 |
9,104,312 | 1 | 3 | 1. A method, performed using one or more processors and a memory, for data input, the method comprising: receiving, through an input device and using the one or more processors, a first user input as part of a gesture, wherein the gesture comprises at least a first input selection that represents less than an entire word and a second input selection; and wherein the gesture is a continuous stroke across a virtual keyboard from a first simulated key across one or more other simulated keys; identifying, in the first user input, a bend from the first input selection to a current input location along the gesture; determining that the bend indicates a third input selection that represents a portion of the word between the first input selection and the second input selection; assigning to the bend a directional classification from a discrete set of directional classifications; determining one or more candidates for the third input selection based on the candidates for the third input selection being in a direction, relative to the first input selection, corresponding to the assigned directional classification; determining, using the one or more processors, one or more possible word suggestions based upon the first input selection and the one or more candidates for the third input selection, wherein the one or more possible word suggestions are determined prior to receiving the second input selection; and providing, using a display, the possible word suggestions to the user. | 1. A method, performed using one or more processors and a memory, for data input, the method comprising: receiving, through an input device and using the one or more processors, a first user input as part of a gesture, wherein the gesture comprises at least a first input selection that represents less than an entire word and a second input selection; and wherein the gesture is a continuous stroke across a virtual keyboard from a first simulated key across one or more other simulated keys; identifying, in the first user input, a bend from the first input selection to a current input location along the gesture; determining that the bend indicates a third input selection that represents a portion of the word between the first input selection and the second input selection; assigning to the bend a directional classification from a discrete set of directional classifications; determining one or more candidates for the third input selection based on the candidates for the third input selection being in a direction, relative to the first input selection, corresponding to the assigned directional classification; determining, using the one or more processors, one or more possible word suggestions based upon the first input selection and the one or more candidates for the third input selection, wherein the one or more possible word suggestions are determined prior to receiving the second input selection; and providing, using a display, the possible word suggestions to the user. 3. The method of claim 1 , wherein the discrete set of directional classifications comprise directional classifications corresponding to up, down, left, and right. | 0.782667 |
7,685,512 | 1 | 6 | 1. A computer readable medium for use in validating an eXtensible Markup Language (XML) message in a particular wire format, said computer readable medium containing computer-executable instructions which, when performed by a processor in a computing device, cause the computing device to: from a custom XML schema based message model having at least one wire format specific rendering option associated with an XML entity representing at least a portion of said XML message, generate an XML schema fragment for use in validating said XML message at a node that lacks said custom XML schema based message model, wherein said XML schema fragment conforms to said particular wire format, wherein said custom XML schema based message model comprises a logical model of said message that complies with a standard XML schema, and wherein said custom XML schema based message model comprises a physical model that customizes said message using a logical model extension that is unsupported by said standard XML schema, and wherein said physical model comprises said logical model extension and a wire format specific rendering option, wherein said wire format specific rendering option is a directive that specifies a different wire format for each partial component of said message. | 1. A computer readable medium for use in validating an eXtensible Markup Language (XML) message in a particular wire format, said computer readable medium containing computer-executable instructions which, when performed by a processor in a computing device, cause the computing device to: from a custom XML schema based message model having at least one wire format specific rendering option associated with an XML entity representing at least a portion of said XML message, generate an XML schema fragment for use in validating said XML message at a node that lacks said custom XML schema based message model, wherein said XML schema fragment conforms to said particular wire format, wherein said custom XML schema based message model comprises a logical model of said message that complies with a standard XML schema, and wherein said custom XML schema based message model comprises a physical model that customizes said message using a logical model extension that is unsupported by said standard XML schema, and wherein said physical model comprises said logical model extension and a wire format specific rendering option, wherein said wire format specific rendering option is a directive that specifies a different wire format for each partial component of said message. 6. The computer readable medium of claim 1 , wherein said XML entity is a local element declaration of simple type or an element reference referencing a referenced global element declaration of simple type, and wherein said wire format specific rendering option specifies that said XML entity is to be rendered as an attribute of an XML element of complex type having a complex type definition which contains said XML entity. | 0.796651 |
8,117,549 | 1 | 10 | 1. A method of capturing actions that are performed on at least one medical image of a patient during a medical imaging interpretation, the method being implemented using a computer system, the method comprising: (a) displaying a workflow template on a display of the computer system; (b) displaying the at least one medical image of the patient on said display; (c) automatically extracting data from an electronic medical record of the patient, or other data related to the patient, from a database, into said workflow template provided on said display; (d) capturing and storing one or more user actions as they are performed on the medical image of the patient, by an interpreting user during an entire medical imaging interpretation, using an auditing function of the computer system; (e) automatically generating user action information from the one or more captured actions, to prompt said user to perform certain actions; (f) storing the captured user actions and user action information, along with said data related to the patient, in said database, with the at least one medical image of the patient, as a new workflow sequence onto a new workflow template as a pre-defined protocol; (g) accessing said new workflow template having said pre-defined protocol from said database; (h) displaying to a new user, in said new workflow template, a recreation of the exact pre-defined protocol including said data related to the patient, stored by said previous interpreting user in said database, as a continuous replica of said previous interpreting user's actions and user action information stored in said workflow sequence, such that said new user may selectively review and modify clinically pertinent medical images and said data related to the patient, in a continuous manner that follows said stored workflow template as created by said previous interpreting user; and (i) repeating steps (b)-(f), such that a modified new workflow template is created and stored in said database: wherein each said modified new workflow template is a cumulative, refined, and dynamic workflow sequence of a series of said captured user actions and user action information, along with data related to each patient, with the at least one medical image of said patient, in order to provide best practice of said medical image interpretation for said user. | 1. A method of capturing actions that are performed on at least one medical image of a patient during a medical imaging interpretation, the method being implemented using a computer system, the method comprising: (a) displaying a workflow template on a display of the computer system; (b) displaying the at least one medical image of the patient on said display; (c) automatically extracting data from an electronic medical record of the patient, or other data related to the patient, from a database, into said workflow template provided on said display; (d) capturing and storing one or more user actions as they are performed on the medical image of the patient, by an interpreting user during an entire medical imaging interpretation, using an auditing function of the computer system; (e) automatically generating user action information from the one or more captured actions, to prompt said user to perform certain actions; (f) storing the captured user actions and user action information, along with said data related to the patient, in said database, with the at least one medical image of the patient, as a new workflow sequence onto a new workflow template as a pre-defined protocol; (g) accessing said new workflow template having said pre-defined protocol from said database; (h) displaying to a new user, in said new workflow template, a recreation of the exact pre-defined protocol including said data related to the patient, stored by said previous interpreting user in said database, as a continuous replica of said previous interpreting user's actions and user action information stored in said workflow sequence, such that said new user may selectively review and modify clinically pertinent medical images and said data related to the patient, in a continuous manner that follows said stored workflow template as created by said previous interpreting user; and (i) repeating steps (b)-(f), such that a modified new workflow template is created and stored in said database: wherein each said modified new workflow template is a cumulative, refined, and dynamic workflow sequence of a series of said captured user actions and user action information, along with data related to each patient, with the at least one medical image of said patient, in order to provide best practice of said medical image interpretation for said user. 10. The method according to claim 1 , further comprising: enabling navigation of the workflow sequence in at least one of a computer system-implemented automatic or manual mode. | 0.870614 |
8,266,585 | 5 | 6 | 5. The method according to claim 4 , wherein said high-level programming language is an object-oriented language, and said source code elements include invocations of software methods exposed by software objects being instantiations of software classes. | 5. The method according to claim 4 , wherein said high-level programming language is an object-oriented language, and said source code elements include invocations of software methods exposed by software objects being instantiations of software classes. 6. The method according to claim 5 , wherein said fitting probabilities include probabilities of software methods of a software class being invoked after software methods of another software class. | 0.91094 |
8,584,045 | 1 | 3 | 1. A method of visually presenting information to a computer user, the method comprising: providing a notification at an interface of a computing device that a status of at least one of an initial data object and a semantic relationship between the initial data object and another data object has changed; receiving a first user input at the interface, the first user input corresponding to at least one of the initial data object and an initial set of data objects; determining, in response to the first user input, semantic relationships among a plurality of data objects, each data object being of a type, wherein the type comprises one or more of a customer, a supplier, a purchase order, and a material, and information about each data object and the semantic relationships among the plurality of data objects being stored in a data object repository; filtering the plurality of data objects based on one or more of a particular type of a data object or an instance of the data object to provide filtered data objects; grouping the filtered data objects into sets of data objects, the data objects in a set of data objects being of a same type and having a same type of semantic relationship to the at least one of the initial data object and the initial set of data objects; presenting, on a display of the interface, a first graphical user interface including multiple path graphical elements presenting respective paths of the semantic relationships between one of the initial data object and the initial set of data objects and a respective one of a destination object and a destination set of data objects, the first graphical user interface allowing the computer user to perform analyses and actions not predefined in existing workflows and to select a first number of data object relationship levels to be presented in the first graphical user interface; receiving a second user input at the interface, the second user input indicating a first graphical element, the first graphical element corresponding to a second data object or a second set of data objects provided in a path graphical element; and in response to receiving the second user input, presenting, on the display, a second graphical user interface including the first graphical element and at least one semantic relationship between the first graphical element and another graphical element, the second graphical user interface allowing the computer user to perform analyses and actions not predefined in the existing workflows and to select a second number of data object relationship levels to be presented in the second graphical user interface. | 1. A method of visually presenting information to a computer user, the method comprising: providing a notification at an interface of a computing device that a status of at least one of an initial data object and a semantic relationship between the initial data object and another data object has changed; receiving a first user input at the interface, the first user input corresponding to at least one of the initial data object and an initial set of data objects; determining, in response to the first user input, semantic relationships among a plurality of data objects, each data object being of a type, wherein the type comprises one or more of a customer, a supplier, a purchase order, and a material, and information about each data object and the semantic relationships among the plurality of data objects being stored in a data object repository; filtering the plurality of data objects based on one or more of a particular type of a data object or an instance of the data object to provide filtered data objects; grouping the filtered data objects into sets of data objects, the data objects in a set of data objects being of a same type and having a same type of semantic relationship to the at least one of the initial data object and the initial set of data objects; presenting, on a display of the interface, a first graphical user interface including multiple path graphical elements presenting respective paths of the semantic relationships between one of the initial data object and the initial set of data objects and a respective one of a destination object and a destination set of data objects, the first graphical user interface allowing the computer user to perform analyses and actions not predefined in existing workflows and to select a first number of data object relationship levels to be presented in the first graphical user interface; receiving a second user input at the interface, the second user input indicating a first graphical element, the first graphical element corresponding to a second data object or a second set of data objects provided in a path graphical element; and in response to receiving the second user input, presenting, on the display, a second graphical user interface including the first graphical element and at least one semantic relationship between the first graphical element and another graphical element, the second graphical user interface allowing the computer user to perform analyses and actions not predefined in the existing workflows and to select a second number of data object relationship levels to be presented in the second graphical user interface. 3. The method of claim 1 , further including, in response to user selection of the first graphical element, presenting a second graphical element corresponding to another set of data objects of a second type, and at least one semantic relationship between presented sets. | 0.745301 |
8,364,694 | 25 | 26 | 25. The server system of claim 20 , wherein the search hints request is issued by a client device, wherein the client device supports one or more media types, and wherein the instructions for determining of the set of search hints further comprise instructions for: obtaining a location of the client device; and eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device. | 25. The server system of claim 20 , wherein the search hints request is issued by a client device, wherein the client device supports one or more media types, and wherein the instructions for determining of the set of search hints further comprise instructions for: obtaining a location of the client device; and eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device. 26. The server system of claim 25 , wherein the one or more programs further comprise instructions for: limiting the number of search hints remaining in the set of search hints. | 0.945938 |
7,600,017 | 6 | 7 | 6. The system of claim 5 , wherein the opinion rating is a numerical sentiment score on a numerical scale. | 6. The system of claim 5 , wherein the opinion rating is a numerical sentiment score on a numerical scale. 7. The system of claim 6 , wherein the sentiment score is capable of being one of a positive sentiment score, a negative sentiment score and a zero sentiment score. | 0.964487 |
9,972,322 | 14 | 23 | 14. The system of claim 10 , wherein the digital signal processor to perform speaker recognition comprises the digital signal processor to accept the received audio input as corresponding to a target user when the speaker recognition score exceeds the selected adaptive speaker recognition threshold or to reject the received audio input as corresponding to the target user when the speaker recognition score does not exceed the selected adaptive speaker recognition threshold. | 14. The system of claim 10 , wherein the digital signal processor to perform speaker recognition comprises the digital signal processor to accept the received audio input as corresponding to a target user when the speaker recognition score exceeds the selected adaptive speaker recognition threshold or to reject the received audio input as corresponding to the target user when the speaker recognition score does not exceed the selected adaptive speaker recognition threshold. 23. The system of claim 14 , wherein the speaker recognition score and the second speaker recognition score both exceed the selected adaptive speaker recognition threshold and the digital signal processor is further to provide an identified speaker indicator corresponding to the first user based on the speaker recognition score exceeding the second speaker recognition score. | 0.883498 |
10,019,708 | 27 | 36 | 27. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store including phrase token configuration information associated with transaction phrase tokens, wherein the transaction phrase tokens comprise a set of unambiguous characters, and wherein the transaction phrase tokens are associated with transaction accounts via the phrase token configuration information; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the phrase token configuration information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the phrase token configuration information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. | 27. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store including phrase token configuration information associated with transaction phrase tokens, wherein the transaction phrase tokens comprise a set of unambiguous characters, and wherein the transaction phrase tokens are associated with transaction accounts via the phrase token configuration information; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the phrase token configuration information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the phrase token configuration information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. 36. The system as recited in claim 27 , wherein the set of characters consists of a set of characters selected in their entirety by a transaction phrase token holder associated with a transaction phrase token assignment request. | 0.843621 |
9,245,051 | 15 | 16 | 15. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, cause, at least in part, a creation of one or more bounding boxes around one or more estimated text portions of sensor data associated with at least one device; cause, at least in part, an optical character recognition of the one or more estimated text portions within each of the one or more bounding boxes to determine recognized characters; cause, at least in part, a merger of some of the one or more bounding boxes into at least one merged box along a bounding box line of some of the estimated text portions based, at least in part, on the recognized characters within the each bounding box; cause, at least in part, an extraction, from some of the recognized characters that are within the remaining one or more bounding boxes that are not merged, of one or more search terms for at least one query based, at least in part, on the recognized characters within the at least one merged box; and a search based, at least in part, on the at least one query and the one or more search terms to generate one or more results of the at least one query, wherein the one or more bounding boxes are assigned an identification number and ranked in order from a top of an image to a bottom of the image sensed by way of an optical sensor. | 15. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, cause, at least in part, a creation of one or more bounding boxes around one or more estimated text portions of sensor data associated with at least one device; cause, at least in part, an optical character recognition of the one or more estimated text portions within each of the one or more bounding boxes to determine recognized characters; cause, at least in part, a merger of some of the one or more bounding boxes into at least one merged box along a bounding box line of some of the estimated text portions based, at least in part, on the recognized characters within the each bounding box; cause, at least in part, an extraction, from some of the recognized characters that are within the remaining one or more bounding boxes that are not merged, of one or more search terms for at least one query based, at least in part, on the recognized characters within the at least one merged box; and a search based, at least in part, on the at least one query and the one or more search terms to generate one or more results of the at least one query, wherein the one or more bounding boxes are assigned an identification number and ranked in order from a top of an image to a bottom of the image sensed by way of an optical sensor. 16. The apparatus of claim 15 , wherein the optical sensor is associated with an augmented reality display. | 0.860313 |
10,078,487 | 12 | 15 | 12. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: accessing a list of notification items, the list including a plurality of notification items, wherein each respective one of the plurality of notification items is associated with a respective urgency value; prior to outputting a first notification item of the plurality of notification items: detecting an information item received from an external device; determining whether the information item is relevant to an urgency value of the first notification item of the plurality of notification items; and upon determining that the information item is relevant to the urgency value of the first notification item, adjusting the urgency value of the first notification item and incorporating content from the information item into the first notification item; determining whether the adjusted urgency value of the first notification item satisfies a predetermined threshold; and upon determining that the adjusted urgency value satisfies the predetermined threshold, providing the first notification item to a user, the first notification item including the incorporated content from the information item. | 12. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: accessing a list of notification items, the list including a plurality of notification items, wherein each respective one of the plurality of notification items is associated with a respective urgency value; prior to outputting a first notification item of the plurality of notification items: detecting an information item received from an external device; determining whether the information item is relevant to an urgency value of the first notification item of the plurality of notification items; and upon determining that the information item is relevant to the urgency value of the first notification item, adjusting the urgency value of the first notification item and incorporating content from the information item into the first notification item; determining whether the adjusted urgency value of the first notification item satisfies a predetermined threshold; and upon determining that the adjusted urgency value satisfies the predetermined threshold, providing the first notification item to a user, the first notification item including the incorporated content from the information item. 15. The electronic device of claim 12 , further comprising establishing the predetermined threshold in accordance with a calendar item associated with a current time. | 0.679537 |
9,916,536 | 3 | 4 | 3. The method of claim 1 , wherein the importance criteria further relates to a comparison between a first set of evidence that identifies the first relationship with a second set of evidence that identifies the second relationship. | 3. The method of claim 1 , wherein the importance criteria further relates to a comparison between a first set of evidence that identifies the first relationship with a second set of evidence that identifies the second relationship. 4. The method of claim 3 , wherein the comparison between the first set of evidence and the second set of evidence is based at least in part upon a number of evidentiary documents within each of the first set of evidence and the second set of evidence. | 0.930078 |
9,030,417 | 12 | 14 | 12. An apparatus configured to assist in avoiding incorrect input in a portable terminal, the apparatus comprising: an input unit configured to receive a user input; a storage unit configured to store data; and a controller configured to, after identifying an input character string from the user input, search a plurality of candidate words recommended for the input character string from among one or more previously registered candidate words, calculate a similarity between the input character string and each of the searched candidate words based at least partially upon a type of keypad used to input the input character string, and display, via a display, one or more of the searched candidate words according to the calculated similarity, wherein the controller is configured to calculate the similarity between the input character string and each of the searched candidate words by identifying the keypad type; determining each cost of an insert operation, a delete operation, and a replace operation correspondingly to the identified keypad type; and calculating an edit distance using the operations according to the respective cost associated with each operation. | 12. An apparatus configured to assist in avoiding incorrect input in a portable terminal, the apparatus comprising: an input unit configured to receive a user input; a storage unit configured to store data; and a controller configured to, after identifying an input character string from the user input, search a plurality of candidate words recommended for the input character string from among one or more previously registered candidate words, calculate a similarity between the input character string and each of the searched candidate words based at least partially upon a type of keypad used to input the input character string, and display, via a display, one or more of the searched candidate words according to the calculated similarity, wherein the controller is configured to calculate the similarity between the input character string and each of the searched candidate words by identifying the keypad type; determining each cost of an insert operation, a delete operation, and a replace operation correspondingly to the identified keypad type; and calculating an edit distance using the operations according to the respective cost associated with each operation. 14. The apparatus of claim 12 , wherein the controller is configured to present the candidate words in order of high similarity by presenting corresponding candidate words in ascending order of calculated edit distance. | 0.865644 |
7,636,701 | 12 | 13 | 12. A method as in claim 2 , including steps of in a computer game having at least one decision model, the decision model being capable of generating a response to a query for decision, generating a response to a query for decision including training one or more non-player characters in response to a set of game results, wherein those game results are produced by at least one of one or more non-player characters or at least one of one or more player characters; wherein group actions by those one or more non-player characters are responsive to the knowledge and style of at least one human user. | 12. A method as in claim 2 , including steps of in a computer game having at least one decision model, the decision model being capable of generating a response to a query for decision, generating a response to a query for decision including training one or more non-player characters in response to a set of game results, wherein those game results are produced by at least one of one or more non-player characters or at least one of one or more player characters; wherein group actions by those one or more non-player characters are responsive to the knowledge and style of at least one human user. 13. A method as in claim 12 , wherein those group actions include at least one of: business actions, military actions, political actions, social actions, sports team actions. | 0.982666 |
8,918,323 | 1 | 7 | 1. A method, comprising: at a computer comprising a computer program to implement processing operations: receiving data related to content of a target; filtering the data to locate a target term; accessing one or more tables in a repository, the one or more tables comprising entries with a substitution unit corresponding to the target term, the entries arranged according to a prioritized scheme that defines a position for the substitution unit in the tables; and generating an output comprising data that represents the substitution unit to be utilized by a text-to-speech generator to generate spoken content, wherein the position of the substitution unit in the one or more tables is assigned based on a specificity characteristic that describes the relative inclusivity of the substitution unit as compared to other substitution units in the one or more tables. | 1. A method, comprising: at a computer comprising a computer program to implement processing operations: receiving data related to content of a target; filtering the data to locate a target term; accessing one or more tables in a repository, the one or more tables comprising entries with a substitution unit corresponding to the target term, the entries arranged according to a prioritized scheme that defines a position for the substitution unit in the tables; and generating an output comprising data that represents the substitution unit to be utilized by a text-to-speech generator to generate spoken content, wherein the position of the substitution unit in the one or more tables is assigned based on a specificity characteristic that describes the relative inclusivity of the substitution unit as compared to other substitution units in the one or more tables. 7. The method of claim 1 , further comprising: selecting a first entry from a first table of the one or more tables; and selecting a second entry from a second table of the one or more tables, wherein the data in the output comprises the substitution unit from the first entry and the second entry. | 0.701403 |
8,190,990 | 21 | 35 | 21. A system for annotating webpage content, the system comprising: a computerized device communicatively coupled with a webpage server under control of a third party and with an annotations repository under control of an entity different from the third party, the computerized device including: a browser configured to perform first operations comprising, the first operations comprising receiving, from a user associated with the computerized device, a request to access a webpage being hosted by the webpage server, where the user is other than both the third party and the entity different from the third party, in response to said receiving from the user the request to access the webpage, requesting the webpage from the webpage server, and receiving a response from the webpage server including a current instance of the webpage, and the browser is further configured to perform second operations, the second operations comprising requesting, from the annotations repository in response to said receiving from the user the request to access the webpage, a collection of annotations made to the webpage by the user associated with the computerized device, the annotations collection being stored at the annotations repository, the annotations collection including one or more annotations relating to corresponding one or more portions of webpage content of the webpage, receiving a response from the annotations repository including the requested annotations collection, and concurrently displaying the current instance of the webpage received with the response from the webpage server and the annotations collection received with the response from the annotations repository, such that the one or more annotations included in the received annotations collection are overlaid on the corresponding one or more portions of the webpage content of the received current instance of the webpage. | 21. A system for annotating webpage content, the system comprising: a computerized device communicatively coupled with a webpage server under control of a third party and with an annotations repository under control of an entity different from the third party, the computerized device including: a browser configured to perform first operations comprising, the first operations comprising receiving, from a user associated with the computerized device, a request to access a webpage being hosted by the webpage server, where the user is other than both the third party and the entity different from the third party, in response to said receiving from the user the request to access the webpage, requesting the webpage from the webpage server, and receiving a response from the webpage server including a current instance of the webpage, and the browser is further configured to perform second operations, the second operations comprising requesting, from the annotations repository in response to said receiving from the user the request to access the webpage, a collection of annotations made to the webpage by the user associated with the computerized device, the annotations collection being stored at the annotations repository, the annotations collection including one or more annotations relating to corresponding one or more portions of webpage content of the webpage, receiving a response from the annotations repository including the requested annotations collection, and concurrently displaying the current instance of the webpage received with the response from the webpage server and the annotations collection received with the response from the annotations repository, such that the one or more annotations included in the received annotations collection are overlaid on the corresponding one or more portions of the webpage content of the received current instance of the webpage. 35. The system of claim 21 , wherein the second operations further comprise receiving, from the user associated with the computerized device, input indicating a portion of the webpage content of the received current instance of the webpage; recording, as part of a new annotation corresponding to the indicated portion of the webpage content, verification information referencing the indicated portion of the webpage content; receiving, from the user associated with the computerized device, input providing supplementary information associated with the indicated portion of the webpage content, the supplementary information including notes and addresses of cross-referenced webpages; recording, as part of the new annotation, the provided supplementary information; and transmitting, to the annotations repository, the new annotation corresponding to the indicated portion of the webpage content to be included in the stored instance of the annotations collection. | 0.716383 |
7,728,839 | 14 | 24 | 14. A computer program product, comprising a computer readable medium storing computer executable code for recognizing and tracking human motion, the computer executable code when executed causing a processor to perform steps of: receiving a plurality of learned motion segments representing different learned motions within a motion class, wherein each learned motion segment comprises a plurality of state vectors and each state vector comprises a time stamp, and wherein one of the learned motion segments comprises temporally contiguous state vectors clustered together in a low-dimensional space based on the time stamps; receiving a representation of human motion having at least one motion from the motion class, the at least one motion comprising a sequence of pose states represented in a high dimensional space; projecting the sequences of pose states from the high dimensional space to the low dimensional space according to a discriminative model that when applied to the sequence of pose states increases the inter-class separability between pose states of different motion classes and decreases the intra-class separability between pose states of a same motion-class; determining an integer P nearest neighbors of a first projected pose state in the low dimensional space, the P nearest neighbors from P different learned motion segments; determining P pose predictions for the P different learned motion segments; and determining the pose prediction that best matches a current frame of the representation of human motion; and storing the determined pose prediction to a memory. | 14. A computer program product, comprising a computer readable medium storing computer executable code for recognizing and tracking human motion, the computer executable code when executed causing a processor to perform steps of: receiving a plurality of learned motion segments representing different learned motions within a motion class, wherein each learned motion segment comprises a plurality of state vectors and each state vector comprises a time stamp, and wherein one of the learned motion segments comprises temporally contiguous state vectors clustered together in a low-dimensional space based on the time stamps; receiving a representation of human motion having at least one motion from the motion class, the at least one motion comprising a sequence of pose states represented in a high dimensional space; projecting the sequences of pose states from the high dimensional space to the low dimensional space according to a discriminative model that when applied to the sequence of pose states increases the inter-class separability between pose states of different motion classes and decreases the intra-class separability between pose states of a same motion-class; determining an integer P nearest neighbors of a first projected pose state in the low dimensional space, the P nearest neighbors from P different learned motion segments; determining P pose predictions for the P different learned motion segments; and determining the pose prediction that best matches a current frame of the representation of human motion; and storing the determined pose prediction to a memory. 24. The computer program product of claim 14 wherein the at least one motion is tracked without background subtraction. | 0.947252 |
9,424,440 | 1 | 3 | 1. A computer-implemented document integrity verification method, executable by a processor, the method comprising: receiving a digital document in a word processing format into a non-transitory computer readable medium; generating a first baseline data sequence from the digital document, the first baseline data sequence having a first printable element and a second printable element following the first printable element of the first baseline data sequence; generating a first modified data sequence from the first baseline data sequence in accordance with a set of modification rules, the first modified data sequence having a first printable element and a second printable element following the first printable element of the first modified data sequence, wherein the first printable element of the first modified data sequence is identical to the first printable element of the first baseline data sequence, wherein the second printable element of the first modified data sequence is identical to the second element of the first baseline data sequence, wherein at least one unprintable element of the first baseline data sequence, between the first and final printable elements of the first baseline data sequence, is not in the first modified data sequence, so that the first modified data sequence is shorter than the first baseline data sequence, and wherein an integrity verification code (IVC) generated for the first modified data sequence will differ from an IVC generated for the first baseline data sequence; generating a first original IVC, wherein generating a first original IVC comprises performing a one-way operation on the first modified data sequence, and wherein the modification rules render tampering of the digital document undetectable for the at least one unprintable element within the first baseline data sequence; generating a second baseline data sequence from the digital document, the second baseline data sequence having a first printable element and a second printable element following the first printable element of the second baseline data sequence; wherein the second baseline data sequence is different than the first baseline data sequence, generating a second modified data sequence from the second baseline data sequence in accordance with the set of modification rules, the second modified data sequence having a first printable element and a second printable element following the first printable element of the second modified data sequence, wherein the first printable element of the second modified data sequence is identical to the first printable element of the second baseline data sequence, wherein the second printable element of the second modified data sequence is identical to the second element of the second baseline data sequence, wherein at least one unprintable element of the second baseline data sequence, between the first and final printable elements of the second baseline data sequence, is not in the second modified data sequence, so that the second modified data sequence is shorter than the second baseline data sequence, and wherein an IVC generated for the second modified data sequence will differ from an IVC generated for the second baseline data sequence; generating a second original IVC, wherein generating a second original IVC comprises performing a one-way operation on the second modified data sequence, and wherein the modification rules render tampering of the digital document undetectable for the at least one unprintable element within the second baseline data sequence; and publishing the digital document with at least a portion of the first original IVC and the second original IVC rendered on a face of the published document. | 1. A computer-implemented document integrity verification method, executable by a processor, the method comprising: receiving a digital document in a word processing format into a non-transitory computer readable medium; generating a first baseline data sequence from the digital document, the first baseline data sequence having a first printable element and a second printable element following the first printable element of the first baseline data sequence; generating a first modified data sequence from the first baseline data sequence in accordance with a set of modification rules, the first modified data sequence having a first printable element and a second printable element following the first printable element of the first modified data sequence, wherein the first printable element of the first modified data sequence is identical to the first printable element of the first baseline data sequence, wherein the second printable element of the first modified data sequence is identical to the second element of the first baseline data sequence, wherein at least one unprintable element of the first baseline data sequence, between the first and final printable elements of the first baseline data sequence, is not in the first modified data sequence, so that the first modified data sequence is shorter than the first baseline data sequence, and wherein an integrity verification code (IVC) generated for the first modified data sequence will differ from an IVC generated for the first baseline data sequence; generating a first original IVC, wherein generating a first original IVC comprises performing a one-way operation on the first modified data sequence, and wherein the modification rules render tampering of the digital document undetectable for the at least one unprintable element within the first baseline data sequence; generating a second baseline data sequence from the digital document, the second baseline data sequence having a first printable element and a second printable element following the first printable element of the second baseline data sequence; wherein the second baseline data sequence is different than the first baseline data sequence, generating a second modified data sequence from the second baseline data sequence in accordance with the set of modification rules, the second modified data sequence having a first printable element and a second printable element following the first printable element of the second modified data sequence, wherein the first printable element of the second modified data sequence is identical to the first printable element of the second baseline data sequence, wherein the second printable element of the second modified data sequence is identical to the second element of the second baseline data sequence, wherein at least one unprintable element of the second baseline data sequence, between the first and final printable elements of the second baseline data sequence, is not in the second modified data sequence, so that the second modified data sequence is shorter than the second baseline data sequence, and wherein an IVC generated for the second modified data sequence will differ from an IVC generated for the second baseline data sequence; generating a second original IVC, wherein generating a second original IVC comprises performing a one-way operation on the second modified data sequence, and wherein the modification rules render tampering of the digital document undetectable for the at least one unprintable element within the second baseline data sequence; and publishing the digital document with at least a portion of the first original IVC and the second original IVC rendered on a face of the published document. 3. The method of claim 1 wherein the second baseline data sequence is a subset, less than all, of the first baseline data sequence. | 0.971731 |
7,644,360 | 32 | 37 | 32. A computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series; wherein the claims are parsed hierarchically wherein the diagram comprises graphical claim structure and textual claim content associated with each patent claim and wherein, for each patent claim, the graphical claim structure fully includes the textual claim content, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. | 32. A computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series; wherein the claims are parsed hierarchically wherein the diagram comprises graphical claim structure and textual claim content associated with each patent claim and wherein, for each patent claim, the graphical claim structure fully includes the textual claim content, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. 37. The computer readable medium having instructions for causing a computer to create an interactive GUI of claim 32 , wherein the imported claims are an entire claims series. | 0.885171 |
7,908,281 | 1 | 8 | 1. A method comprising: receiving, with a context assembly device, a request to assemble a pedigree that describes a history of origin of a primary resource, wherein the requested pedigree of the primary resource represents the history as a set of statements that describe relationships between the primary resource and a plurality of other resources from which an asserted fact of the primary resource was derived; submitting, from the context assembly device to a set of one or more pedigree management servers, a first query for a first set of pedigree fragments that each include one or more statements that specify direct relationships between the primary resource and a first set of resources, wherein the direct relationships indicate that the asserted fact of the primary resource was derived from data of the first set of the resources; receiving, in response to the first query, a first set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the primary resource and the first set of resources; submitting, with the context assembly device to the pedigree management servers, a second query for a second set of pedigree fragments that include one or more statements that specify direct relationships between the first set of resources and a second set of resources, wherein the direct relationships of the second set of pedigree fragments indicate that the data of the first set of resources was derived from data of the second set of the resources; receiving, in response to the second query, the second set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the first set of resources and the second set of resources; and assembling, with the context assembly device, the pedigree of the primary resource from the statements of the first set of pedigree fragments and the second set of pedigree fragments received from the pedigree management servers. | 1. A method comprising: receiving, with a context assembly device, a request to assemble a pedigree that describes a history of origin of a primary resource, wherein the requested pedigree of the primary resource represents the history as a set of statements that describe relationships between the primary resource and a plurality of other resources from which an asserted fact of the primary resource was derived; submitting, from the context assembly device to a set of one or more pedigree management servers, a first query for a first set of pedigree fragments that each include one or more statements that specify direct relationships between the primary resource and a first set of resources, wherein the direct relationships indicate that the asserted fact of the primary resource was derived from data of the first set of the resources; receiving, in response to the first query, a first set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the primary resource and the first set of resources; submitting, with the context assembly device to the pedigree management servers, a second query for a second set of pedigree fragments that include one or more statements that specify direct relationships between the first set of resources and a second set of resources, wherein the direct relationships of the second set of pedigree fragments indicate that the data of the first set of resources was derived from data of the second set of the resources; receiving, in response to the second query, the second set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the first set of resources and the second set of resources; and assembling, with the context assembly device, the pedigree of the primary resource from the statements of the first set of pedigree fragments and the second set of pedigree fragments received from the pedigree management servers. 8. The method of claim 1 , wherein identifying statements in the set of statements comprises applying a second-stage query to the statements in the set of pedigree fragments in order to identify the statements in the set of statements. | 0.738889 |
6,120,297 | 1 | 4 | 1. A method of guiding a student's acquisition of additional terminology for use in the student's vocabulary through the use of structured inductive reasoning, said method comprising the steps of: displaying information indicating the derivation of a current target word to be added to the student's vocabulary; displaying a clue that relates to the information indicating the derivation of the current target word and does not use the current target word, said clue offering answers for selection by the student; displaying a clue that relates to and does use the current target word, said clue offering answers for selection by the student; displaying the student's selected answer and asking the student to try again, if the answer selected by the student for a given clue was incorrect; displaying the correct answer to the clue and an explanation of that answer, if the answer selected by the student for a given clue was correct; and displaying the correct answer to the clue and an explanation of that answer after a given number of incorrect answers have been selected by the student for a given clue. | 1. A method of guiding a student's acquisition of additional terminology for use in the student's vocabulary through the use of structured inductive reasoning, said method comprising the steps of: displaying information indicating the derivation of a current target word to be added to the student's vocabulary; displaying a clue that relates to the information indicating the derivation of the current target word and does not use the current target word, said clue offering answers for selection by the student; displaying a clue that relates to and does use the current target word, said clue offering answers for selection by the student; displaying the student's selected answer and asking the student to try again, if the answer selected by the student for a given clue was incorrect; displaying the correct answer to the clue and an explanation of that answer, if the answer selected by the student for a given clue was correct; and displaying the correct answer to the clue and an explanation of that answer after a given number of incorrect answers have been selected by the student for a given clue. 4. The method of claim 1, said method further comprising the steps of: displaying the current target word, its pronunciation and part of speech, as a part of each clue displayed, and providing the student access to a display of the derivation information as a part of each clue displayed. | 0.856431 |
9,767,114 | 14 | 15 | 14. The storage medium of claim 13 , wherein providing the content item to the target entity involves: providing, to the local user, a dissemination plan that indicates one or more target entities; receiving a response from the local user to the dissemination plan; and responsive to determining from the response that the local user accepts the dissemination plan, providing the content item to the target entities. | 14. The storage medium of claim 13 , wherein providing the content item to the target entity involves: providing, to the local user, a dissemination plan that indicates one or more target entities; receiving a response from the local user to the dissemination plan; and responsive to determining from the response that the local user accepts the dissemination plan, providing the content item to the target entities. 15. The storage medium of claim 14 , wherein the response indicates one or more of: a target entity to remove from the dissemination plan; a target entity to add to the dissemination plan; a security policy for a target entity of the dissemination plan; a privacy policy for a target entity of the dissemination plan; and a user-confirmation indicating that the local user accepts the dissemination plan. | 0.780673 |
4,739,398 | 3 | 11 | 3. The method of claim 1 wherein each of said segments has an audio portion and a video portion and said signatures and parametized signals are derived from both the audio and video portions of said segments and said monitored signals. | 3. The method of claim 1 wherein each of said segments has an audio portion and a video portion and said signatures and parametized signals are derived from both the audio and video portions of said segments and said monitored signals. 11. The method of claim 3 wherein said signatures and said parametized signals are derived at least in part from the frequency spectrum of said audio portion. | 0.976111 |
8,316,097 | 1 | 6 | 1. A computer network-based messaging system including a multiple-layer chat filtering system for controlling the content of messages sent by users in the messaging system, the messaging system comprising: a user computer that receives a message, the message including a plurality of words entered by a sender; one or more data storage devices including: a word database including a plurality of permitted words which are allowed to be transmitted, and a phrase database including a plurality of prohibited phrases which are not allowed to be transmitted, at least one of the plurality of prohibited phrases consisting of a plurality of individual words that are each included in the word database, wherein said phrase database is not part of the user computer in the computer network and said user computer is operative to send information addressed to a messaging server system that is remote from the user computer, and said user computer receives an indication from the phrase database of whether said information includes the prohibited phrases; and a message sending part that transmits the message over a computer network only if all of the plurality of words entered by the sender are contained in the word database and none of the plurality of prohibited phrases are contained in the message, wherein the user computer provides a display of the message to the sender prior to the message sending part transmitting the message, and wherein the display highlights words included in the message that must be removed before the message sending part will transmit the message over the computer network. | 1. A computer network-based messaging system including a multiple-layer chat filtering system for controlling the content of messages sent by users in the messaging system, the messaging system comprising: a user computer that receives a message, the message including a plurality of words entered by a sender; one or more data storage devices including: a word database including a plurality of permitted words which are allowed to be transmitted, and a phrase database including a plurality of prohibited phrases which are not allowed to be transmitted, at least one of the plurality of prohibited phrases consisting of a plurality of individual words that are each included in the word database, wherein said phrase database is not part of the user computer in the computer network and said user computer is operative to send information addressed to a messaging server system that is remote from the user computer, and said user computer receives an indication from the phrase database of whether said information includes the prohibited phrases; and a message sending part that transmits the message over a computer network only if all of the plurality of words entered by the sender are contained in the word database and none of the plurality of prohibited phrases are contained in the message, wherein the user computer provides a display of the message to the sender prior to the message sending part transmitting the message, and wherein the display highlights words included in the message that must be removed before the message sending part will transmit the message over the computer network. 6. The messaging system of claim 1 , wherein the user computer includes a send button for requesting the message sending part to transmit the message, and wherein the user computer permits the sender to trigger the send button and does not inform the sender if the message sending part does not transmit the message. | 0.786198 |
8,214,354 | 29 | 32 | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. 32. The apparatus set forth in claim 29 wherein: when a term in the constrained object is no longer contained in the different set of terms, the apparatus that alters one or more values sets the one or more terms to a null value. | 0.708651 |
9,727,610 | 8 | 11 | 8. A non-transitory computer-readable storage medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for tuning access middleware that provides an application with one or more connections to a database, the process comprising: receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; querying the user, based on the first response received from the user, regarding whether the application connected via the access middleware to the database supports a functionality specified in the query; receiving a second response from the user specifying whether the application connected via the access middleware to the database supports the functionality specified in the query; querying the user, based on the first and second responses, regarding one or more user preferences associated with application performance; receiving a third response from the user specifying one or more user preferences associated with performance; generating, based on the first response received from the user, the second response received from the user specifying whether the application supports the functionality and the third response from the user specifying one or more user preferences associated with performance, a set of connection options and values configured to achieve optimal performance of the driver/provider; and providing the set of connection options and values to the user. | 8. A non-transitory computer-readable storage medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for tuning access middleware that provides an application with one or more connections to a database, the process comprising: receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; querying the user, based on the first response received from the user, regarding whether the application connected via the access middleware to the database supports a functionality specified in the query; receiving a second response from the user specifying whether the application connected via the access middleware to the database supports the functionality specified in the query; querying the user, based on the first and second responses, regarding one or more user preferences associated with application performance; receiving a third response from the user specifying one or more user preferences associated with performance; generating, based on the first response received from the user, the second response received from the user specifying whether the application supports the functionality and the third response from the user specifying one or more user preferences associated with performance, a set of connection options and values configured to achieve optimal performance of the driver/provider; and providing the set of connection options and values to the user. 11. The computer-readable storage medium of claim 8 , the process comprising indicating progress of the tuning process. | 0.887736 |
10,135,910 | 6 | 8 | 6. A system comprising: at least one processor; at least one memory device; at least one module stored by the at least one memory device and executable by the at least one processor, wherein the at least one module is configured to perform operations comprising: rendering, by an application executing on a target platform, a document that specifies one or more widgets of each of a first widget type and a second widget type, the rendering including: in response to determining, by the application, that the application includes a first native widget renderer for rendering the one or more widgets of the first widget type, wherein the first native widget renderer is written using an application program interface (API) that is native to the target platform, rendering the one or more widgets of the first widget type by the first native widget renderer for first widget type, and in response to determining, by the application, that the application does not include a second native widget renderer for rendering the one or more widgets of the second widget type, wherein the second native widget renderer is written using the API that is native to the target platform, rendering the one or more widgets of the second widget type by a default widget renderer for the second widget type, wherein the default widget renderer is written using cross-platform code for a plurality of target platforms including the target platform. | 6. A system comprising: at least one processor; at least one memory device; at least one module stored by the at least one memory device and executable by the at least one processor, wherein the at least one module is configured to perform operations comprising: rendering, by an application executing on a target platform, a document that specifies one or more widgets of each of a first widget type and a second widget type, the rendering including: in response to determining, by the application, that the application includes a first native widget renderer for rendering the one or more widgets of the first widget type, wherein the first native widget renderer is written using an application program interface (API) that is native to the target platform, rendering the one or more widgets of the first widget type by the first native widget renderer for first widget type, and in response to determining, by the application, that the application does not include a second native widget renderer for rendering the one or more widgets of the second widget type, wherein the second native widget renderer is written using the API that is native to the target platform, rendering the one or more widgets of the second widget type by a default widget renderer for the second widget type, wherein the default widget renderer is written using cross-platform code for a plurality of target platforms including the target platform. 8. The system of claim 6 , wherein the at least one module is configured to perform operations comprising: downloading, by the application, the default widget renderer for rendering the second widget type from a network location specified by the document. | 0.663588 |
7,792,353 | 1 | 2 | 1. A method of machine learning, comprising: (a) obtaining a training set that includes training samples and corresponding assigned classification labels; (b) training an automated classifier against the training set; (c) selecting at least one of the training samples; (d) requesting confirmation/re-labeling of said at least one training sample; (e) in response to step (d), receiving a reply classification label for said at least one training sample; (f) retraining the automated classifier using the reply classification label; and, predicting a label for said at least one training sample, wherein said at least one training sample is selected in step (c) based on a comparison between the assigned classification label and the predicted label for said at least one training sample. | 1. A method of machine learning, comprising: (a) obtaining a training set that includes training samples and corresponding assigned classification labels; (b) training an automated classifier against the training set; (c) selecting at least one of the training samples; (d) requesting confirmation/re-labeling of said at least one training sample; (e) in response to step (d), receiving a reply classification label for said at least one training sample; (f) retraining the automated classifier using the reply classification label; and, predicting a label for said at least one training sample, wherein said at least one training sample is selected in step (c) based on a comparison between the assigned classification label and the predicted label for said at least one training sample. 2. A method according to claim 1 , wherein said at least one training sample is selected in step (c) after considering for possible selection a group of samples that includes a plurality of the training samples and a plurality of unlabeled samples. | 0.810398 |
7,617,178 | 7 | 12 | 7. A peer-to-peer file sharing client for moving a file from background file sharing to foreground file sharing and preventing duplicate downloads in a peer-to-peer file sharing network, the peer-to-peer file sharing client comprising: a processor; and a memory, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive at least one file fragment of a file from a background swarm for background file sharing; responsive to a user-generated request to move the file from background file sharing to foreground file sharing, identify the at least one file fragment stored locally; and request at least one remaining file fragment from the background swarm, wherein the background swarm becomes a foreground swarm, wherein requesting at least one remaining file fragment from the background swarm comprises sending a request to a tracker for a peer list. | 7. A peer-to-peer file sharing client for moving a file from background file sharing to foreground file sharing and preventing duplicate downloads in a peer-to-peer file sharing network, the peer-to-peer file sharing client comprising: a processor; and a memory, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive at least one file fragment of a file from a background swarm for background file sharing; responsive to a user-generated request to move the file from background file sharing to foreground file sharing, identify the at least one file fragment stored locally; and request at least one remaining file fragment from the background swarm, wherein the background swarm becomes a foreground swarm, wherein requesting at least one remaining file fragment from the background swarm comprises sending a request to a tracker for a peer list. 12. The peer-to-peer file sharing client of claim 7 , wherein requesting at least one remaining file fragment from the background swarm further comprises exchanging messages with peers to request, respond, and exchange data for the at least one remaining file fragment. | 0.624302 |
8,352,485 | 7 | 11 | 7. A computer system, comprising: one or more processors; a display; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: while a document displayed on the display is being browsed: displaying a first portion of the document on the display; receiving a user-specified text string that includes multiple search keywords; and upon receiving the user-specified text string that includes multiple search keywords: comparing the multiple search keywords with a plurality of candidate chunks within the document, wherein each candidate chunk corresponds to a predefined semantically-based unit of text in the document; identifying, among the plurality of candidate chunks, one or more chunks matching the multiple search keywords; and displaying, in addition to the first portion of the document, a list of the one or more chunks matching the search keywords in the document on the display, wherein terms in a respective chunk that satisfy the search keywords are either ordered differently from the search keywords in the user-specified text string or separated from one another by at least one term that does not satisfy any of the search keywords. | 7. A computer system, comprising: one or more processors; a display; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: while a document displayed on the display is being browsed: displaying a first portion of the document on the display; receiving a user-specified text string that includes multiple search keywords; and upon receiving the user-specified text string that includes multiple search keywords: comparing the multiple search keywords with a plurality of candidate chunks within the document, wherein each candidate chunk corresponds to a predefined semantically-based unit of text in the document; identifying, among the plurality of candidate chunks, one or more chunks matching the multiple search keywords; and displaying, in addition to the first portion of the document, a list of the one or more chunks matching the search keywords in the document on the display, wherein terms in a respective chunk that satisfy the search keywords are either ordered differently from the search keywords in the user-specified text string or separated from one another by at least one term that does not satisfy any of the search keywords. 11. The computer system of claim 7 , wherein the first chunk is not located within the first portion of the document. | 0.877101 |
8,001,140 | 1 | 7 | 1. A computer-implemented method, comprising: at a computer having memory, a display, and one or more processors, receiving a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determining an archetype for the search keyword; identifying a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; applying the identified query operator to a document; identifying a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and returning the chunk for display to the user. | 1. A computer-implemented method, comprising: at a computer having memory, a display, and one or more processors, receiving a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determining an archetype for the search keyword; identifying a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; applying the identified query operator to a document; identifying a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and returning the chunk for display to the user. 7. The method of claim 1 , further comprising: before applying the identified query operator, receiving one or more user instructions in connection with the archetype; and updating the identified query operator in accordance with the user instructions. | 0.752456 |
9,501,264 | 1 | 3 | 1. A system, including a mobile device, including a processor and memory maintaining instructions, the instructions being interpretable by the processor to present display elements having a first human-language meaning to a user of the mobile device; a development device, including a development environment suitable to create an app by a designer or programmer, the app including at least some of the instructions, and suitable to distribute the app to the mobile device, the app including at least some of the instructions interpretable by the processor to present the display elements in a form having a second human-language meaning to the user; the mobile device including a communication link responsive to one or more signals delivering the app to the mobile device, the communication link being responsive to the user and suitable to present messages regarding the second human-language meaning from the user to the designer or programmer, the messages including a relation between the second human-language meaning and the first human-language meaning; the app including communication link being responsive to the user to send information to the developer or programmer; the app including a first mode in which it performs a first designated function; instructions executable or interpretable by the processor to receive a signal from the user when performing the first designated function, the signal directing the app to enter a state in which it performs a second designated function; the second designated function including a user interface in which the app receives input from the user and communicates that input to the developer or programmer. | 1. A system, including a mobile device, including a processor and memory maintaining instructions, the instructions being interpretable by the processor to present display elements having a first human-language meaning to a user of the mobile device; a development device, including a development environment suitable to create an app by a designer or programmer, the app including at least some of the instructions, and suitable to distribute the app to the mobile device, the app including at least some of the instructions interpretable by the processor to present the display elements in a form having a second human-language meaning to the user; the mobile device including a communication link responsive to one or more signals delivering the app to the mobile device, the communication link being responsive to the user and suitable to present messages regarding the second human-language meaning from the user to the designer or programmer, the messages including a relation between the second human-language meaning and the first human-language meaning; the app including communication link being responsive to the user to send information to the developer or programmer; the app including a first mode in which it performs a first designated function; instructions executable or interpretable by the processor to receive a signal from the user when performing the first designated function, the signal directing the app to enter a state in which it performs a second designated function; the second designated function including a user interface in which the app receives input from the user and communicates that input to the developer or programmer. 3. A system as in claim 1 , wherein the development device, in response to the messages, packages at least some information from the messages in a pre-determined initialization data structure. | 0.814313 |
7,827,100 | 18 | 27 | 18. A method for estimating a propensity to pay an owed amount to a revenue agency, the method comprising: assigning to each score band of a plurality of score bands of a collections model a different scoring expression specially determined for the score band, wherein each said score band corresponds to a different credit score range; obtaining a first credit score for a first debtor; selecting, based on the first credit score, a first score band from the plurality of score bands; and in response to the selecting, applying the scoring expression assigned to the first score band to first raw credit data and first tax form data to determine a first collection score for the first debtor, wherein said first raw credit data and first tax form data are operable to be stored in computer memory. | 18. A method for estimating a propensity to pay an owed amount to a revenue agency, the method comprising: assigning to each score band of a plurality of score bands of a collections model a different scoring expression specially determined for the score band, wherein each said score band corresponds to a different credit score range; obtaining a first credit score for a first debtor; selecting, based on the first credit score, a first score band from the plurality of score bands; and in response to the selecting, applying the scoring expression assigned to the first score band to first raw credit data and first tax form data to determine a first collection score for the first debtor, wherein said first raw credit data and first tax form data are operable to be stored in computer memory. 27. The method of claim 18 , further comprising; configuring the plurality of score bands from historical tax data; and creating a segment model for each said score band of the plurality of score bands. | 0.717087 |
8,103,962 | 4 | 5 | 4. The method of claim 3 , further comprising determining context of a node or set of nodes identified by the Xpath pointing to the user selected data items and wherein extracting comprises using the context to determine the extracted data items. | 4. The method of claim 3 , further comprising determining context of a node or set of nodes identified by the Xpath pointing to the user selected data items and wherein extracting comprises using the context to determine the extracted data items. 5. The method of claim 4 , wherein the context of a node or set of nodes comprises at least one of a symbol or measurement unit. | 0.946309 |
8,175,875 | 10 | 16 | 10. A system for processing documents, comprising: one or more processors; memory; and one or more modules, wherein the modules are stored within memory and configured to be executed by the one or more processors, the one or more modules including instructions to: group a set of documents into a plurality of clusters, the set of documents comprising a sequence of tokens, wherein each cluster includes one or more documents in the set of documents; generate a compressed representation of the set of documents from which respective documents in the set can be reconstructed, including instructions to generate, for the plurality of clusters, a compressed sequence of tokens by eliding duplicate sequences of tokens within respective clusters; and generate an index of the compressed sequence of tokens, including instructions to index each respective token in the compressed sequence of tokens based on a respective token position of the respective token in the compressed sequence. | 10. A system for processing documents, comprising: one or more processors; memory; and one or more modules, wherein the modules are stored within memory and configured to be executed by the one or more processors, the one or more modules including instructions to: group a set of documents into a plurality of clusters, the set of documents comprising a sequence of tokens, wherein each cluster includes one or more documents in the set of documents; generate a compressed representation of the set of documents from which respective documents in the set can be reconstructed, including instructions to generate, for the plurality of clusters, a compressed sequence of tokens by eliding duplicate sequences of tokens within respective clusters; and generate an index of the compressed sequence of tokens, including instructions to index each respective token in the compressed sequence of tokens based on a respective token position of the respective token in the compressed sequence. 16. The system of claim 10 , the one or more modules further comprising instructions for generating a token position mapping between corresponding tokens in the sequence of tokens and the compressed sequence of token. | 0.82967 |
7,735,073 | 26 | 39 | 26. A method of data profiling code, the method comprising: associating a source-level data object language construct for a source-level data object by tagging an instruction instance stored in at least one computer readable storage medium that may consume execution time based on loading of data utilizing at least one processing unit, with identifiers that describe the instruction instance with a source-level data object language construct; and attributing a sampled runtime event to the source-level data object language construct describing units of data identifiable in source code utilizing the at least one processing unit, wherein the attributing is based at least in part on the association between the instruction instance in executable code and the source-level data object language construct corresponding thereto. | 26. A method of data profiling code, the method comprising: associating a source-level data object language construct for a source-level data object by tagging an instruction instance stored in at least one computer readable storage medium that may consume execution time based on loading of data utilizing at least one processing unit, with identifiers that describe the instruction instance with a source-level data object language construct; and attributing a sampled runtime event to the source-level data object language construct describing units of data identifiable in source code utilizing the at least one processing unit, wherein the attributing is based at least in part on the association between the instruction instance in executable code and the source-level data object language construct corresponding thereto. 39. The method of claim 26 further comprising aggregating profile data for the code based at least in part on the language construct utilizing the at least one processing unit. | 0.888748 |
9,058,335 | 15 | 20 | 15. A method for protecting derived metadata in a computerized search system, the method comprising: parsing and analyzing an indexing request associated with an object, the indexing request being received at a search engine embodied on a non-transitory computer-readable memory and communicatively connected to a client device over a network connection; identifying any derived metadata fields in a search index that would be affected by the indexing request; determining whether any of the identified derived metadata fields in the search index that would be affected by the indexing request are within a list or record of protected metadata fields that are to be protected from change; and executing an indexing command to update the search index with data associated with the object without erasing or modifying values of the derived metadata fields in the search index that have been identified as would be affected by the indexing request and that have been determined to be associated with the list or record of protected metadata fields, the data comprising text, metadata, or both. | 15. A method for protecting derived metadata in a computerized search system, the method comprising: parsing and analyzing an indexing request associated with an object, the indexing request being received at a search engine embodied on a non-transitory computer-readable memory and communicatively connected to a client device over a network connection; identifying any derived metadata fields in a search index that would be affected by the indexing request; determining whether any of the identified derived metadata fields in the search index that would be affected by the indexing request are within a list or record of protected metadata fields that are to be protected from change; and executing an indexing command to update the search index with data associated with the object without erasing or modifying values of the derived metadata fields in the search index that have been identified as would be affected by the indexing request and that have been determined to be associated with the list or record of protected metadata fields, the data comprising text, metadata, or both. 20. The method of claim 15 , wherein the determining comprises pattern matching. | 0.906977 |
10,102,243 | 8 | 10 | 8. A system, comprising: a processor coupled to a memory, the processor configured to execute computer-executable instructions stored in the memory that when executed, perform the following acts: receive a data analysis expression comprising a calculation and a relationship, from multiple relationships between data of two tables of a database, to employ with respect to the calculation; override a default relationship of the database with the relationship by setting the default relationship as active and other relationships of the multiple relationships as inactive; retrieve data from the two tables for the calculation based on the active relationship, wherein the active relationship enables acquisition of data based on a particular column of matching data in the two tables; initiate execution of the calculation on the data, wherein execution of the calculation comprises evaluating an expression specified by the calculation on the data retrieved from the two tables; restore the default relationship after execution of the calculation is complete by setting the default relationship as active and other relationships of the multiple relationships as inactive; and return a result of execution of the calculation. | 8. A system, comprising: a processor coupled to a memory, the processor configured to execute computer-executable instructions stored in the memory that when executed, perform the following acts: receive a data analysis expression comprising a calculation and a relationship, from multiple relationships between data of two tables of a database, to employ with respect to the calculation; override a default relationship of the database with the relationship by setting the default relationship as active and other relationships of the multiple relationships as inactive; retrieve data from the two tables for the calculation based on the active relationship, wherein the active relationship enables acquisition of data based on a particular column of matching data in the two tables; initiate execution of the calculation on the data, wherein execution of the calculation comprises evaluating an expression specified by the calculation on the data retrieved from the two tables; restore the default relationship after execution of the calculation is complete by setting the default relationship as active and other relationships of the multiple relationships as inactive; and return a result of execution of the calculation. 10. The system of claim 8 , the multiple relationships are assigned weighted priorities and an ambiguity is resolved based on the weighted priorities. | 0.772727 |
6,092,034 | 32 | 33 | 32. The method of claim 19, wherein the method is trained on a sentence-aligned training text including a plurality of sentences in the source language and a plurality of sentences in the target language, wherein each sentence in the plurality of source language sentences is a translation of a corresponding sentence in the plurality of target language sentences, and a training portion of the method comprises: determining an alignment between the words of each of the plurality of source language sentences and the corresponding target language sentence; accumulating fertility-context events from the alignments for at least some occurrence of the source word in a source language sentence, each fertility-context event including a number of target language words that the source language word is aligned to, the source language word, and the context of the source-language word; accumulating sense-context events from the alignments for at least some occurrence of the source word in a source language sentence, each sense-context event including the target word, the source-language word to which the target language word is aligned, and the context of the source-language word; and wherein the probability of the fertility of the source word and the probability of the target are determined using the accumulated fertility-context and sense-context events, respectively. | 32. The method of claim 19, wherein the method is trained on a sentence-aligned training text including a plurality of sentences in the source language and a plurality of sentences in the target language, wherein each sentence in the plurality of source language sentences is a translation of a corresponding sentence in the plurality of target language sentences, and a training portion of the method comprises: determining an alignment between the words of each of the plurality of source language sentences and the corresponding target language sentence; accumulating fertility-context events from the alignments for at least some occurrence of the source word in a source language sentence, each fertility-context event including a number of target language words that the source language word is aligned to, the source language word, and the context of the source-language word; accumulating sense-context events from the alignments for at least some occurrence of the source word in a source language sentence, each sense-context event including the target word, the source-language word to which the target language word is aligned, and the context of the source-language word; and wherein the probability of the fertility of the source word and the probability of the target are determined using the accumulated fertility-context and sense-context events, respectively. 33. The method of claim 32, further comprising the step of implementing a confidence measure to exclude unreliable fertility-context and sense-context events from being accumulated. | 0.94085 |
6,058,435 | 1 | 5 | 1. A routing method for distributing communications to a plurality of individuals comprising steps of: storing resume data indicative of proficiencies of said individuals with respect to skills advantageous to processing said communications; enabling reception of incoming communications having substantial content freedom; formatting original message content of each of said incoming communications in a program-searchable format; searching said original message content of each formatted incoming communications to determine which skills are advantageous to processing said incoming communications; and at least partially based upon correlations between said stored resume data and said determined skills advantageous to processing said incoming communications, routing said incoming communications to said individuals on a one-by-one basis. | 1. A routing method for distributing communications to a plurality of individuals comprising steps of: storing resume data indicative of proficiencies of said individuals with respect to skills advantageous to processing said communications; enabling reception of incoming communications having substantial content freedom; formatting original message content of each of said incoming communications in a program-searchable format; searching said original message content of each formatted incoming communications to determine which skills are advantageous to processing said incoming communications; and at least partially based upon correlations between said stored resume data and said determined skills advantageous to processing said incoming communications, routing said incoming communications to said individuals on a one-by-one basis. 5. The routing method of claim 1 further comprising a step of receiving said incoming communications in a form of telephonically recorded voice messages, said step of formatting original message content of said incoming communications including generating computer-generated text information representative of said voice messages. | 0.542936 |
9,737,813 | 1 | 2 | 1. A method for training a semantic ability of a subject, the method being performed by a computer, the method comprising: a. displaying a linguistic task to a subject on a display of the computer, said linguistic task comprising providing one or more words, wherein said linguistic task is directed to training the subject in a specific semantic skill or skills; b. providing a plurality of linguistic clues to the subject, through the display of the computer, said plurality of linguistic clues comprising content capable of activating concepts related to said one or more words but wherein said content does not include said one or more words or synonyms thereof, wherein said linguistic clues are selected such that the subject integrates said plurality of linguistic clues to solve said linguistic task, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof; c. receiving a solution to said linguistic task by the subject through the computer; and d. when said solution is not correct, providing one or more additional linguistic clues to the subject, said one or more additional linguistic clues comprising content capable of activating concepts related to said one or more words, wherein the subject integrates said one or more additional linguistic clues with said plurality of linguistic clues to solve said linguistic task, and wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text; wherein said plurality of clues is revealed sequentially according to a requirement for integration of said plurality of linguistic clues by the subject; wherein each clue is revealed separately, such that only one clue is revealed at a given time; wherein said providing said linguistic clues to the subject further comprises penalizing the subject when the subject requests display of a previously displayed clue. | 1. A method for training a semantic ability of a subject, the method being performed by a computer, the method comprising: a. displaying a linguistic task to a subject on a display of the computer, said linguistic task comprising providing one or more words, wherein said linguistic task is directed to training the subject in a specific semantic skill or skills; b. providing a plurality of linguistic clues to the subject, through the display of the computer, said plurality of linguistic clues comprising content capable of activating concepts related to said one or more words but wherein said content does not include said one or more words or synonyms thereof, wherein said linguistic clues are selected such that the subject integrates said plurality of linguistic clues to solve said linguistic task, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof; c. receiving a solution to said linguistic task by the subject through the computer; and d. when said solution is not correct, providing one or more additional linguistic clues to the subject, said one or more additional linguistic clues comprising content capable of activating concepts related to said one or more words, wherein the subject integrates said one or more additional linguistic clues with said plurality of linguistic clues to solve said linguistic task, and wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text; wherein said plurality of clues is revealed sequentially according to a requirement for integration of said plurality of linguistic clues by the subject; wherein each clue is revealed separately, such that only one clue is revealed at a given time; wherein said providing said linguistic clues to the subject further comprises penalizing the subject when the subject requests display of a previously displayed clue. 2. The method of claim 1 , wherein said providing one or more words by the subject comprises at least one of entering said one or more words to the computer and identifying said one or more words by the subject. | 0.793945 |
10,003,688 | 1 | 2 | 1. A method of authenticating a telephone caller, the method comprising: receiving, by a processor of an authentication server, audio data including speech of the telephone caller; analyzing, by the processor, the audio data to identify a plurality of words from the speech of the telephone caller and to identify an occurrence frequency for each of the plurality of words; comparing, by the processor, the plurality of words and the occurrence frequencies to a plurality of word clusters, each word cluster comprising a plurality of associated words and an occurrence frequency for each of the plurality of associated words, and each word cluster being associated with one of a plurality of demographics; determining, by the processor, a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the plurality of words and the plurality of associated words of the most similar cluster and a similarity of the occurrence frequencies of the plurality of words and the occurrence frequencies of the plurality of associated words of the most similar cluster; receiving, by the processor, a purported identity of the telephone caller, the purported identity including caller demographic data; comparing, by the processor, the caller demographic data to the demographic associated with the most similar word cluster; and identifying, by the processor, the telephone caller as at least one of: likely having the purported identity in response to determining the caller demographic data matches the demographic associated with the most similar word cluster, and unlikely to have the purported identity in response to determining the caller demographic data matches a demographic associated with a word cluster different from the most similar word cluster. | 1. A method of authenticating a telephone caller, the method comprising: receiving, by a processor of an authentication server, audio data including speech of the telephone caller; analyzing, by the processor, the audio data to identify a plurality of words from the speech of the telephone caller and to identify an occurrence frequency for each of the plurality of words; comparing, by the processor, the plurality of words and the occurrence frequencies to a plurality of word clusters, each word cluster comprising a plurality of associated words and an occurrence frequency for each of the plurality of associated words, and each word cluster being associated with one of a plurality of demographics; determining, by the processor, a most similar word cluster of the plurality of word clusters to the audio data based on a similarity of the plurality of words and the plurality of associated words of the most similar cluster and a similarity of the occurrence frequencies of the plurality of words and the occurrence frequencies of the plurality of associated words of the most similar cluster; receiving, by the processor, a purported identity of the telephone caller, the purported identity including caller demographic data; comparing, by the processor, the caller demographic data to the demographic associated with the most similar word cluster; and identifying, by the processor, the telephone caller as at least one of: likely having the purported identity in response to determining the caller demographic data matches the demographic associated with the most similar word cluster, and unlikely to have the purported identity in response to determining the caller demographic data matches a demographic associated with a word cluster different from the most similar word cluster. 2. The method of claim 1 , further comprising: analyzing, by the processor, the audio data to identify at least one acoustic characteristic of the speech of the telephone caller; and comparing, by the processor, the at least one acoustic characteristic of the speech of the telephone caller to the plurality of word clusters, each word cluster further comprising at least one associated acoustic characteristic; wherein the determining, by the processor, the most similar word cluster of the plurality of word clusters to the audio data is further based on a similarity of the at least one acoustic characteristic of the speech of the telephone caller and the at least one associated acoustic characteristic of the most similar cluster. | 0.758213 |
9,779,081 | 1 | 8 | 1. A system for feature completion for machine learning, comprising: one or more processing devices that: store a first set of data items, wherein each data item includes a text stream of words; provide a dictionary, wherein the dictionary includes a list of words that define a concept usable as an input feature for training a machine-learning model to score data items with a probability of being a positive example or a negative example of a particular class of data item; provide a feature that is trained to calculate a first probability of a presence, within a stream of one or more words, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; utilize the feature to determine the first probability of the presence, within a stream of one or more words, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary at a given word position in the data item; provide a machine-learning model that is trainable to calculate a second probability of the presence, within the stream of one or more words at the given word position, of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary, based on one or more words in the data item not utilized by the feature to determine the first probability; utilize the machine-learning model to determine the second probability of the presence, within the stream of one or more words at the given word position, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary, based on the one or more words in the data item not utilized by the feature to determine the first probability; determine an actual presence or absence, at the given word position, of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; and modify the machine-learning model to adjust the second probability in a positive or negative direction based on the determined actual presence or absence of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; wherein the feature determines one or more of: whether any words from a given list appear at the center of a window of text around the given word position in which center words in the window of text have been removed, a presence or absence of a verb in the window, a presence or absence of a noun followed by an adjective, or a number of occurrences of a given word in the window. | 1. A system for feature completion for machine learning, comprising: one or more processing devices that: store a first set of data items, wherein each data item includes a text stream of words; provide a dictionary, wherein the dictionary includes a list of words that define a concept usable as an input feature for training a machine-learning model to score data items with a probability of being a positive example or a negative example of a particular class of data item; provide a feature that is trained to calculate a first probability of a presence, within a stream of one or more words, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; utilize the feature to determine the first probability of the presence, within a stream of one or more words, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary at a given word position in the data item; provide a machine-learning model that is trainable to calculate a second probability of the presence, within the stream of one or more words at the given word position, of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary, based on one or more words in the data item not utilized by the feature to determine the first probability; utilize the machine-learning model to determine the second probability of the presence, within the stream of one or more words at the given word position, of a disjunction of one or more n-grams that correspond semantically to the concept defined by the words in the dictionary, based on the one or more words in the data item not utilized by the feature to determine the first probability; determine an actual presence or absence, at the given word position, of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; and modify the machine-learning model to adjust the second probability in a positive or negative direction based on the determined actual presence or absence of the disjunction of the one or more n-grams that correspond semantically to the concept defined by the words in the dictionary; wherein the feature determines one or more of: whether any words from a given list appear at the center of a window of text around the given word position in which center words in the window of text have been removed, a presence or absence of a verb in the window, a presence or absence of a noun followed by an adjective, or a number of occurrences of a given word in the window. 8. The system of claim 1 , wherein the window of text is a sliding window that includes a number of words immediately preceding a given word position and a number of words immediately following the given word position. | 0.768085 |
9,727,642 | 18 | 20 | 18. The apparatus of claim 17 , wherein the instructions further cause the processor to prune the set of questions into a subset of questions based on the at least one of characteristics of the hypothetical link or characteristics of the at least two information concept entities at least by: comparing characteristics of the hypothetical link or characteristics of the at least two information concept entities to characteristics associated with question templates in the set of question templates; and selecting question templates, from the set of question templates, that have at least one characteristic that matches at least one characteristic of the hypothetical link or at least one characteristic of the at least two information concept entities. | 18. The apparatus of claim 17 , wherein the instructions further cause the processor to prune the set of questions into a subset of questions based on the at least one of characteristics of the hypothetical link or characteristics of the at least two information concept entities at least by: comparing characteristics of the hypothetical link or characteristics of the at least two information concept entities to characteristics associated with question templates in the set of question templates; and selecting question templates, from the set of question templates, that have at least one characteristic that matches at least one characteristic of the hypothetical link or at least one characteristic of the at least two information concept entities. 20. The apparatus of claim 18 , wherein the characteristics of the at least two information concept entities comprise at least one of an occupation associated with each of the information concept entities, a classification of the information concept entity as being a victim, witness, bystander, or suspect, a classification of a location represented by an information concept entity, or a type of relationship between the information concept entities represented by the hypothetical link. | 0.808835 |
8,694,500 | 1 | 17 | 1. A method of providing services in a network, the method comprising: storing structured service documents defining available services in a database in at least one network element; receiving a service request in the at least one network element from a service requestor, the service request comprising a structured request document, the structured request document containing a plurality of nodes; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and providing to the service requestor, at least part of an structured service document in the identified subset of structured service documents to enable the service requestor to access the service defined by the structured service document of which at least part was provided. | 1. A method of providing services in a network, the method comprising: storing structured service documents defining available services in a database in at least one network element; receiving a service request in the at least one network element from a service requestor, the service request comprising a structured request document, the structured request document containing a plurality of nodes; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and providing to the service requestor, at least part of an structured service document in the identified subset of structured service documents to enable the service requestor to access the service defined by the structured service document of which at least part was provided. 17. The method of claim 1 , wherein the structured request document is an XML request document. | 0.840067 |
7,809,669 | 2 | 6 | 2. The system of claim 1 where the inclusive constraints comprise included or true relations between an attribute and an enumeration value of the rule model; and where the exclusive constraints comprise excluded or false relations between an attribute and an enumeration value of the rule model. | 2. The system of claim 1 where the inclusive constraints comprise included or true relations between an attribute and an enumeration value of the rule model; and where the exclusive constraints comprise excluded or false relations between an attribute and an enumeration value of the rule model. 6. The system of claim 2 where the Include and Exclude ZDD rule components have associated attributes and enumeration values. | 0.928571 |
8,738,705 | 16 | 22 | 16. A computer program product having a nontransitory computer-readable storage medium storing computer-executable code, the code comprising: an object classifier module configured to: receive information identifying a set of malicious groups associated with a social networking system, wherein a group is an entity represented in the social networking system that users can join, the malicious groups predetermined to be associated with a type of malicious activity, determine a measure of interactions of the user with the malicious group, select users associated with the malicious groups, wherein each user is selected based on the determined measure of interactions of the user with the malicious groups, and select a set of potentially malicious groups associated with the selected users; a keyword search module configured to: receive keywords associated with the type of malicious activity, and search for occurrences of the keywords in content received from users of the potentially malicious groups; the object classifier module, further configured to: determine a level of association of each potentially malicious group with the type of malicious activity based on the occurrences; and a group store configured to: store information describing the level of association of each potentially malicious group with the type of malicious activity. | 16. A computer program product having a nontransitory computer-readable storage medium storing computer-executable code, the code comprising: an object classifier module configured to: receive information identifying a set of malicious groups associated with a social networking system, wherein a group is an entity represented in the social networking system that users can join, the malicious groups predetermined to be associated with a type of malicious activity, determine a measure of interactions of the user with the malicious group, select users associated with the malicious groups, wherein each user is selected based on the determined measure of interactions of the user with the malicious groups, and select a set of potentially malicious groups associated with the selected users; a keyword search module configured to: receive keywords associated with the type of malicious activity, and search for occurrences of the keywords in content received from users of the potentially malicious groups; the object classifier module, further configured to: determine a level of association of each potentially malicious group with the type of malicious activity based on the occurrences; and a group store configured to: store information describing the level of association of each potentially malicious group with the type of malicious activity. 22. The computer program product of claim 16 , the code further comprising an access control module configured to: responsive to determining that a potentially malicious group is associated with a type of malicious activity, modify access control information for the group. | 0.686927 |
10,007,803 | 1 | 3 | 1. A computer implemented method executed by one or more computing devices for searching encrypted keywords in a database, the method comprising: generating a keyword; based on the generated keyword, creating, at a data owner computing device, two or more different encrypted keywords corresponding to the generated keyword; storing the two or more different encrypted keywords for the generated keyword in the database, wherein the database is stored on a data provider computing device and storing the two or more different encrypted keywords comprises sending the two or more different encrypted keywords from the data owner computing device to the data provider computing device; generating, by the data owner computing device, a first trapdoor that matches at least one of the two or more different encrypted keywords stored in the database; generating, by the data owner computing device, a second trapdoor, different from the first trapdoor, that matches at least one of the two or more different encrypted keywords stored in the database; receiving, at the data owner computing device, a first request for a trapdoor for the generated keyword from a data user computing device; responsive to the first request, sending the first trapdoor from the data owner computing device to the data user computing device for use in searching of the encrypted keywords in the database, wherein the first trapdoor causes a keyword-is-found result when the first trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device; receiving, at the data owner computing device, a second request for a trapdoor for the generated keyword from the data user computing device; and responsive to the second request, sending the second trapdoor from the data owner computing device to the data user computing device for use in searching the encrypted keywords in the database, wherein the second trapdoor causes a keyword-is-found result when the second trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device. | 1. A computer implemented method executed by one or more computing devices for searching encrypted keywords in a database, the method comprising: generating a keyword; based on the generated keyword, creating, at a data owner computing device, two or more different encrypted keywords corresponding to the generated keyword; storing the two or more different encrypted keywords for the generated keyword in the database, wherein the database is stored on a data provider computing device and storing the two or more different encrypted keywords comprises sending the two or more different encrypted keywords from the data owner computing device to the data provider computing device; generating, by the data owner computing device, a first trapdoor that matches at least one of the two or more different encrypted keywords stored in the database; generating, by the data owner computing device, a second trapdoor, different from the first trapdoor, that matches at least one of the two or more different encrypted keywords stored in the database; receiving, at the data owner computing device, a first request for a trapdoor for the generated keyword from a data user computing device; responsive to the first request, sending the first trapdoor from the data owner computing device to the data user computing device for use in searching of the encrypted keywords in the database, wherein the first trapdoor causes a keyword-is-found result when the first trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device; receiving, at the data owner computing device, a second request for a trapdoor for the generated keyword from the data user computing device; and responsive to the second request, sending the second trapdoor from the data owner computing device to the data user computing device for use in searching the encrypted keywords in the database, wherein the second trapdoor causes a keyword-is-found result when the second trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device. 3. The method as claimed in claim 1 , wherein said creating the two or more encrypted keywords comprises: using a function J=rH 1 (W)P 0 +rQ t and N=r·P 0 , where r is a random number, H 1 is a hash function, W is the generated keyword, P 0 is a generator of a group G1, and Q t is a public key. | 0.797945 |
6,035,273 | 21 | 24 | 21. A compressed voice communication system, comprising: at least one customer premise device connected to a first device for compressing and transmitting speech; at least one other customer premise device connected to a second device for compressing and transmitting speech; a transmission media connecting said first and second devices for compressing and transmitting speech for transmitting signals therebetween; each of said first and second devices for compressing and transmitting speech, comprising: means for receiving speech from said at least one customer premise device; a speech profile defining coefficients of speech for an individual in a mathematical model; means for detecting changes in the individual's speech, said changes being defined by at least one of said coefficients of speech; means for converting said speech to text which operates in response to said means for detecting to add hypertext characters to said text indicative of said detected changes; means for transmitting said text over said transmission media; means for converting text received from said transmission media to speech; and means for delivering speech to said at least one customer premise device. | 21. A compressed voice communication system, comprising: at least one customer premise device connected to a first device for compressing and transmitting speech; at least one other customer premise device connected to a second device for compressing and transmitting speech; a transmission media connecting said first and second devices for compressing and transmitting speech for transmitting signals therebetween; each of said first and second devices for compressing and transmitting speech, comprising: means for receiving speech from said at least one customer premise device; a speech profile defining coefficients of speech for an individual in a mathematical model; means for detecting changes in the individual's speech, said changes being defined by at least one of said coefficients of speech; means for converting said speech to text which operates in response to said means for detecting to add hypertext characters to said text indicative of said detected changes; means for transmitting said text over said transmission media; means for converting text received from said transmission media to speech; and means for delivering speech to said at least one customer premise device. 24. The system according to claim 21, wherein said transmission media includes a public switched telephone network. | 0.883603 |
10,019,708 | 27 | 33 | 27. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store including phrase token configuration information associated with transaction phrase tokens, wherein the transaction phrase tokens comprise a set of unambiguous characters, and wherein the transaction phrase tokens are associated with transaction accounts via the phrase token configuration information; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the phrase token configuration information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the phrase token configuration information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. | 27. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store including phrase token configuration information associated with transaction phrase tokens, wherein the transaction phrase tokens comprise a set of unambiguous characters, and wherein the transaction phrase tokens are associated with transaction accounts via the phrase token configuration information; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the phrase token configuration information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the phrase token configuration information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. 33. The system as recited in claim 27 , wherein the set of characters corresponds to a set of one or more alphanumeric characters. | 0.910837 |
9,984,323 | 1 | 8 | 1. A method, comprising: identifying one or more structures recurring across multiple model files, wherein each model file comprises information relating to one or more neurosynaptic cores; for each recurring structure identified, generating a corresponding reusable compositional prototype, wherein each reusable compositional prototype comprises one or more metadata tags and a set of pre-defined rules, and each rule identifies one or more modifications for a neurosynaptic network; maintaining a library including each reusable compositional prototype generated; in response to receiving one or more search parameters, searching the library based on the one or more search parameters; selecting at least one reusable compositional prototype with at least one metadata tag satisfying the one or more search parameters; and instantiating one or more components of the network and connectivity between the one or more components based on one or more rules included in the at least one selected reusable compositional prototype, thereby decreasing time associated with developing and debugging the network and increasing accuracy of the network. | 1. A method, comprising: identifying one or more structures recurring across multiple model files, wherein each model file comprises information relating to one or more neurosynaptic cores; for each recurring structure identified, generating a corresponding reusable compositional prototype, wherein each reusable compositional prototype comprises one or more metadata tags and a set of pre-defined rules, and each rule identifies one or more modifications for a neurosynaptic network; maintaining a library including each reusable compositional prototype generated; in response to receiving one or more search parameters, searching the library based on the one or more search parameters; selecting at least one reusable compositional prototype with at least one metadata tag satisfying the one or more search parameters; and instantiating one or more components of the network and connectivity between the one or more components based on one or more rules included in the at least one selected reusable compositional prototype, thereby decreasing time associated with developing and debugging the network and increasing accuracy of the network. 8. The method of claim 1 , wherein the one or more rules include instantiating a transducer corelet to interconnect two neurosynaptic programs operating on different spike coding schemes. | 0.913185 |
9,639,519 | 1 | 12 | 1. An apparatus for scanning an executable script object comprising: a digital dictionary configured to store tokens each comprising a possible piece of a uniform resource locator (URL); a script parser configured to: receive an executable script object comprising text, parse the text of the executable script object to find an instance of one of the tokens in the text, continue to parse the text of the executable script object adjacent to the instance of the token to find a syntax element, and construct a candidate URL from the instance of the token and the syntax element; a URL rules detector configured to: store rules for validating URLs, and utilize the stored rules to determine whether the candidate URL is a valid URL. | 1. An apparatus for scanning an executable script object comprising: a digital dictionary configured to store tokens each comprising a possible piece of a uniform resource locator (URL); a script parser configured to: receive an executable script object comprising text, parse the text of the executable script object to find an instance of one of the tokens in the text, continue to parse the text of the executable script object adjacent to the instance of the token to find a syntax element, and construct a candidate URL from the instance of the token and the syntax element; a URL rules detector configured to: store rules for validating URLs, and utilize the stored rules to determine whether the candidate URL is a valid URL. 12. The apparatus of claim 1 , wherein: the digital dictionary is further configured to store syntax elements for constructing complete URLs from the tokens, and the syntax element the script parser is configured to fine is one of the stored syntax elements. | 0.509506 |
9,477,729 | 10 | 12 | 10. A computer program product having a non-transitory computer readable storage medium storing executable code for performing a keyword search on a database, the code when executed performs steps comprising: receiving a request including a search string for searching the database; parsing the search string to identify a plurality of keywords included in the search string; generating a plurality of string permutations based on the received search string, each string permutation being database agnostic and including at least a subset of the plurality of keywords included in the received search string, the plurality of string permutations including two string permutations each comprising different orderings of a same subset of the plurality of keywords; for each string permutation: determining a string similarity score between the string permutation and the search string based on which keywords are included in the string permutation and an order of keywords in the string permutation relative to an order of the keywords in the search string; launching an asynchronous thread for executing a search on the data in the database based on the string permutation; receiving a plurality of search results when the thread completes execution of the search, each search result identifying a row in the database that includes data relevant to the string permutation: determining a result relevance score associated with each search result by combining the string similarity score for the string permutation and a permutation result relevance score included with the search result, the permutation result relevance score measuring relevance between the string permutation and the data relevant to the string permutation; and collecting the plurality of search results in an ordered queue, the ordering of the search results based on the result relevance score associated with each search result; and retrieving data from rows in the database identified by a subset of the search results collected in the ordered queue for display in response to the request. | 10. A computer program product having a non-transitory computer readable storage medium storing executable code for performing a keyword search on a database, the code when executed performs steps comprising: receiving a request including a search string for searching the database; parsing the search string to identify a plurality of keywords included in the search string; generating a plurality of string permutations based on the received search string, each string permutation being database agnostic and including at least a subset of the plurality of keywords included in the received search string, the plurality of string permutations including two string permutations each comprising different orderings of a same subset of the plurality of keywords; for each string permutation: determining a string similarity score between the string permutation and the search string based on which keywords are included in the string permutation and an order of keywords in the string permutation relative to an order of the keywords in the search string; launching an asynchronous thread for executing a search on the data in the database based on the string permutation; receiving a plurality of search results when the thread completes execution of the search, each search result identifying a row in the database that includes data relevant to the string permutation: determining a result relevance score associated with each search result by combining the string similarity score for the string permutation and a permutation result relevance score included with the search result, the permutation result relevance score measuring relevance between the string permutation and the data relevant to the string permutation; and collecting the plurality of search results in an ordered queue, the ordering of the search results based on the result relevance score associated with each search result; and retrieving data from rows in the database identified by a subset of the search results collected in the ordered queue for display in response to the request. 12. The computer program product of claim 10 , wherein the subset of the search results comprise one or more search results included in a first plurality of search results received when a first thread completes the execution of the search, and the subset of the search results are selected before a second thread has completed the execution of the search. | 0.738971 |
9,946,794 | 27 | 39 | 27. A search system comprising: a remote general purpose search system including one or more processors that are configured to execute instructions stored in a non-transitory computer-readable medium; a special purpose search system in communication with the remote general purpose search system, wherein the special purpose search system includes one or more processors that are configured to execute instructions stored in a non-transitory computer-readable medium; and a recommendation device in communication with the remote general purpose search system and the special purpose search system, wherein: the recommendation device includes one or more processors that are configured to execute instructions stored in a nontransitory computer-readable medium; and the recommendation device is configured to, in response to receiving a search query originating from the remote general purpose search system or a user device in communication with the remote general purpose search system, determine a first module score; the first module score is based on at least one input received by the user device in response to a previous search query; the recommendation device is configured to, in response to determining that the first module score is greater than a first minimum threshold score and less than a first maximum threshold score, determine a second module score; the second module score is based on a match between (i) the search query and (ii) each application of a first set of applications associated with a special purpose search system; each application of the first set of applications has a popularity score greater than or equal to a threshold popularity score; the recommendation device is configured to, in response to determining that the second module score is less than a second threshold score, determine a third module score; the third module score is based on a match between (i) the search query and (ii) previously executed search queries; the previously executed search queries are associated with an application search; the recommendation device is configured to, in response to one of (i) the first module score being greater than or equal to the first maximum threshold score, (ii) the second module score being greater than or equal to the second threshold score, and (iii) the third module score being greater than or equal to a third maximum threshold score, determine that a special purpose search intent of the search query exists; the recommendation device is configured to, in response to determining that the special purpose search intent of the search query exists, send a positive recommendation to at least one of the general purpose search system, the special purpose search system or the user device; the positive recommendation includes an instruction to obtain special purpose search results from the special purpose search system; the special purpose search system is configured to, in response to the remote general purpose search system receiving the positive recommendation, generate application search results based on the search query; the remote general purpose search system is configured to, in response to the special purpose search system generating application search results, obtain the application search results from the special purpose search system; the remote general purpose search system is configured to generate general purpose search results based on the search query; and the remote general purpose search system is configured to transmit a set of the application search results and a set of the general purpose search results to the user device. | 27. A search system comprising: a remote general purpose search system including one or more processors that are configured to execute instructions stored in a non-transitory computer-readable medium; a special purpose search system in communication with the remote general purpose search system, wherein the special purpose search system includes one or more processors that are configured to execute instructions stored in a non-transitory computer-readable medium; and a recommendation device in communication with the remote general purpose search system and the special purpose search system, wherein: the recommendation device includes one or more processors that are configured to execute instructions stored in a nontransitory computer-readable medium; and the recommendation device is configured to, in response to receiving a search query originating from the remote general purpose search system or a user device in communication with the remote general purpose search system, determine a first module score; the first module score is based on at least one input received by the user device in response to a previous search query; the recommendation device is configured to, in response to determining that the first module score is greater than a first minimum threshold score and less than a first maximum threshold score, determine a second module score; the second module score is based on a match between (i) the search query and (ii) each application of a first set of applications associated with a special purpose search system; each application of the first set of applications has a popularity score greater than or equal to a threshold popularity score; the recommendation device is configured to, in response to determining that the second module score is less than a second threshold score, determine a third module score; the third module score is based on a match between (i) the search query and (ii) previously executed search queries; the previously executed search queries are associated with an application search; the recommendation device is configured to, in response to one of (i) the first module score being greater than or equal to the first maximum threshold score, (ii) the second module score being greater than or equal to the second threshold score, and (iii) the third module score being greater than or equal to a third maximum threshold score, determine that a special purpose search intent of the search query exists; the recommendation device is configured to, in response to determining that the special purpose search intent of the search query exists, send a positive recommendation to at least one of the general purpose search system, the special purpose search system or the user device; the positive recommendation includes an instruction to obtain special purpose search results from the special purpose search system; the special purpose search system is configured to, in response to the remote general purpose search system receiving the positive recommendation, generate application search results based on the search query; the remote general purpose search system is configured to, in response to the special purpose search system generating application search results, obtain the application search results from the special purpose search system; the remote general purpose search system is configured to generate general purpose search results based on the search query; and the remote general purpose search system is configured to transmit a set of the application search results and a set of the general purpose search results to the user device. 39. The system of claim 27 , wherein the recommendation device is configured to: in response to determining that the third module score is greater than a third minimum threshold score and less than the third maximum threshold score, determine, at a grammar matching module executing at the recommendation device, a fourth module score by: matching the search query with a grammar within a search domain of the special purpose search system, wherein each grammar has an associated grammar score; and outputting the fourth module score based on the associated grammar score of the grammar matching module; and in response to the fourth module score being greater than a fourth maximum threshold, determine that the special purpose search intent of the search query exists. | 0.500649 |
8,340,405 | 1 | 2 | 1. A computer implemented method for annotating digital files, the method comprising: at a computer system having one or more processors and memory storing one or more programs that when executed by the one or more processors cause the computer system to perform the method: identifying a plurality of first features of a plurality of first digital files having one or more associated annotations; partitioning the plurality of first features into a plurality of subsets of the first features, including a respective subset of the first features; generating one or more classifiers based on the respective subset of the first features; identifying a plurality of second features of a respective second digital file; for each respective first digital file of two or more of the plurality of first digital files, determining a distance vector corresponding to a respective partial distance between a representation of features of the respective second digital file and a representation of features of the respective first digital file using a respective classifier; identifying a subset of the plurality of first digital files as candidate nearest neighbors to the respective second digital file based on the partial distances; determining scores corresponding to full distances between features of a plurality of the candidate nearest neighbors and features of the respective second digital file and ranking the determined scores; selecting a subset of the candidate nearest neighbors as matched files based on the ranking, wherein the matched files are associated with a respective annotation; and associating the respective annotation with the respective second digital file. | 1. A computer implemented method for annotating digital files, the method comprising: at a computer system having one or more processors and memory storing one or more programs that when executed by the one or more processors cause the computer system to perform the method: identifying a plurality of first features of a plurality of first digital files having one or more associated annotations; partitioning the plurality of first features into a plurality of subsets of the first features, including a respective subset of the first features; generating one or more classifiers based on the respective subset of the first features; identifying a plurality of second features of a respective second digital file; for each respective first digital file of two or more of the plurality of first digital files, determining a distance vector corresponding to a respective partial distance between a representation of features of the respective second digital file and a representation of features of the respective first digital file using a respective classifier; identifying a subset of the plurality of first digital files as candidate nearest neighbors to the respective second digital file based on the partial distances; determining scores corresponding to full distances between features of a plurality of the candidate nearest neighbors and features of the respective second digital file and ranking the determined scores; selecting a subset of the candidate nearest neighbors as matched files based on the ranking, wherein the matched files are associated with a respective annotation; and associating the respective annotation with the respective second digital file. 2. The method of claim 1 , further comprising: generating a plurality of classifiers from the plurality of first features; applying the respective second digital file to the plurality of classifiers and determining a weight value corresponding to each of the plurality of classifiers; combining the weight values corresponding to one or more of the classifiers; and associating one or more annotations from a respective subset of matched files to the respective second digital file based on the combined weight values. | 0.777108 |
8,977,625 | 1 | 3 | 1. A computer-implemented method of facilitating generation of an inference index using a computing system having processor, memory, and data storage subsystems, the computer-implemented method comprising: referencing a canonical entity that is associated with one or more web documents; identifying a plurality of queries that, when input, result in a selection of at least one web document of the one or more web documents associated with the canonical entity; generating, via the processor, an entity document for the canonical entity, the entity document including the plurality of identified queries and a representation of the at least one web document, wherein the plurality of identified queries resulted in the selection of the at least one web document corresponding with the canonical entity comprising a unique representation of an entity; generating an inference index using the canonical entity and the entity document along with other related canonical entities and corresponding entity documents, the inference index corresponding with a knowledge domain of related canonical entities; and utilizing the inference index in response to a real-time user query provided by a user after generation of the inference index to select a particular canonical entity that is most related to the real-time user query, the particular canonical entity comprising a unique representation of an entity that indicates a person or place and that is selected based on a cumulative score associated with the selected canonical entity being greater than cumulative scores associated with one or more other canonical entities within the inference index, wherein each of the cumulative scores for the canonical entities comprises an aggregate of entity document scores within the corresponding canonical entity, each entity document score calculated based on a frequency of at least a portion of the real-time user query occurring within queries of the corresponding entity document. | 1. A computer-implemented method of facilitating generation of an inference index using a computing system having processor, memory, and data storage subsystems, the computer-implemented method comprising: referencing a canonical entity that is associated with one or more web documents; identifying a plurality of queries that, when input, result in a selection of at least one web document of the one or more web documents associated with the canonical entity; generating, via the processor, an entity document for the canonical entity, the entity document including the plurality of identified queries and a representation of the at least one web document, wherein the plurality of identified queries resulted in the selection of the at least one web document corresponding with the canonical entity comprising a unique representation of an entity; generating an inference index using the canonical entity and the entity document along with other related canonical entities and corresponding entity documents, the inference index corresponding with a knowledge domain of related canonical entities; and utilizing the inference index in response to a real-time user query provided by a user after generation of the inference index to select a particular canonical entity that is most related to the real-time user query, the particular canonical entity comprising a unique representation of an entity that indicates a person or place and that is selected based on a cumulative score associated with the selected canonical entity being greater than cumulative scores associated with one or more other canonical entities within the inference index, wherein each of the cumulative scores for the canonical entities comprises an aggregate of entity document scores within the corresponding canonical entity, each entity document score calculated based on a frequency of at least a portion of the real-time user query occurring within queries of the corresponding entity document. 3. The computer-implemented method of claim 1 , further comprising: composing one or more queries which are mapped to the canonical entity; searching the composed one or more queries to obtain one or more resultant web documents mapped to the canonical entity; collecting stored queries linked to the one or more resultant web documents; and combining the collected stored queries to the entity document for the canonical entity. | 0.5397 |
8,903,754 | 1 | 7 | 1. A process for reporting identified items of interest associated with a brand associated with an identity of an entity, the process comprising: generating, by a computer, a seed document containing criteria representative of items of interest representative of a brand associated with an identity of a selected entity, wherein the items of interest are associated with the identity of the selected entity by a policy for associating items of interest with brand indicia of predetermined entities; receiving, by the computer, the seed document containing the criteria into a repository to initialize the repository, wherein the repository comprises information describing brand indicia representative of the selected entity; analyzing, by the computer, a selected source material using the criteria in the seed document in combination with the repository, by selectively applying adapters associated with specific types of content contained within the selected source material to perform analysis including semantic analysis and pattern matching; responsive to the analysis, the computer identifying a set of items of interest in the selected source material that meet the criteria representative of items of interest associated with the selected entity to form an identified set of items of interest; and generating a report wherein the report includes the identified set of items of interest, by the computer by: filtering a result, by the computer, using a set of rules to form a filtered result; prompting a user, by the computer, to accept or reject an identified item of interest in the filtered result; responsive to receiving an acceptance, the computer increasing a relevancy score associated with the identified item of interest; responsive to receiving a rejection, the computer decreasing the relevancy score associated with the identified item of interest; determining, by the computer, whether a relevancy score associated with the identified item of interest meets a predetermined threshold value; responsive to the relevancy score associated with the identified item of interest not meeting the predetermined threshold value, the computer filtering the result to remove the identified item of interest from the identified set of items of interest in the filtered result to form a remaining set of identified items of interest in the filtered result; linking an identified item of interest in the remaining set of identified items of interest in the filtered result, by the computer, to a corresponding document in the selected source in which the identified item of interest is located; marking the identified item of interest in the remaining set of identified items of interest in the filtered result for review; and updating the repository, by the computer, using information associated with the remaining set of identified items of interest in the filtered result including respective relevancy scores. | 1. A process for reporting identified items of interest associated with a brand associated with an identity of an entity, the process comprising: generating, by a computer, a seed document containing criteria representative of items of interest representative of a brand associated with an identity of a selected entity, wherein the items of interest are associated with the identity of the selected entity by a policy for associating items of interest with brand indicia of predetermined entities; receiving, by the computer, the seed document containing the criteria into a repository to initialize the repository, wherein the repository comprises information describing brand indicia representative of the selected entity; analyzing, by the computer, a selected source material using the criteria in the seed document in combination with the repository, by selectively applying adapters associated with specific types of content contained within the selected source material to perform analysis including semantic analysis and pattern matching; responsive to the analysis, the computer identifying a set of items of interest in the selected source material that meet the criteria representative of items of interest associated with the selected entity to form an identified set of items of interest; and generating a report wherein the report includes the identified set of items of interest, by the computer by: filtering a result, by the computer, using a set of rules to form a filtered result; prompting a user, by the computer, to accept or reject an identified item of interest in the filtered result; responsive to receiving an acceptance, the computer increasing a relevancy score associated with the identified item of interest; responsive to receiving a rejection, the computer decreasing the relevancy score associated with the identified item of interest; determining, by the computer, whether a relevancy score associated with the identified item of interest meets a predetermined threshold value; responsive to the relevancy score associated with the identified item of interest not meeting the predetermined threshold value, the computer filtering the result to remove the identified item of interest from the identified set of items of interest in the filtered result to form a remaining set of identified items of interest in the filtered result; linking an identified item of interest in the remaining set of identified items of interest in the filtered result, by the computer, to a corresponding document in the selected source in which the identified item of interest is located; marking the identified item of interest in the remaining set of identified items of interest in the filtered result for review; and updating the repository, by the computer, using information associated with the remaining set of identified items of interest in the filtered result including respective relevancy scores. 7. The process of claim 1 further comprising: reviewing of the marked items to imitate other analysis including bug reporting and corrective action modifying previously used criteria, adapters and associated definitions. | 0.896907 |
8,442,309 | 1 | 13 | 1. A computer implemented method for learning a random multinomial logit (RML) classifier for scene segmentation, the method comprising: receiving an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; generating a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; selecting one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; learning multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluating the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. | 1. A computer implemented method for learning a random multinomial logit (RML) classifier for scene segmentation, the method comprising: receiving an image training set, wherein the image training set comprises multiple digital representations of images, and an object of an image of the image training set has a semantic label; generating a plurality of texton images corresponding to the images in the image training set, wherein a texton image of its corresponding image in the image training set is an image of pixels, and wherein each pixel value in a texton image is replaced by a representation of the pixel value of its corresponding image in the image training set; selecting one or more texture-layout features from the plurality of the texton images, wherein selecting one or more texture-layout features comprises swapping a feature currently being used by the RML classifier with a randomly selected new feature based on the statistical significance of the feature currently being used; learning multiple multinomial logistic regression models of the RML classifier based on the selected texture-layout features; and evaluating the performance of the multiple multinomial logistic regression models based on the semantic labels of the objects in the image training set. 13. The method of claim 1 further comprises applying the RML classifier to an input image for scene segmentation. | 0.911856 |
7,917,455 | 1 | 8 | 1. A computing device for rapidly evaluating logical expressions, the computing device comprising: a memory space for storing code; a processor, coupled to the memory space, executing the code to cause the computing device to repeatedly perform operations of: determining a set of primitives defining some or all of a current state of a model of a virtual or real world; accessing a set of logical expressions including the primitives, each of the logical expressions being either a true or false statement about the current state of the model, wherein a union of the logical expressions is expressed in one or more directed acyclic graphs; and computing which of the logical expressions are true statements about the current state of the model by traversing the one or more directed acyclic graphs once exactly in one path from a root node to a leaf node in the one or more directed acyclic graphs. | 1. A computing device for rapidly evaluating logical expressions, the computing device comprising: a memory space for storing code; a processor, coupled to the memory space, executing the code to cause the computing device to repeatedly perform operations of: determining a set of primitives defining some or all of a current state of a model of a virtual or real world; accessing a set of logical expressions including the primitives, each of the logical expressions being either a true or false statement about the current state of the model, wherein a union of the logical expressions is expressed in one or more directed acyclic graphs; and computing which of the logical expressions are true statements about the current state of the model by traversing the one or more directed acyclic graphs once exactly in one path from a root node to a leaf node in the one or more directed acyclic graphs. 8. The computing device as recited in claim 1 , wherein the computing device is executing a video game and is configured to facilitate real-time or near real-time decision making in accordance with a subset of the logical expressions that are true. | 0.842839 |
10,032,450 | 1 | 12 | 1. A system for generating and updating user interface with machine learning output data relating to electronic communications and contact data, the system comprising: a data storage device storing a graph structure of nodes and edges, the nodes corresponding to contacts and the edges corresponding to relationship scores; a message routing plug in configured to intercept an electronic communication in real-time, the electronic communication having a reference to a contact for at least one of a sender, a recipient and another entity referred to in the electronic communication, the contact corresponding to a node in the graph structure; a machine learning processor configured to: process the electronic communication using classification rules to compute a relationship score, the classification rules comprising natural language processing rules for sentiment classification and formality classification, the relationship score indicating strength of a relationship between the contact and another contact; update the graph structure using the relationship score by updating or creating an edge connected to the node corresponding to the contact in the graph structure based on the relationship score and contact data; a presentation processor configured to process machine interpretable instructions to generate visual effects for at least a portion of the graph structure in response to search requests and queries identifying the contact, the presentation processor further configured to control rendering, on a display at a device, of a user interface including visual interface elements corresponding to the visual effects for the portion of the graph structure generated by the machine learning processor, the visual interface elements indicating contact nodes and relationship edges connecting the contact nodes, the visual effects indicating a contact node representing the node corresponding to the contact in the graph structure, a relationship edge representing the edge connected to the node corresponding to the contact, and an indication of the relationship score; the user interface adapted to render a button configured to be responsive to input representing an indication of the search requests and the queries identifying the contact for provision to the machine learning processor; responsive to the button, the presentation processor further configured to control updating, at the user interface, of the visual interface elements with the visual effects to indicate the contact node, the relationship edge, and the indication of the relationship score. | 1. A system for generating and updating user interface with machine learning output data relating to electronic communications and contact data, the system comprising: a data storage device storing a graph structure of nodes and edges, the nodes corresponding to contacts and the edges corresponding to relationship scores; a message routing plug in configured to intercept an electronic communication in real-time, the electronic communication having a reference to a contact for at least one of a sender, a recipient and another entity referred to in the electronic communication, the contact corresponding to a node in the graph structure; a machine learning processor configured to: process the electronic communication using classification rules to compute a relationship score, the classification rules comprising natural language processing rules for sentiment classification and formality classification, the relationship score indicating strength of a relationship between the contact and another contact; update the graph structure using the relationship score by updating or creating an edge connected to the node corresponding to the contact in the graph structure based on the relationship score and contact data; a presentation processor configured to process machine interpretable instructions to generate visual effects for at least a portion of the graph structure in response to search requests and queries identifying the contact, the presentation processor further configured to control rendering, on a display at a device, of a user interface including visual interface elements corresponding to the visual effects for the portion of the graph structure generated by the machine learning processor, the visual interface elements indicating contact nodes and relationship edges connecting the contact nodes, the visual effects indicating a contact node representing the node corresponding to the contact in the graph structure, a relationship edge representing the edge connected to the node corresponding to the contact, and an indication of the relationship score; the user interface adapted to render a button configured to be responsive to input representing an indication of the search requests and the queries identifying the contact for provision to the machine learning processor; responsive to the button, the presentation processor further configured to control updating, at the user interface, of the visual interface elements with the visual effects to indicate the contact node, the relationship edge, and the indication of the relationship score. 12. The system of claim 1 , wherein the visual effects for at least a portion of the graph structure are dynamically generated in response to search requests and queries identifying the contacts to indicate the strength of connection between contacts based on the relationship score. | 0.674713 |
8,560,615 | 7 | 8 | 7. The method of claim 1 , wherein each row in the set of rows includes a conversation topic and a date/time value for the conversation represented by the row. | 7. The method of claim 1 , wherein each row in the set of rows includes a conversation topic and a date/time value for the conversation represented by the row. 8. The method of claim 7 , wherein the conversation topic of a row in the set of rows includes a conversation name and a snippet of the conversation associated with the row. | 0.95357 |
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