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8,983,940 | 1 | 5 | 1. A method for object retrieval and localization, comprising: performing, by one or more computing devices: obtaining an initial ranking of a collection of a plurality of images, with regard to a query object included in a query image, the initial ranking based on a similarity score for each of the images of the collection to the query object, the similarity score determined using a spatially-constrained similarity measure; generating a ranking of the collection with regard to each of one or more nearest neighbors to the query object as indicated by the initial ranking of the collection, said generating the ranking comprising: for each of the one or more nearest neighbors, searching the collection according to a localized object of the respective nearest neighbor to determine the similarity scores for the collection, the localized object being a best match object of the respective nearest neighbor to the query object in the query image; ranking the collection according to the similarity scores; and generating a new ranking of the collection with regard to the query object according to the initial ranking and the generated rankings with regard to each of the one or more nearest neighbors. | 1. A method for object retrieval and localization, comprising: performing, by one or more computing devices: obtaining an initial ranking of a collection of a plurality of images, with regard to a query object included in a query image, the initial ranking based on a similarity score for each of the images of the collection to the query object, the similarity score determined using a spatially-constrained similarity measure; generating a ranking of the collection with regard to each of one or more nearest neighbors to the query object as indicated by the initial ranking of the collection, said generating the ranking comprising: for each of the one or more nearest neighbors, searching the collection according to a localized object of the respective nearest neighbor to determine the similarity scores for the collection, the localized object being a best match object of the respective nearest neighbor to the query object in the query image; ranking the collection according to the similarity scores; and generating a new ranking of the collection with regard to the query object according to the initial ranking and the generated rankings with regard to each of the one or more nearest neighbors. 5. The method as recited in claim 1 , further comprising repeating said generating a ranking of the collection with regard to each of one or more nearest neighbors to the query object as indicated by the initial ranking of the collection and said generating a new ranking of the collection with regard to the query object according to the initial ranking and the generated rankings with regard to each of the one or more nearest neighbors for one or more iterations, wherein the new ranking is used as the initial ranking in the subsequent iterations. | 0.5 |
8,909,572 | 9 | 10 | 9. A method for performing classification comprising: implementing a boosted classifier having a plurality of weak hypotheses that produce a classification, each of the plurality of weak hypotheses having at least one weight, using a hardware processor; receiving testing data; receiving at least one piece of training data subsequently to receiving the testing data; calculating corrective terms for correcting a sum of weights of correctly classified training data and a sum of weights of incorrectly classified training data for at least one of the plurality of weak hypotheses based on a change in weights for the at least one weight of other of the plurality of weak hypotheses; calculating the sum of weights of correctly classified training data and the sum of weights of incorrectly classified training data based on the corrective terms; modifying the at least one weight of at least one of the plurality of weak hypotheses in response to the at least one piece of training data based on the sum of weights to produce modified weights; classifying the testing data based on the modified weights to produce a classification; and indicating the classification of the testing data. | 9. A method for performing classification comprising: implementing a boosted classifier having a plurality of weak hypotheses that produce a classification, each of the plurality of weak hypotheses having at least one weight, using a hardware processor; receiving testing data; receiving at least one piece of training data subsequently to receiving the testing data; calculating corrective terms for correcting a sum of weights of correctly classified training data and a sum of weights of incorrectly classified training data for at least one of the plurality of weak hypotheses based on a change in weights for the at least one weight of other of the plurality of weak hypotheses; calculating the sum of weights of correctly classified training data and the sum of weights of incorrectly classified training data based on the corrective terms; modifying the at least one weight of at least one of the plurality of weak hypotheses in response to the at least one piece of training data based on the sum of weights to produce modified weights; classifying the testing data based on the modified weights to produce a classification; and indicating the classification of the testing data. 10. The method of claim 9 , further comprising determining, for each of at least two of the plurality of weak hypotheses, a product of the weight for the corresponding weak hypothesis and the classification for the corresponding weak hypothesis, and sums the products for the at least two of the plurality of weak hypotheses. | 0.5 |
7,797,316 | 32 | 34 | 32. A system, implemented within one or more computer devices, for determining a freshness of a first document, comprising: means for identifying a set of second documents that each contains, or previously contained, a link to the first document; means for determining a freshness attribute associated with each document of the set of second documents; means for determining a freshness score of the first document based on the freshness attribute associated with each document of the set of second documents, where the freshness attribute indicates when each document was last modified; and means for ranking the first document with respect to at least one other document based on the determined freshness score. | 32. A system, implemented within one or more computer devices, for determining a freshness of a first document, comprising: means for identifying a set of second documents that each contains, or previously contained, a link to the first document; means for determining a freshness attribute associated with each document of the set of second documents; means for determining a freshness score of the first document based on the freshness attribute associated with each document of the set of second documents, where the freshness attribute indicates when each document was last modified; and means for ranking the first document with respect to at least one other document based on the determined freshness score. 34. The system of claim 32 , further comprising: means for assigning a first freshness score to the first document if a majority of documents of the set of second documents correspond to documents that have freshness values that are less than a threshold; and means for assigning a second freshness score to the first document if a majority of documents of the set of second documents correspond to documents that have freshness values that are greater than or equal to the threshold, where the first freshness score is less than the second freshness score. | 0.5 |
8,719,031 | 2 | 6 | 2. The method of claim 1 , wherein making the supplemental media content available comprises presenting an option to select the supplemental media content available to the first audience member for the audio conference, and wherein the supplemental media content is selectively presented to the first audience member responsive to selection of the supplemental media content by the first audience member. | 2. The method of claim 1 , wherein making the supplemental media content available comprises presenting an option to select the supplemental media content available to the first audience member for the audio conference, and wherein the supplemental media content is selectively presented to the first audience member responsive to selection of the supplemental media content by the first audience member. 6. The method of claim 2 , further comprising: accepting preference input from the first audience member for the audio conference; and editing the supplemental media content for which the option to select is presented to the first audience member based on the accepted preference input. | 0.740942 |
9,798,813 | 1 | 2 | 1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. | 1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. 2. The method of claim 1 , wherein the lead active person object is identified based on most recent account activity in the first person-related set. | 0.648585 |
7,567,922 | 9 | 10 | 9. A data processing system for generating a normalized configuration model comprises: a processor; and a memory, coupled to the processor, the memory having code encoded therein and executable by the processor to: generate product configuration instances from one or more product configuration models that include non-normalized feature references; identify non-normalized feature references included in one or more of the product configuration instances; access a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locate normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replace non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generate a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. | 9. A data processing system for generating a normalized configuration model comprises: a processor; and a memory, coupled to the processor, the memory having code encoded therein and executable by the processor to: generate product configuration instances from one or more product configuration models that include non-normalized feature references; identify non-normalized feature references included in one or more of the product configuration instances; access a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locate normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replace non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generate a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. 10. The data processing system of claim 9 wherein the normalized configuration model includes a complete representation of all generated product configuration instances. | 0.629386 |
10,034,099 | 1 | 8 | 1. An apparatus for differentiating between vowels and consonants in a spoken sound, the apparatus comprising: a microphone configured to receive the spoken sound and generate an output signal, the microphone including: a set of carbon nanotube bundles configured to receive the spoken sound, wherein the set of carbon nanotube bundles includes carbon nanotubes of varying lengths and thicknesses, wherein the carbon nanotube bundles in the set of carbon nanotube bundles are arranged parallel to each other and wherein the set of carbon nanotube bundles provide an output for differentiating the spoken sound as vowels and consonants; an electrode block configured to measure variation in a set of characteristic parameters of the set of carbon nanotube bundles caused by the received spoken sound and generate the output signal based on the measured variation in the set of characteristic parameters, wherein the electrode block includes a set of conducting plates and an electrode electrically connected to the set of conducting plates, and wherein the set of carbon nanotube bundles is located adjacent to the electrode block in a longitudinal direction. | 1. An apparatus for differentiating between vowels and consonants in a spoken sound, the apparatus comprising: a microphone configured to receive the spoken sound and generate an output signal, the microphone including: a set of carbon nanotube bundles configured to receive the spoken sound, wherein the set of carbon nanotube bundles includes carbon nanotubes of varying lengths and thicknesses, wherein the carbon nanotube bundles in the set of carbon nanotube bundles are arranged parallel to each other and wherein the set of carbon nanotube bundles provide an output for differentiating the spoken sound as vowels and consonants; an electrode block configured to measure variation in a set of characteristic parameters of the set of carbon nanotube bundles caused by the received spoken sound and generate the output signal based on the measured variation in the set of characteristic parameters, wherein the electrode block includes a set of conducting plates and an electrode electrically connected to the set of conducting plates, and wherein the set of carbon nanotube bundles is located adjacent to the electrode block in a longitudinal direction. 8. The apparatus of claim 1 , wherein: the set of carbon nanotube bundles support a set of dynamic characteristics of the spoken sound; and the set of dynamic characteristics is selected from the group consisting of: (i) sound loudness; (ii) sound pitch; and (iii) sound quality including timbre and richness. | 0.66044 |
7,835,943 | 6 | 7 | 6. The database searching apparatus of claim 1 , further comprising: one or more software agents configured to: receive advertiser bid information; and act on the advertiser bid information to adjust the CPC for a specified search listing. | 6. The database searching apparatus of claim 1 , further comprising: one or more software agents configured to: receive advertiser bid information; and act on the advertiser bid information to adjust the CPC for a specified search listing. 7. The database searching apparatus of claim 6 , wherein the one or more software agents is configured to: increase the current CPC of the specified search listing if the rank of the specified search listing can be improved without exceeding the maximum CPC, otherwise, not adjust the current CPC of the specified search listing; and decrease the current CPC of the specified search listing without moving the specified search listing to a rank worse than the desired rank. | 0.5 |
8,732,160 | 1 | 8 | 1. A method comprising: receiving, via at least one computer, a data set and a query template, the data set comprising a plurality of attributes for a plurality of web pages; organizing, via the at least one computer, the query template based on a number of seeks of the data set needed to fetch data associated with the query template, the organizing comprising identifying a plurality of dense attributes from the plurality of attributes, each dense attribute having a selectivity exceeding a maximum query selectivity threshold; building, via the at least one computer, an index for the query template after the query template is organized, the index is organized into a plurality of sections based on a number of seeks of the data set needed to fetch data associated with the query template, the plurality of sections comprising a plurality of primary sections and a plurality of secondary sections, each dense attribute of the plurality having a corresponding primary section and each secondary section having a corresponding dense attribute that is denser than one or more other dense attributes of the plurality; receiving, via the at least one computer, one or more bindings for the query template, the bindings comprising query restrictions; computing, via the at least one computer, an answer to the query template by using the index and the bindings; and precomputing, via the at least one computer, answers for one or more future queries that a user may submit to explore the data set, wherein the future queries comprise query terms of the query template and at least one additional query term. | 1. A method comprising: receiving, via at least one computer, a data set and a query template, the data set comprising a plurality of attributes for a plurality of web pages; organizing, via the at least one computer, the query template based on a number of seeks of the data set needed to fetch data associated with the query template, the organizing comprising identifying a plurality of dense attributes from the plurality of attributes, each dense attribute having a selectivity exceeding a maximum query selectivity threshold; building, via the at least one computer, an index for the query template after the query template is organized, the index is organized into a plurality of sections based on a number of seeks of the data set needed to fetch data associated with the query template, the plurality of sections comprising a plurality of primary sections and a plurality of secondary sections, each dense attribute of the plurality having a corresponding primary section and each secondary section having a corresponding dense attribute that is denser than one or more other dense attributes of the plurality; receiving, via the at least one computer, one or more bindings for the query template, the bindings comprising query restrictions; computing, via the at least one computer, an answer to the query template by using the index and the bindings; and precomputing, via the at least one computer, answers for one or more future queries that a user may submit to explore the data set, wherein the future queries comprise query terms of the query template and at least one additional query term. 8. The method of claim 1 , further comprising at least one of: determining that the query template is a candidate for precomputing; and precomputing an answer to the query in an online fashion. | 0.643911 |
8,572,071 | 21 | 22 | 21. The non-transitory computer readable storage medium of claim 20 wherein naΓ―ve assumption of conditional independence of attributes given a value of attribute i is: P β² β‘ ( x 1 , β¦ β’ , x n β X x i β‘ ( i ) ) = β j = 1 n β’ P β² β‘ ( x j β x i ) , where conditional higher-order probability mass function Pβ²(x j |x i ) is estimated by P β² β‘ ( x j = 1 β x i ) = ο Ο β‘ ( j , X x i β‘ ( i ) ) ο ο Ξ¦ β‘ ( X x i β‘ ( i ) ) ο since Pβ²(x j =0|x i )=1βPβ²(x j =1|x i ), and the proposed transform is a non-linear mapping Z=(z 1 (x), . . . , z n (x)):{0,1} n β n , from a n-dimensional boolean space X to a n-dimensional real space Z, where function Z maps each boolean attribute i to the real domain by a non-linear function z i (x 1 , . . . , x n ):{0,1}β n , and mapping functions z i are defined over a space of higher-order paths as z i β‘ ( x 1 , β¦ β’ , x n ) = P β² β‘ ( x i = 1 β x 1 , β¦ β’ , x n ) P β² β‘ ( x i = 0 β x 1 , β¦ β’ , x n ) = β j = 1 n β’ P β² β‘ ( x j β x i = 1 ) P β² β‘ ( x j β x i = 0 ) β’ P β² β‘ ( X 1 β‘ ( i ) ) P β² β‘ ( X 0 β‘ ( i ) ) . | 21. The non-transitory computer readable storage medium of claim 20 wherein naΓ―ve assumption of conditional independence of attributes given a value of attribute i is: P β² β‘ ( x 1 , β¦ β’ , x n β X x i β‘ ( i ) ) = β j = 1 n β’ P β² β‘ ( x j β x i ) , where conditional higher-order probability mass function Pβ²(x j |x i ) is estimated by P β² β‘ ( x j = 1 β x i ) = ο Ο β‘ ( j , X x i β‘ ( i ) ) ο ο Ξ¦ β‘ ( X x i β‘ ( i ) ) ο since Pβ²(x j =0|x i )=1βPβ²(x j =1|x i ), and the proposed transform is a non-linear mapping Z=(z 1 (x), . . . , z n (x)):{0,1} n β n , from a n-dimensional boolean space X to a n-dimensional real space Z, where function Z maps each boolean attribute i to the real domain by a non-linear function z i (x 1 , . . . , x n ):{0,1}β n , and mapping functions z i are defined over a space of higher-order paths as z i β‘ ( x 1 , β¦ β’ , x n ) = P β² β‘ ( x i = 1 β x 1 , β¦ β’ , x n ) P β² β‘ ( x i = 0 β x 1 , β¦ β’ , x n ) = β j = 1 n β’ P β² β‘ ( x j β x i = 1 ) P β² β‘ ( x j β x i = 0 ) β’ P β² β‘ ( X 1 β‘ ( i ) ) P β² β‘ ( X 0 β‘ ( i ) ) . 22. The non-transitory computer readable storage medium of claim 21 wherein a log transformation of mapping functions is defined as: log β’ β’ z i β‘ ( x 1 , β¦ β’ , x n ) = β j = 1 n β’ P β² β‘ ( x j β x i = 1 ) P β² β‘ ( x j β x i = 0 ) + log β’ P β² β‘ ( X 1 β‘ ( i ) ) P β² β‘ ( X 0 β‘ ( i ) ) . | 0.5 |
8,315,851 | 25 | 36 | 25. A computer system for processing Japanese Kana language, comprising: a computer memory to store program code; and a processor to execute the program code to: receive at least one Kana character from a user; apply a Kana rule set to the at least one Kana character; define the at least one Kana character in an alphabetic language based on a sound of the at least one Kana character; generate a full phonetic key for the defined at least one Kana character; generate a replaced-vowel phonetic key by replacing a vowel in the full phonetic key; generate a no-vowel phonetic key by removing the vowel in the full phonetic key; process Kana records in a database to determine a relevant Kana record that has a phonetic key identical to at least one of the full phonetic key, the replaced-vowel phonetic key, and the no-vowel phonetic key; and present the relevant Kana record to the user. | 25. A computer system for processing Japanese Kana language, comprising: a computer memory to store program code; and a processor to execute the program code to: receive at least one Kana character from a user; apply a Kana rule set to the at least one Kana character; define the at least one Kana character in an alphabetic language based on a sound of the at least one Kana character; generate a full phonetic key for the defined at least one Kana character; generate a replaced-vowel phonetic key by replacing a vowel in the full phonetic key; generate a no-vowel phonetic key by removing the vowel in the full phonetic key; process Kana records in a database to determine a relevant Kana record that has a phonetic key identical to at least one of the full phonetic key, the replaced-vowel phonetic key, and the no-vowel phonetic key; and present the relevant Kana record to the user. 36. The system of claim 25 , wherein the alphabetic language is English. | 0.95288 |
8,836,652 | 1 | 2 | 1. A method performed at an electronic device with a touch-sensitive surface, the method comprising: receiving a document from a server, the document including an embedded script; rendering and displaying the document at the electronic device and executing the embedded script, including: establishing a touchevent interface object that includes a plurality of touchlists; and upon detecting one or more touches on the touch-sensitive surface: updating the touchevent interface object with touch data, including values in two or more of the touchlists; and further executing the embedded script in accordance with the values in at least one of the two or more touchlists, wherein: the touchevent interface object includes a plurality of distinct touchlists, a respective touchlist including two or more concurrent touches; and updating the touchevent interface object with touch data includes updating values in two or more of the touchlists. | 1. A method performed at an electronic device with a touch-sensitive surface, the method comprising: receiving a document from a server, the document including an embedded script; rendering and displaying the document at the electronic device and executing the embedded script, including: establishing a touchevent interface object that includes a plurality of touchlists; and upon detecting one or more touches on the touch-sensitive surface: updating the touchevent interface object with touch data, including values in two or more of the touchlists; and further executing the embedded script in accordance with the values in at least one of the two or more touchlists, wherein: the touchevent interface object includes a plurality of distinct touchlists, a respective touchlist including two or more concurrent touches; and updating the touchevent interface object with touch data includes updating values in two or more of the touchlists. 2. The method of claim 1 , wherein the touchevent interface object is for a first respective displayed region of the document, the plurality of touchlists includes a first touchlist listing all touches on the touch-sensitive surface and a target touchlist listing only touches in the first respective displayed region of the document. | 0.819459 |
6,101,515 | 3 | 13 | 3. A method for automated learning of at least one term from an input set of documents, the method comprising the steps of: storing a classification system comprising a plurality of categories of terminology arranged in a hierarchy of categories so as to reflect associations among related categories; processing the input set of documents to generate contextual data by classifying the term in a plurality of categories of the classification system; and analyzing the contextual data by performing hierarchical clustering analysis on the selected categories of the hierarchy of categories in the classification system to identify a cluster of categories and to select a single category in the cluster from the plurality of selected categories to learn the term as the single category selected. | 3. A method for automated learning of at least one term from an input set of documents, the method comprising the steps of: storing a classification system comprising a plurality of categories of terminology arranged in a hierarchy of categories so as to reflect associations among related categories; processing the input set of documents to generate contextual data by classifying the term in a plurality of categories of the classification system; and analyzing the contextual data by performing hierarchical clustering analysis on the selected categories of the hierarchy of categories in the classification system to identify a cluster of categories and to select a single category in the cluster from the plurality of selected categories to learn the term as the single category selected. 13. The method as set forth in claim 3, wherein the step of analyzing the contextual data comprises the steps of: determining whether the term is ambiguous such that the contextual data for the term does not indicate classification in a single category; and removing the term from consideration for learning if the term is ambiguous. | 0.73445 |
8,296,127 | 14 | 16 | 14. A method, comprising: obtaining, via a processing module that is executable by a processor, a first amount of parallel training data for a learning component of a machine translation system; using the learning component of the machine translation system trained using said parallel data to determine translation parameters, including at least one probabilistic word dictionary; using said translation parameters to extract parallel sentences from a second corpus of nonparallel data, where said second corpus is larger than a database of said parallel training data; using said parallel sentences to create training data for said learning component of said machine translation system; training said learning component using said training data, and iteratively re-analyzing said comparable corpus using the system thus trained; continuing said iterative re-analyzing until training reaches a specified level. | 14. A method, comprising: obtaining, via a processing module that is executable by a processor, a first amount of parallel training data for a learning component of a machine translation system; using the learning component of the machine translation system trained using said parallel data to determine translation parameters, including at least one probabilistic word dictionary; using said translation parameters to extract parallel sentences from a second corpus of nonparallel data, where said second corpus is larger than a database of said parallel training data; using said parallel sentences to create training data for said learning component of said machine translation system; training said learning component using said training data, and iteratively re-analyzing said comparable corpus using the system thus trained; continuing said iterative re-analyzing until training reaches a specified level. 16. The method recited in claim 14 , wherein said continuing comprises terminating the iterative process when a translation system trained on the data stops improving. | 0.5 |
9,355,150 | 1 | 7 | 1. A method for producing solution documents, the method comprising: receiving, from a client system, at least one selection for specifying an issue or query regarding a computer system; selecting a first solution mapping from a plurality of solution mappings based on the at least one received selection, the first solution mapping specifying a plurality of document mappings, wherein (1) each of the plurality of solution mappings is associated with at least one document mapping and a set of content fragments, and (2) at least some of the plurality of solution mappings are associated with existing solution documents; retrieving one or more content fragments associated with each of the plurality of document mappings from a content database, wherein (1) the plurality of document mappings refers to at least a first document encoded in a first format and a second document encoded in a second format, and (2) at least one of the first and second formats is incompatible with the client system; producing a solution document in a format compatible with the client system, the solution document including at least the one or more content fragments; and providing the solution document to the client system, the solution document comprising at least some modifiable content pertaining to the selected issue or query; receiving, from the client system, modifications to at least one content fragment in the solution document; updating the at least one modified content fragment in the content database; and producing new solution documents to replace the existing solution documents for each of the plurality of solution mappings with one of the modified content fragments in its set of content fragments. | 1. A method for producing solution documents, the method comprising: receiving, from a client system, at least one selection for specifying an issue or query regarding a computer system; selecting a first solution mapping from a plurality of solution mappings based on the at least one received selection, the first solution mapping specifying a plurality of document mappings, wherein (1) each of the plurality of solution mappings is associated with at least one document mapping and a set of content fragments, and (2) at least some of the plurality of solution mappings are associated with existing solution documents; retrieving one or more content fragments associated with each of the plurality of document mappings from a content database, wherein (1) the plurality of document mappings refers to at least a first document encoded in a first format and a second document encoded in a second format, and (2) at least one of the first and second formats is incompatible with the client system; producing a solution document in a format compatible with the client system, the solution document including at least the one or more content fragments; and providing the solution document to the client system, the solution document comprising at least some modifiable content pertaining to the selected issue or query; receiving, from the client system, modifications to at least one content fragment in the solution document; updating the at least one modified content fragment in the content database; and producing new solution documents to replace the existing solution documents for each of the plurality of solution mappings with one of the modified content fragments in its set of content fragments. 7. The method of claim 1 , further comprising: sending the solution document to the client system in a web-based format for displaying on a web browser executing on the client system. | 0.836898 |
9,053,422 | 9 | 12 | 9. The method according to claim 1 , wherein the executing of the at least one selected model comprises at least one executing the model using code libraries, executing the model using external programs, and executing the model using visual machines. | 9. The method according to claim 1 , wherein the executing of the at least one selected model comprises at least one executing the model using code libraries, executing the model using external programs, and executing the model using visual machines. 12. The method according to claim 9 , wherein the virtual machines are accessed via a cloud server. | 0.565789 |
8,463,606 | 12 | 15 | 12. A method for managing interactions in a contact center, comprising: monitoring and analyzing, by a processor, a communication with a customer; verifying, by the processor, an identity of the customer based on the analyzed communication; detecting, by the processor, a topic or an emotional state of the customer or a contact center agent based on the analyzed communication; and providing, by the processor, real-time advice to the contact center agent based on the detected topic or the emotional state in response to the identity of the customer being verified. | 12. A method for managing interactions in a contact center, comprising: monitoring and analyzing, by a processor, a communication with a customer; verifying, by the processor, an identity of the customer based on the analyzed communication; detecting, by the processor, a topic or an emotional state of the customer or a contact center agent based on the analyzed communication; and providing, by the processor, real-time advice to the contact center agent based on the detected topic or the emotional state in response to the identity of the customer being verified. 15. The method of claim 12 , wherein providing real-time advice to the contact center agent further comprises providing, by the processor, an interface for allowing a supervisor to select the real-time advice provided to the contact center agent. | 0.5 |
9,542,165 | 8 | 10 | 8. The method of claim 1 , wherein each module includes a plurality of identifiers associated therewith. | 8. The method of claim 1 , wherein each module includes a plurality of identifiers associated therewith. 10. The method of claim 8 , wherein an identifier of the plurality of identifiers includes a universal unique identifier (UUID) that uniquely identifies a respective module. | 0.590047 |
8,607,136 | 1 | 2 | 1. A method, comprising: in response to tagging a document page displayed within a main window of a browser with one or more tags, associating, by a processing device, the one or more tags with one or more communities of a plurality of communities, the one or more communities selected from a list of available communities, each of the plurality of communities comprising a group of associated tags; storing the one or more tags in a storage device having information linking the document page and the one or more communities; and publishing the one or more tags within the one or more communities such that a member of at least one of the one or more communities is able to search within the storage device based on at least one of the one or more tags to identify and retrieve the document page. | 1. A method, comprising: in response to tagging a document page displayed within a main window of a browser with one or more tags, associating, by a processing device, the one or more tags with one or more communities of a plurality of communities, the one or more communities selected from a list of available communities, each of the plurality of communities comprising a group of associated tags; storing the one or more tags in a storage device having information linking the document page and the one or more communities; and publishing the one or more tags within the one or more communities such that a member of at least one of the one or more communities is able to search within the storage device based on at least one of the one or more tags to identify and retrieve the document page. 2. The method of claim 1 , further comprising: displaying the list of the available communities in a sidebar window which is communicatively coupled to the main window to allow a user to select the one or more communities from the list of the available communities. | 0.5 |
9,116,978 | 12 | 13 | 12. A computer-implemented method for facilitating cross-subsystem queries of a plurality of building automation subsystems, comprising: receiving a cross-subsystem query from an application; accessing a fact database that stores instance values for the plurality of building automation subsystems and a logical type for each of the stored instance values, wherein the logical type identifies a particular attribute of an ontological model described by the stored instance value and represents, in a flat format, a portion of the ontological model that provides semantic type information for the stored instance value; parsing the logical types in the fact database to obtain the semantic type information for the stored instance values; using the obtained semantic type information to identify one or more of the stored instance values relevant to the cross-subsystem query without requiring access to another database; recognizing that the identified instance values are provided by more than one of the plurality of building automation subsystems; and decomposing the cross-subsystem query into a plurality of subsystem queries using information from the fact database. | 12. A computer-implemented method for facilitating cross-subsystem queries of a plurality of building automation subsystems, comprising: receiving a cross-subsystem query from an application; accessing a fact database that stores instance values for the plurality of building automation subsystems and a logical type for each of the stored instance values, wherein the logical type identifies a particular attribute of an ontological model described by the stored instance value and represents, in a flat format, a portion of the ontological model that provides semantic type information for the stored instance value; parsing the logical types in the fact database to obtain the semantic type information for the stored instance values; using the obtained semantic type information to identify one or more of the stored instance values relevant to the cross-subsystem query without requiring access to another database; recognizing that the identified instance values are provided by more than one of the plurality of building automation subsystems; and decomposing the cross-subsystem query into a plurality of subsystem queries using information from the fact database. 13. The computer-implemented method of claim 12 , further comprising: determining ordering for the subsystem queries using information from the fact database. | 0.840726 |
7,925,975 | 4 | 5 | 4. The method of claim 1 wherein receiving a search request comprises: displaying a text entry mechanism; and receiving a text entry indicative of the search request. | 4. The method of claim 1 wherein receiving a search request comprises: displaying a text entry mechanism; and receiving a text entry indicative of the search request. 5. The method of claim 4 wherein returning the possible commands in a user selectable form comprises: displaying a user actuable interface element, for each possible command, that can be actuated by the user through a graphical user interface to perform the possible command; and displaying an associated command identifier, associated with each user actuable interface element, wherein the command identifier can be entered in the text entry mechanism to perform the possible command. | 0.5 |
10,109,278 | 1 | 3 | 1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated. | 1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated. 3. The system of claim 1 , wherein the physical computing device is further configured to synchronously present the paragraph of the electronic book and the portion of the audiobook from which the corresponding portion of the textual transcription was generated. | 0.5 |
6,053,951 | 37 | 38 | 37. The memory media of claim 36, wherein the program instructions further implement: receiving user input indicating a desire to change said configured graphical code portion; displaying parameter configuration information of said configured graphical code portion in said configuration panel; modifying said parameter configuration information in said configuration panel in response to user input; and automatically modifying said configured graphical code portion in response to said modifying said parameter configuration information. | 37. The memory media of claim 36, wherein the program instructions further implement: receiving user input indicating a desire to change said configured graphical code portion; displaying parameter configuration information of said configured graphical code portion in said configuration panel; modifying said parameter configuration information in said configuration panel in response to user input; and automatically modifying said configured graphical code portion in response to said modifying said parameter configuration information. 38. The memory media of claim 37, wherein the program instructions further implement: wherein said automatically modifying said configured graphical code portion in response to said modify said parameter configuration information includes selecting a new graphical code portion in response to said modifying said parameter configuration information. | 0.5 |
8,004,539 | 2 | 3 | 2. The method of claim 1 , further comprising: determining to display the transformation object. | 2. The method of claim 1 , further comprising: determining to display the transformation object. 3. The method of claim 2 , wherein the determining to display the transformation object comprises: determining a type of the graphical editing operation; and determining that the transformation object is associated with the type of the graphical editing operation. | 0.5 |
9,595,005 | 3 | 4 | 3. The method of claim 1 , further comprising coding a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle. | 3. The method of claim 1 , further comprising coding a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle. 4. The method of claim 3 , further comprising adding the coded second portion of the plurality of documents to the initial set. | 0.5 |
9,141,689 | 12 | 13 | 12. A system comprising: a communication analyzer to identify an element of original content of a written communication and to determine that the element of the original content of the written communication is incompatible with a selected persona style, wherein the selected persona style defines a communication style; a modification engine coupled to the communication analyzer, the modification engine to identify a substitute element, and propose the substitute element for replacement of the element of the original content for consideration by an author of the original content of the written communication, wherein the substitute element is identified based on a compatibility between the substitute element and the selected persona style, wherein the modification engine is further configured to modify the original content of the written communication to replace the element of the original content with the substitute element that is compatible with the selected persona style; and a hardware display device coupled to the modification engine, the hardware display device to display the proposal of the substitute element for replacement of the element of the original content for consideration to the author. | 12. A system comprising: a communication analyzer to identify an element of original content of a written communication and to determine that the element of the original content of the written communication is incompatible with a selected persona style, wherein the selected persona style defines a communication style; a modification engine coupled to the communication analyzer, the modification engine to identify a substitute element, and propose the substitute element for replacement of the element of the original content for consideration by an author of the original content of the written communication, wherein the substitute element is identified based on a compatibility between the substitute element and the selected persona style, wherein the modification engine is further configured to modify the original content of the written communication to replace the element of the original content with the substitute element that is compatible with the selected persona style; and a hardware display device coupled to the modification engine, the hardware display device to display the proposal of the substitute element for replacement of the element of the original content for consideration to the author. 13. The system of claim 12 , wherein the communication analyzer is further configured to perform linguistic analysis on the original content of the written communication to identify a plurality of elements of the original content of the written communication. | 0.620235 |
8,131,767 | 15 | 19 | 15. An augmentation system for augmenting web pages with rich media content, the system comprising: an input/output module for retrieving web pages, receiving requests, and transmitting augmented web pages and rich media content; an image augmentation module for analyzing a web page to identify a visual element that is a qualified visual element, determining a keyword associated with the qualified visual element, generating an association of the visual element and the keyword, and embedding the association in an augmented web page corresponding to the web page; an advertisement deliver module for receiving a request from a client computer corresponding to a pointer being positioned over the visual element in the augmented web page, responsive to receiving the signal, determining a piece rich media content relevant to the visual element by searching for the advertisement using the keyword, and transmitting the piece of media content to the client computer for display. | 15. An augmentation system for augmenting web pages with rich media content, the system comprising: an input/output module for retrieving web pages, receiving requests, and transmitting augmented web pages and rich media content; an image augmentation module for analyzing a web page to identify a visual element that is a qualified visual element, determining a keyword associated with the qualified visual element, generating an association of the visual element and the keyword, and embedding the association in an augmented web page corresponding to the web page; an advertisement deliver module for receiving a request from a client computer corresponding to a pointer being positioned over the visual element in the augmented web page, responsive to receiving the signal, determining a piece rich media content relevant to the visual element by searching for the advertisement using the keyword, and transmitting the piece of media content to the client computer for display. 19. The augmentation system of claim 15 , wherein the image augmentation module is further configured for embedding computer code in the augmented web page for monitoring user pointer movement on a display of the web page. | 0.681948 |
8,427,509 | 1 | 8 | 1. A method for embedding symbols of a message into a document containing a set of glyphs, comprising: representing a glyph in a document as a distance field; representing a symbol in a message to be embedded in the document as a modification of a subset of values in the distance field; and modifying the subset of values in the distance field according to the modification to produce a modified glyph in a modified document, wherein the symbol in the message is embedded in the modified glyph, wherein steps of the method are performed by a processor. | 1. A method for embedding symbols of a message into a document containing a set of glyphs, comprising: representing a glyph in a document as a distance field; representing a symbol in a message to be embedded in the document as a modification of a subset of values in the distance field; and modifying the subset of values in the distance field according to the modification to produce a modified glyph in a modified document, wherein the symbol in the message is embedded in the modified glyph, wherein steps of the method are performed by a processor. 8. The method of claim 1 , wherein the modification defines new values for the subset of values in the distance field. | 0.83046 |
9,262,719 | 1 | 22 | 1. A reasoning engine comprising: a data interface configured to acquire environment data from sensors, the environment data representing a first and a second aspect of an environment; at least one inference engine coupled within the data interface and configured to: receive an inquiry relating to the first and second aspect of the environment; recognize the first and second aspects as first and second target objects respectively, each having object attributes, as a function of the environment data; select a reasoning rules set from available reasoning rules sets as a function of the environment data and object attributes of the first and second target objects, and establish a hypothesis according to the selected reasoning rules set, the hypothesis representing that the first and second target objects have a suspected correlation; and configure an output device to present the hypothesis along with a reasoning supporting the hypothesis. | 1. A reasoning engine comprising: a data interface configured to acquire environment data from sensors, the environment data representing a first and a second aspect of an environment; at least one inference engine coupled within the data interface and configured to: receive an inquiry relating to the first and second aspect of the environment; recognize the first and second aspects as first and second target objects respectively, each having object attributes, as a function of the environment data; select a reasoning rules set from available reasoning rules sets as a function of the environment data and object attributes of the first and second target objects, and establish a hypothesis according to the selected reasoning rules set, the hypothesis representing that the first and second target objects have a suspected correlation; and configure an output device to present the hypothesis along with a reasoning supporting the hypothesis. 22. The engine of claim 1 , wherein the hypothesis comprises a representation of a creative work. | 0.912613 |
8,347,392 | 1 | 8 | 1. A non-transitory computer readable storage medium, comprising executable instructions to: perform an automated analysis of program instructions using a security module to analyze application output prior to the program instructions being invoked, wherein the automated analysis includes an automated analysis of injection vulnerabilities, an automated analysis of potential repetitive attacks including session ID guessing, credential guessing, click fraud and site probing, an automated analysis of sensitive information, and an automated analysis of specific HTTP attributes; select and insert protective instructions into the program instructions based on the automated analysis of the injection vulnerabilities, wherein the protective instructions comprise a call that generates a security event during runtime; and utilize a runtime security module to detect and respond to attacks by analyzing the generated security event during execution of the program instructions. | 1. A non-transitory computer readable storage medium, comprising executable instructions to: perform an automated analysis of program instructions using a security module to analyze application output prior to the program instructions being invoked, wherein the automated analysis includes an automated analysis of injection vulnerabilities, an automated analysis of potential repetitive attacks including session ID guessing, credential guessing, click fraud and site probing, an automated analysis of sensitive information, and an automated analysis of specific HTTP attributes; select and insert protective instructions into the program instructions based on the automated analysis of the injection vulnerabilities, wherein the protective instructions comprise a call that generates a security event during runtime; and utilize a runtime security module to detect and respond to attacks by analyzing the generated security event during execution of the program instructions. 8. The compute readable storage medium of claim 1 , wherein the executable instructions include executable instructions to defuse an attack. | 0.713115 |
8,413,126 | 1 | 5 | 1. In a compiler, a method of computing a shortest path expression in a loop having a plurality of expressions, comprising: identifying candidate expressions from the plurality of loop expressions; partitioning candidate expressions into sets, including a first set; computing a cost matrix as a function of the sets of the candidate expressions, the cost matrix indicating cost of generating each candidate expression from other candidate expressions and having a row for each candidate expression and a column for each candidate expression; finding one or more paths through the cost matrix; detecting cycles in the paths; if there are cycles in the paths, breaking the cycles; generating one or more shortest path expressions as a function of the paths; and replacing one or more of the expressions in the loop with the shortest path expressions. | 1. In a compiler, a method of computing a shortest path expression in a loop having a plurality of expressions, comprising: identifying candidate expressions from the plurality of loop expressions; partitioning candidate expressions into sets, including a first set; computing a cost matrix as a function of the sets of the candidate expressions, the cost matrix indicating cost of generating each candidate expression from other candidate expressions and having a row for each candidate expression and a column for each candidate expression; finding one or more paths through the cost matrix; detecting cycles in the paths; if there are cycles in the paths, breaking the cycles; generating one or more shortest path expressions as a function of the paths; and replacing one or more of the expressions in the loop with the shortest path expressions. 5. The method of claim 1 , wherein finding one or more paths includes selecting paths through the cost matrix which produce the lowest cost for each expression. | 0.545455 |
9,065,914 | 15 | 19 | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: selecting a spoken dialog application from a plurality of spoken dialog applications; transmitting, over a network, an identification of the selected spoken dialog application, the spoken dialog application having a grammar identifier; selecting a grammar from a plurality of grammars based on the grammar identifier, wherein the grammar is provided by the selected spoken dialog application and chosen from a predetermined group of grammars based upon information provided by the selected spoken dialog application; transmitting digitized user speech over the network while receiving user speech which is digitized into the digitized user speech; receiving partially synthesized speech in response to the digitized user speech, wherein the selected spoken dialog application recognizes the digitized user speech using the grammar; and receiving final synthesized speech in response to the digitized user speech, wherein the receiving of the final synthesized speech occurs after receiving the partially synthesized speech. | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: selecting a spoken dialog application from a plurality of spoken dialog applications; transmitting, over a network, an identification of the selected spoken dialog application, the spoken dialog application having a grammar identifier; selecting a grammar from a plurality of grammars based on the grammar identifier, wherein the grammar is provided by the selected spoken dialog application and chosen from a predetermined group of grammars based upon information provided by the selected spoken dialog application; transmitting digitized user speech over the network while receiving user speech which is digitized into the digitized user speech; receiving partially synthesized speech in response to the digitized user speech, wherein the selected spoken dialog application recognizes the digitized user speech using the grammar; and receiving final synthesized speech in response to the digitized user speech, wherein the receiving of the final synthesized speech occurs after receiving the partially synthesized speech. 19. The computer-readable storage device of claim 15 , wherein the spoken dialog application carries on a dialog with a user communicating with a client device. | 0.711191 |
9,679,002 | 1 | 11 | 1. A method of managing digital data, the method comprising: searching, by a processor, a plurality of data sets comprising digital data; recording, by the processor, a hit into an index for each occurrence of a unique object in one of the plurality of data sets, wherein each of the plurality of data sets comprises a numbered sequence of objects, wherein said objects are represented by unique machine-readable object values, and wherein said hit comprises an ordinal number of an occurrence of said unique object and at least one of: a value of a previous object that is positioned one unit before said unique object and a value of a next object that is positioned one unit after said unique object; recording hit data into the index, wherein the hit data comprises at least one of: values of additional previous objects with respect to the unique object and values of additional next objects with respect to the unique object, for N objects where N is at least one; restoring at least one of past relationship and future relationship with respect to the unique object based on the recorded hit data; searching for at least two occurrences of the unique object in indexed data set, wherein the searching comprises gathering a value of the unique object, retrieving hits with the occurrence of the unique object in the indexed data set and other data sets from among the data sets; and displaying the retrieved hits as search results, obtained based on the searching or recording the retrieved relationships into the memory available for a processor or an algorithm capable of analyzing the co-occurrence of the unique object with each of the N next or previous objects in the indexed data set or transferring the retrieved relationship to a processor, wherein the search results or the memory records further comprise the restored relationships. | 1. A method of managing digital data, the method comprising: searching, by a processor, a plurality of data sets comprising digital data; recording, by the processor, a hit into an index for each occurrence of a unique object in one of the plurality of data sets, wherein each of the plurality of data sets comprises a numbered sequence of objects, wherein said objects are represented by unique machine-readable object values, and wherein said hit comprises an ordinal number of an occurrence of said unique object and at least one of: a value of a previous object that is positioned one unit before said unique object and a value of a next object that is positioned one unit after said unique object; recording hit data into the index, wherein the hit data comprises at least one of: values of additional previous objects with respect to the unique object and values of additional next objects with respect to the unique object, for N objects where N is at least one; restoring at least one of past relationship and future relationship with respect to the unique object based on the recorded hit data; searching for at least two occurrences of the unique object in indexed data set, wherein the searching comprises gathering a value of the unique object, retrieving hits with the occurrence of the unique object in the indexed data set and other data sets from among the data sets; and displaying the retrieved hits as search results, obtained based on the searching or recording the retrieved relationships into the memory available for a processor or an algorithm capable of analyzing the co-occurrence of the unique object with each of the N next or previous objects in the indexed data set or transferring the retrieved relationship to a processor, wherein the search results or the memory records further comprise the restored relationships. 11. The method of claim 1 , wherein at least one of a Location and a LocationOffset are stored in the hit and wherein, in the searching, the at least one of the Location and the LocationOffset are retrieved and locations of search objects are spatially organized. | 0.896701 |
7,698,654 | 13 | 21 | 13. A computer-implemented method for navigating a set of recordings stored on a handheld storage and retrieval device on a display of the handheld storage and retrieval device, comprising: on the display of the handheld device, presenting an initial screen for displaying only a hierarchical menu comprising only two hierarchical levels of a plurality of hierarchical levels of the set of recordings, the initial screen having initial headers representing a first one of the plurality of hierarchical levels and oriented according to a first orientation, said initial headers providing top-level categories for filtering the set of recordings, wherein each of said initial headers includes an association with a child list, whereby said initial headers form a band of lists represented by the initial headers; navigating the initial headers according to the first orientation; presenting a list of elements representing a second one of the plurality of hierarchical levels oriented according to a second orientation different from the first orientation, the list of elements associated with a currently selected header of the initial headers as a child list for the currently selected header; navigating the list of elements according to the second orientation; selecting an element from the list of elements; in response to said selecting the element, presenting a new screen having the list of elements as element headers displayed according to the first orientation, the element headers including the selected element as a new currently selected header of the element headers and displayed in an order determined by the selecting; and presenting a second list of elements representing a third one of the plurality of hierarchical levels and associated with the new currently selected header of the element headers as a child list for the new currently selected header, the second list of elements displayed according to the second orientation, the new screen displaying only the element headers and the second list of elements; and repeating navigating and selecting until a particular hierarchical level comprising atomic elements is displayed in the second orientation, wherein upon selection of an atomic element of the atomic elements, the display screen displays only the particular hierarchical level in the first orientation with the selected atomic element as an active header and an information display box containing information about the selected atomic element. | 13. A computer-implemented method for navigating a set of recordings stored on a handheld storage and retrieval device on a display of the handheld storage and retrieval device, comprising: on the display of the handheld device, presenting an initial screen for displaying only a hierarchical menu comprising only two hierarchical levels of a plurality of hierarchical levels of the set of recordings, the initial screen having initial headers representing a first one of the plurality of hierarchical levels and oriented according to a first orientation, said initial headers providing top-level categories for filtering the set of recordings, wherein each of said initial headers includes an association with a child list, whereby said initial headers form a band of lists represented by the initial headers; navigating the initial headers according to the first orientation; presenting a list of elements representing a second one of the plurality of hierarchical levels oriented according to a second orientation different from the first orientation, the list of elements associated with a currently selected header of the initial headers as a child list for the currently selected header; navigating the list of elements according to the second orientation; selecting an element from the list of elements; in response to said selecting the element, presenting a new screen having the list of elements as element headers displayed according to the first orientation, the element headers including the selected element as a new currently selected header of the element headers and displayed in an order determined by the selecting; and presenting a second list of elements representing a third one of the plurality of hierarchical levels and associated with the new currently selected header of the element headers as a child list for the new currently selected header, the second list of elements displayed according to the second orientation, the new screen displaying only the element headers and the second list of elements; and repeating navigating and selecting until a particular hierarchical level comprising atomic elements is displayed in the second orientation, wherein upon selection of an atomic element of the atomic elements, the display screen displays only the particular hierarchical level in the first orientation with the selected atomic element as an active header and an information display box containing information about the selected atomic element. 21. A computing device comprising a display, an input mechanism, and means for performing the method of claim 13 . | 0.779923 |
7,797,625 | 3 | 4 | 3. The method of claim 2 , wherein said message formats further include formatted display. | 3. The method of claim 2 , wherein said message formats further include formatted display. 4. The method of claim 3 , wherein computer instructions for steps (a) and (b) are implemented in Java script. | 0.918276 |
9,817,896 | 47 | 49 | 47. The search server of claim 40 further comprising: logic executed by the processor for obtaining targeted information about the thing; and, logic executed by the processor for communicating the targeted information for display by the user computing device. | 47. The search server of claim 40 further comprising: logic executed by the processor for obtaining targeted information about the thing; and, logic executed by the processor for communicating the targeted information for display by the user computing device. 49. The search server of claim 47 , the targeted information being displayed only when the relative popularity score exceeds a given threshold. | 0.5 |
9,653,067 | 15 | 20 | 15. A system comprising: one or more processing devices; and a computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing the one or more processing devices to: receive input information that represents a multi-dimensional communication, that comprises at least two different communication domains; detect based on contents of the input information, at least two different communication inputs, corresponding to the at least two different communication domains; determine one or more corresponding weighted values for each of the at least two different communication inputs, with a weighted value based on a communication domain weight value divided by a time interval between receiving a first one of the at least two different communication inputs and a subsequent one of the at least two different communication inputs; assign confidence levels to the at least two different communications inputs, with the confidence levels being based on the weighted values; determine which of the confidence levels are below a confidence threshold; execute one or more disambiguation rules to disambiguate between the at least two different communication inputs when the assigned confidence levels are below the confidence threshold; and generate a communication instruction to perform an action that is specified by the multi-dimensional communication. | 15. A system comprising: one or more processing devices; and a computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing the one or more processing devices to: receive input information that represents a multi-dimensional communication, that comprises at least two different communication domains; detect based on contents of the input information, at least two different communication inputs, corresponding to the at least two different communication domains; determine one or more corresponding weighted values for each of the at least two different communication inputs, with a weighted value based on a communication domain weight value divided by a time interval between receiving a first one of the at least two different communication inputs and a subsequent one of the at least two different communication inputs; assign confidence levels to the at least two different communications inputs, with the confidence levels being based on the weighted values; determine which of the confidence levels are below a confidence threshold; execute one or more disambiguation rules to disambiguate between the at least two different communication inputs when the assigned confidence levels are below the confidence threshold; and generate a communication instruction to perform an action that is specified by the multi-dimensional communication. 20. The system of claim 15 , further comprising instructions for causing the one or more processing devices to: transmit the communication instruction to a networked device for execution of the communication instruction. | 0.748284 |
6,154,754 | 1 | 2 | 1. An AIU structure synthesizer of semantic information from multimedia non-textual documents comprising: an error corrector for receiving raw AIU's extracted from said non-textual documents and for correcting errors in said raw AIU's; a primitive identifier connected to said error corrector, for assigning semantics to outputs of said error corrector; a basic synthesizer connected to said primitive identifier, for grouping related outputs of said primitive identifier; and, an abstract synthesizer connected to said basic synthesizer, for grouping related outputs of said basic synthesizer. | 1. An AIU structure synthesizer of semantic information from multimedia non-textual documents comprising: an error corrector for receiving raw AIU's extracted from said non-textual documents and for correcting errors in said raw AIU's; a primitive identifier connected to said error corrector, for assigning semantics to outputs of said error corrector; a basic synthesizer connected to said primitive identifier, for grouping related outputs of said primitive identifier; and, an abstract synthesizer connected to said basic synthesizer, for grouping related outputs of said basic synthesizer. 2. An AIU structure synthesizer of semantic information from multimedia documents as claimed in claim 1 wherein said error corrector comprises: a plurality of state machines each state machine for receiving a pattern specified in a rule and for providing an output; a composite state machine for unioning together each of said output from each of said plurality of state machines; an execute state machine for providing pattern fitting by receiving input AIU's and a composite output from said composite state machine and by providing corrected raw AIU's and a syntax error; and, a substitute single character for receiving said syntax error and for providing a single character substitution to said input AIU's. | 0.680717 |
8,761,988 | 6 | 7 | 6. The method of claim 1 , wherein determining the candidate power cost associated with operating the powertrain system at the candidate engine torque comprises: determining a preferred powertrain operating point in response to the output torque request when the engine is operating at the candidate engine torque; and determining the candidate power cost at the preferred powertrain operating point. | 6. The method of claim 1 , wherein determining the candidate power cost associated with operating the powertrain system at the candidate engine torque comprises: determining a preferred powertrain operating point in response to the output torque request when the engine is operating at the candidate engine torque; and determining the candidate power cost at the preferred powertrain operating point. 7. The method of claim 6 , wherein determining the preferred powertrain operating point in response to the output torque request when the engine is operating at the candidate engine torque comprises determining preferred torque commands for the torque machines and determining a preferred battery power for a high-voltage battery coupled to the torque machines in response to the output torque request when the engine is operating at the candidate engine torque. | 0.5 |
8,706,475 | 11 | 13 | 11. An apparatus for identifying a table of contents in a document, the apparatus comprising: a computer programmed to perform a method including deriving an ordered sequence of text fragments from the document and selecting a table of contents as a contiguous sub-sequence of the ordered sequence of text fragments wherein the selecting employs the criteria: (i) entries defined by text fragments of the table of contents each have a link to a target text fragment having textual similarity with the entry, (ii) no target text fragment lies within the table of contents, and (iii) the target text fragments have an ascending ordering corresponding to an ascending ordering of the entries defining the target text fragments. | 11. An apparatus for identifying a table of contents in a document, the apparatus comprising: a computer programmed to perform a method including deriving an ordered sequence of text fragments from the document and selecting a table of contents as a contiguous sub-sequence of the ordered sequence of text fragments wherein the selecting employs the criteria: (i) entries defined by text fragments of the table of contents each have a link to a target text fragment having textual similarity with the entry, (ii) no target text fragment lies within the table of contents, and (iii) the target text fragments have an ascending ordering corresponding to an ascending ordering of the entries defining the target text fragments. 13. The apparatus as set forth in claim 11 , wherein the method performed by the computer further includes: constructing a structured document including the ordered sequence of text fragments, the structured document being structured in accordance with the selected table of contents and having sections associated with the corresponding target text fragments. | 0.810726 |
8,923,609 | 7 | 12 | 7. A non-transitory computer-readable storage medium containing a program, which, when executed on a processor is configured to perform an operation for processing video image data, the operation comprising: detecting a plurality of objects in the video image data; and for each object: generating a primitive event symbol stream identifying one or more primitive events engaged in by the object, wherein each primitive event represents a behavior engaged in by the object, generating a phase-space symbol stream representing quantitative characteristics of the object, wherein the phase-space symbol stream for the object indicates a trajectory of that object in the video image data over time, and combining the primitive event symbol stream and the phase-space symbol stream to generate a vector representation of the behavior engaged in by the object as depicted in the video image data. | 7. A non-transitory computer-readable storage medium containing a program, which, when executed on a processor is configured to perform an operation for processing video image data, the operation comprising: detecting a plurality of objects in the video image data; and for each object: generating a primitive event symbol stream identifying one or more primitive events engaged in by the object, wherein each primitive event represents a behavior engaged in by the object, generating a phase-space symbol stream representing quantitative characteristics of the object, wherein the phase-space symbol stream for the object indicates a trajectory of that object in the video image data over time, and combining the primitive event symbol stream and the phase-space symbol stream to generate a vector representation of the behavior engaged in by the object as depicted in the video image data. 12. The computer-readable storage medium of claim 7 , wherein the primitive events are described using a formal language grammar. | 0.756604 |
8,359,326 | 19 | 22 | 19. A system comprising: a data processing apparatus; a memory coupled to the data processing apparatus, and including instructions, which, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a first search query during a search session, the first search query comprising a first set of search terms, each term in the first search query having a respective first ordinal position, wherein each first ordinal position of each search term in the first set defines a position of the search term in the first search query relative to other search terms in the first search query; receiving a subsequent search query during the search session after receipt of the first search query, the subsequent search query being another search query and being received separately from the first search query, the subsequent search query comprising a second set of search terms, each term in the subsequent search query having a respective second ordinal position, wherein each second ordinal position of each search term in the second set defines a position of the search term in the subsequent search query relative to other search terms in the subsequent search query; determining that the second set of search terms in the subsequent search query includes one or more differing search terms, each of the one or more differing search terms being a search term that is not included in the first set; determining common terms between the first search query and the subsequent search query based on a comparison of the first ordinal positions to the second ordinal positions and the first set of search terms and the second set of search terms, wherein each of the common terms is a search term that is included in the first set and in the second set and has a first ordinal position in the first set equal to a second ordinal position in the second set; identifying adjacent common terms, the adjacent common terms being common terms that are located adjacent to one another in the first set and adjacent to one another in the second set; submitting the adjacent common terms for a bigram analysis of the subsequent search query; and excluding the one or more differing search terms from the bigram analysis of the subsequent search query. | 19. A system comprising: a data processing apparatus; a memory coupled to the data processing apparatus, and including instructions, which, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a first search query during a search session, the first search query comprising a first set of search terms, each term in the first search query having a respective first ordinal position, wherein each first ordinal position of each search term in the first set defines a position of the search term in the first search query relative to other search terms in the first search query; receiving a subsequent search query during the search session after receipt of the first search query, the subsequent search query being another search query and being received separately from the first search query, the subsequent search query comprising a second set of search terms, each term in the subsequent search query having a respective second ordinal position, wherein each second ordinal position of each search term in the second set defines a position of the search term in the subsequent search query relative to other search terms in the subsequent search query; determining that the second set of search terms in the subsequent search query includes one or more differing search terms, each of the one or more differing search terms being a search term that is not included in the first set; determining common terms between the first search query and the subsequent search query based on a comparison of the first ordinal positions to the second ordinal positions and the first set of search terms and the second set of search terms, wherein each of the common terms is a search term that is included in the first set and in the second set and has a first ordinal position in the first set equal to a second ordinal position in the second set; identifying adjacent common terms, the adjacent common terms being common terms that are located adjacent to one another in the first set and adjacent to one another in the second set; submitting the adjacent common terms for a bigram analysis of the subsequent search query; and excluding the one or more differing search terms from the bigram analysis of the subsequent search query. 22. The system of claim 19 , wherein the data processing apparatus further performs operations comprising: identifying substitute search terms comprising differing terms from the second set of search terms that are not part of the first set of search terms, each substitute search term having a second ordinal position equal to that of a first ordinal position of a search term of the first search query; determining whether any of the substitute search terms is immediately adjacent to another substitute search term or an additional search term; and in response to determining that one substitute search term is immediately adjacent to another substitute search term or an additional search term, performing bigram analysis on the adjacent substitute search terms separately from the adjacent common terms. | 0.5 |
7,480,860 | 9 | 10 | 9. The method as defined in claim 8 , wherein the organization-level transform enables subscription-specific content filtering of a subscription-level document. | 9. The method as defined in claim 8 , wherein the organization-level transform enables subscription-specific content filtering of a subscription-level document. 10. The method as defined in claim 9 , wherein decomposing the document comprises applying a presentation-level transform to the organization-level document to create a presentation-level document. | 0.5 |
9,154,506 | 6 | 7 | 6. A data security client (DSC) system for secure generation and transmission, over a communication network, of data, the DSC system comprising: a processor; a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which on execution cause the processor to: receive a data payload; receive a secure passkey from a client user; process the data payload to extract an obfuscated query and data from the data payload wherein at least one of a table and a field of the data is randomized; decipher an executable query from the obfuscated query based on the secure passkey; restructure the data, based on the secure passkey, by reconstructing at least one of the table and at least one of the field of the data which is randomized; execute the executable query on the restructured data to generate a document; and provide at least one of a client user and the client device with an access of the document. | 6. A data security client (DSC) system for secure generation and transmission, over a communication network, of data, the DSC system comprising: a processor; a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which on execution cause the processor to: receive a data payload; receive a secure passkey from a client user; process the data payload to extract an obfuscated query and data from the data payload wherein at least one of a table and a field of the data is randomized; decipher an executable query from the obfuscated query based on the secure passkey; restructure the data, based on the secure passkey, by reconstructing at least one of the table and at least one of the field of the data which is randomized; execute the executable query on the restructured data to generate a document; and provide at least one of a client user and the client device with an access of the document. 7. The DSC system as claimed in claim 6 , wherein the instructions, on execution, further cause the processor to: process the data payload to extract an access control list wherein the access control list includes an access allowed white-list, and an access disallowed black-list of the client users authorized to access the document; and provide access of the document based on the access control list. | 0.514458 |
8,539,359 | 87 | 100 | 87. A machine system configured for performing prespecified operations wherein at least a portion of the machine system includes a data processing machine configured to perform at least part of the prespecified operations of the machine system, the machine system comprising: a user monitoring subsystem configured to automatically repeatedly monitor at least one of recent states of and recent locations and/or other recent surroundings of a corresponding first user of the machine system and to automatically repeatedly record report records corresponding to the monitored recent states and/or recent locations and/or other recent surroundings of the first user, wherein the automatically repeated monitorings are carried out transparently by the user monitoring subsystem without need for diverting focused attention of the user to aiding the monitorings; and an invitations and/or suggestions presenting subsystem configured to repeatedly automatically present to the first user, immediately actionable on invitations and/or acceptable suggestions to respectively connect with system-identified and telecommunications-mediated forums and/or information providing sources based on automatically repeated determinations by the machine system of a recent context of the first user where the automatically repeated determinations of user context are based on at least some of the recorded report records corresponding to the monitored recent states and/or recent locations and/or other recent surroundings of the first user and the recorded report records used as the basis for the repeated determinations of recent context are generated no more than at least one of: 3 hours prior to said determination of user context; and a determined time duration prior to said determination of user context, the determined time duration being determined based on a currently active profile characterizing the first user. | 87. A machine system configured for performing prespecified operations wherein at least a portion of the machine system includes a data processing machine configured to perform at least part of the prespecified operations of the machine system, the machine system comprising: a user monitoring subsystem configured to automatically repeatedly monitor at least one of recent states of and recent locations and/or other recent surroundings of a corresponding first user of the machine system and to automatically repeatedly record report records corresponding to the monitored recent states and/or recent locations and/or other recent surroundings of the first user, wherein the automatically repeated monitorings are carried out transparently by the user monitoring subsystem without need for diverting focused attention of the user to aiding the monitorings; and an invitations and/or suggestions presenting subsystem configured to repeatedly automatically present to the first user, immediately actionable on invitations and/or acceptable suggestions to respectively connect with system-identified and telecommunications-mediated forums and/or information providing sources based on automatically repeated determinations by the machine system of a recent context of the first user where the automatically repeated determinations of user context are based on at least some of the recorded report records corresponding to the monitored recent states and/or recent locations and/or other recent surroundings of the first user and the recorded report records used as the basis for the repeated determinations of recent context are generated no more than at least one of: 3 hours prior to said determination of user context; and a determined time duration prior to said determination of user context, the determined time duration being determined based on a currently active profile characterizing the first user. 100. The machine system of claim 87 wherein the monitored recent states and/or recent locations and/or other recent surroundings of the first user can be respectively monitored by respective different monitoring devices that are proximate to the first user. | 0.879116 |
9,064,006 | 1 | 2 | 1. A method for providing natural language query translation, the method comprising: training a statistical model according to a plurality of query click log data, the plurality of click log data being mined to train the statistical model for domain detection in the absence of available in-domain data; receiving a natural language query; translating the natural language query into a search query according to the statistical model; performing the search query; and providing at least one result associated with performing the search query. | 1. A method for providing natural language query translation, the method comprising: training a statistical model according to a plurality of query click log data, the plurality of click log data being mined to train the statistical model for domain detection in the absence of available in-domain data; receiving a natural language query; translating the natural language query into a search query according to the statistical model; performing the search query; and providing at least one result associated with performing the search query. 2. The method of claim 1 , wherein the natural language query is received as text. | 0.702899 |
9,146,989 | 1 | 6 | 1. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared outlier results: for both datasets the greatest number of plays in the past D days is in a category C, for predetermined values of D, C; for both datasets the greatest number of plays in the past D days is in a category C, for values of D, C determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in categories C1 and C2 and no goods in category C3, for predetermined values of C1, C2, C3; both datasets have goods in categories C1 and C2 and no goods in category C3, for values of C1, C2, C3 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a predetermined value of C1; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a value of C1 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. | 1. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared outlier results: for both datasets the greatest number of plays in the past D days is in a category C, for predetermined values of D, C; for both datasets the greatest number of plays in the past D days is in a category C, for values of D, C determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in categories C1 and C2 and no goods in category C3, for predetermined values of C1, C2, C3; both datasets have goods in categories C1 and C2 and no goods in category C3, for values of C1, C2, C3 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a predetermined value of C1; both datasets have goods in category C1 but no playlist containing any goods in category C1, for a value of C1 determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. 6. The configured medium of claim 1 , wherein the process comprises visualizing at least one of the following: playlist content over time, play frequency over time, play count over time. | 0.857143 |
9,131,045 | 24 | 27 | 24. A system for providing captioned telephone service to an assisted user communicating with a hearing person, the system comprising: a relay for providing captioned text, the relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a captioned device processor; a microphone; a speaker; a visually readable display in communication with the captioned device processor; an activation switch in communication with the captioned device processor and selectable by an assisted user to initiate a captioning service; the captioned device enabling the assisted user to use the captioned device to facilitate a telephonic communication via the first communication link between the user of the captioned device and a hearing person and facilitating a captioned call in which a text translation of words spoken by the hearing person is presented via the visually readable display, the captioned device configured to perform the steps of: (i) facilitating a voice telephone call on the first communication link between the captioned device and the hearing person during which voice communication occurs between the hearing person and the assisted user and during which words spoken by the hearing person are received by the processor via the first communication link; (ii) after the first communication link is established and while the voice telephone call is progressing, receiving an indication that the activation switch has been activated; (iii) after receiving the indication that the activation switch has been activated, passing the words spoken by the hearing person to the relay via the second communication link; (iv) receiving a text message corresponding to the words spoken by the hearing person from the relay; and (v) displaying the text message on the display within sight of the assisted user; wherein the words spoken by the hearing person and received by the processor during each of the telephone call and the captioned call are broadcast via the speaker substantially in real time as the words are received by the processor; the relay configured to perform the steps of: (i) generating a text message stream corresponding to the words spoken by the hearing person and received via the second communication link; (ii) displaying the text message stream on the relay display screen; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device. | 24. A system for providing captioned telephone service to an assisted user communicating with a hearing person, the system comprising: a relay for providing captioned text, the relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a captioned device processor; a microphone; a speaker; a visually readable display in communication with the captioned device processor; an activation switch in communication with the captioned device processor and selectable by an assisted user to initiate a captioning service; the captioned device enabling the assisted user to use the captioned device to facilitate a telephonic communication via the first communication link between the user of the captioned device and a hearing person and facilitating a captioned call in which a text translation of words spoken by the hearing person is presented via the visually readable display, the captioned device configured to perform the steps of: (i) facilitating a voice telephone call on the first communication link between the captioned device and the hearing person during which voice communication occurs between the hearing person and the assisted user and during which words spoken by the hearing person are received by the processor via the first communication link; (ii) after the first communication link is established and while the voice telephone call is progressing, receiving an indication that the activation switch has been activated; (iii) after receiving the indication that the activation switch has been activated, passing the words spoken by the hearing person to the relay via the second communication link; (iv) receiving a text message corresponding to the words spoken by the hearing person from the relay; and (v) displaying the text message on the display within sight of the assisted user; wherein the words spoken by the hearing person and received by the processor during each of the telephone call and the captioned call are broadcast via the speaker substantially in real time as the words are received by the processor; the relay configured to perform the steps of: (i) generating a text message stream corresponding to the words spoken by the hearing person and received via the second communication link; (ii) displaying the text message stream on the relay display screen; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device. 27. The system of claim 24 wherein the microphone and the speaker are in communication with the captioned device processor. | 0.888182 |
10,146,872 | 8 | 11 | 8. A system for predicting search results quality, the system comprising: at least one processor configured by machine-readable instructions to: receive a search query from a user; obtain a plurality of search results from each of a plurality of content sources based on the search query, wherein the plurality of search results from each content source is ranked based on their relevance scores with respect to the search query; normalize a distribution of the relevance scores of the plurality of search results for each of the plurality of content sources in each position of the ranking by building an order-statistic model based on a first set of the plurality of search results from the each content source and by generating estimated relevance scores of a second set of the plurality of search results from the each content source based on the order-statistic model, wherein the first set is different from the second set; compute a metric for each of the plurality of content sources based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the respective plurality of search results from the content source and the search query, rank the plurality of content sources based on the metrics associated with the plurality of content sources, identify one or more search results from at least one content source that has a higher ranking, and provide the one or more search results to the user as a response to the search query. | 8. A system for predicting search results quality, the system comprising: at least one processor configured by machine-readable instructions to: receive a search query from a user; obtain a plurality of search results from each of a plurality of content sources based on the search query, wherein the plurality of search results from each content source is ranked based on their relevance scores with respect to the search query; normalize a distribution of the relevance scores of the plurality of search results for each of the plurality of content sources in each position of the ranking by building an order-statistic model based on a first set of the plurality of search results from the each content source and by generating estimated relevance scores of a second set of the plurality of search results from the each content source based on the order-statistic model, wherein the first set is different from the second set; compute a metric for each of the plurality of content sources based on the normalized distribution of the relevance scores, wherein the metric indicates a relevance between the respective plurality of search results from the content source and the search query, rank the plurality of content sources based on the metrics associated with the plurality of content sources, identify one or more search results from at least one content source that has a higher ranking, and provide the one or more search results to the user as a response to the search query. 11. The system of claim 8 , wherein the order-statistic model is built based on the relevance scores of the first set and the positions of the first set in the ranking. | 0.641026 |
7,522,967 | 1 | 6 | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. 6. The method of claim 1 , further comprising classifying audio pieces into categories in response to user input received during rendering of the associated audio summaries. | 0.816348 |
6,070,160 | 5 | 6 | 5. The apparatus of claim 4, wherein the digital image data is transferable as an ASCII text file directly executable by the remote computer as assembled source code. | 5. The apparatus of claim 4, wherein the digital image data is transferable as an ASCII text file directly executable by the remote computer as assembled source code. 6. The apparatus of claim 5, wherein the ASCII text file is self destructive during successful execution. | 0.5 |
8,825,405 | 4 | 5 | 4. The method of claim 3 , further comprising: determining whether the first road intersects the second road; and generating a portion of the routing graph that includes the first and second route links when the first and second roads intersect, the first and second route links being connected within the routing graph by a node. | 4. The method of claim 3 , further comprising: determining whether the first road intersects the second road; and generating a portion of the routing graph that includes the first and second route links when the first and second roads intersect, the first and second route links being connected within the routing graph by a node. 5. The method of claim 4 , further comprising: obtaining, when the first and second roads fail to intersect, a third positional data element associated with a third time, the first time being subsequent to the third time; and determining whether the first road intersects a road associated with the third positional data element. | 0.601695 |
10,049,097 | 20 | 21 | 20. A system comprising: a scanner configured to: scan a document to generate a scanned image, the document having text information; and a computing device in communication with the scanner, wherein the computing device comprises a multi-layered OCR (Optical Character Recognition) document generation module, configured to: receive the scanned image from the scanner; generate a binary image from the scanned image; perform a morphological dilation operation on the binary image to create one or more text groups using a horizontal structuring element and a vertical structuring element; apply OCR on each text group to create the corresponding OCR layer; combine the one or more OCR layers while creating a multi-layered OCR file; and superimpose the combined OCR layers over the scanned image to generate the multi-layered OCR file, wherein the multi-layered OCR file allows a user to select a portion of text from the multi-layered OCR file. | 20. A system comprising: a scanner configured to: scan a document to generate a scanned image, the document having text information; and a computing device in communication with the scanner, wherein the computing device comprises a multi-layered OCR (Optical Character Recognition) document generation module, configured to: receive the scanned image from the scanner; generate a binary image from the scanned image; perform a morphological dilation operation on the binary image to create one or more text groups using a horizontal structuring element and a vertical structuring element; apply OCR on each text group to create the corresponding OCR layer; combine the one or more OCR layers while creating a multi-layered OCR file; and superimpose the combined OCR layers over the scanned image to generate the multi-layered OCR file, wherein the multi-layered OCR file allows a user to select a portion of text from the multi-layered OCR file. 21. The system as claimed in claim 20 , wherein the multi-layered OCR document generation module is configured to: dilate the binary image with the horizontal structuring element for merging one or more nearby adjacent text regions along a horizontal axis, wherein the horizontal structuring element has a shorter width with respect to text size in order to prevent merging of one or more farther adjacent text information along the horizontal axis; and dilate the horizontally dilated processed image with the vertical structuring element for merging one or more nearby adjacent text regions along a vertical axis, wherein the vertical structuring element has a larger height with respect to text size in order to enable merging of one or more nearby adjacent text regions along the vertical axis. | 0.5 |
8,347,245 | 1 | 2 | 1. A computer-implemented method for generating hardware description language (HDL) code, the method comprising: receiving an executable, graphical model having a plurality of blocks including a frame-enabled block that processes frame-based input data, the frame-enabled block implementable in hardware in a plurality of ways, the plurality of ways in which the frame-enabled block is implementable in hardware include: a fully parallelized way that uses a plurality of first parallel hardware components, a fully serialized way that uses a first serial hardware component, and a combination serialized and parallelized way that uses a plurality of second parallel hardware components and a second serial hardware component; receiving a selected preference for influencing a way in which the frame-enabled block is implemented in hardware, where: the selected preference is free from affecting execution of the frame-enabled block in the model, and the selected preference causes the frame-enabled block to be implemented in hardware in a particular way of the plurality of ways; and generating, using a processor of a computer, the HDL code for the frame-enabled block of the model, the generating including implementing the frame-enabled block in hardware in the particular way that satisfies the selected preference, the particular way selected from the group consisting of: the fully parallelized way, in which the plurality of first parallel hardware components are included in the hardware implementation of the frame-enabled block, the fully serialized way, in which the first serial hardware component is included in the hardware implementation of the frame-enabled block, and the combination serialized and parallelized way, in which the second serial hardware component and the plurality of second parallel hardware components are included in the hardware implementation of the frame-enabled block. | 1. A computer-implemented method for generating hardware description language (HDL) code, the method comprising: receiving an executable, graphical model having a plurality of blocks including a frame-enabled block that processes frame-based input data, the frame-enabled block implementable in hardware in a plurality of ways, the plurality of ways in which the frame-enabled block is implementable in hardware include: a fully parallelized way that uses a plurality of first parallel hardware components, a fully serialized way that uses a first serial hardware component, and a combination serialized and parallelized way that uses a plurality of second parallel hardware components and a second serial hardware component; receiving a selected preference for influencing a way in which the frame-enabled block is implemented in hardware, where: the selected preference is free from affecting execution of the frame-enabled block in the model, and the selected preference causes the frame-enabled block to be implemented in hardware in a particular way of the plurality of ways; and generating, using a processor of a computer, the HDL code for the frame-enabled block of the model, the generating including implementing the frame-enabled block in hardware in the particular way that satisfies the selected preference, the particular way selected from the group consisting of: the fully parallelized way, in which the plurality of first parallel hardware components are included in the hardware implementation of the frame-enabled block, the fully serialized way, in which the first serial hardware component is included in the hardware implementation of the frame-enabled block, and the combination serialized and parallelized way, in which the second serial hardware component and the plurality of second parallel hardware components are included in the hardware implementation of the frame-enabled block. 2. The method of claim 1 wherein the selected preference is one of a group consisting of: reducing implementation area on a target device, reducing power consumption of the target device, improving latency, and increasing throughput. | 0.5 |
8,631,305 | 18 | 26 | 18. A device comprising: a memory to store a block of words that are generated as a result of an forward error correction operation, each word, of the block of words, including a plurality of samples, a particular one of the plurality of samples including encoded bits and reliability bits, the reliability bits identifying a level of reliability of the encoded bits; and one or more components to: obtain a word from the block of words within traffic, identify, in a random manner, a first segment of the word, the first segment including a first subset of samples of a plurality of samples associated with the word, select one or more first samples, from the first subset of samples, associated with one or more of first lowest reliability bits within the first subset of samples, identify a second segment associated with the word, the second segment including a second subset of samples of the plurality of samples associated with the word, select one or more second samples, from the second subset of samples, associated with one or more of second lowest reliability bits within the second subset of samples, identify a third segment associated with the word, the third segment including a third subset of samples of the plurality of samples associated with the word, select one or more third samples, from the third subset of samples, associated with one or more of third lowest reliability bits within the third subset of samples, identify lowest reliability bits within the one or more first lowest reliability bits, the one or more second lowest reliability bits, and the one or more third lowest reliability bits, create a merged subset of samples based on selected samples from the one or more first samples, the one or more second samples and the one or more third samples, the selected samples corresponding to the lowest reliability bits, select at least one sample from the merged subset, generate two or more candidate words based on the at least one sample, and process the word using the two or more candidate words. | 18. A device comprising: a memory to store a block of words that are generated as a result of an forward error correction operation, each word, of the block of words, including a plurality of samples, a particular one of the plurality of samples including encoded bits and reliability bits, the reliability bits identifying a level of reliability of the encoded bits; and one or more components to: obtain a word from the block of words within traffic, identify, in a random manner, a first segment of the word, the first segment including a first subset of samples of a plurality of samples associated with the word, select one or more first samples, from the first subset of samples, associated with one or more of first lowest reliability bits within the first subset of samples, identify a second segment associated with the word, the second segment including a second subset of samples of the plurality of samples associated with the word, select one or more second samples, from the second subset of samples, associated with one or more of second lowest reliability bits within the second subset of samples, identify a third segment associated with the word, the third segment including a third subset of samples of the plurality of samples associated with the word, select one or more third samples, from the third subset of samples, associated with one or more of third lowest reliability bits within the third subset of samples, identify lowest reliability bits within the one or more first lowest reliability bits, the one or more second lowest reliability bits, and the one or more third lowest reliability bits, create a merged subset of samples based on selected samples from the one or more first samples, the one or more second samples and the one or more third samples, the selected samples corresponding to the lowest reliability bits, select at least one sample from the merged subset, generate two or more candidate words based on the at least one sample, and process the word using the two or more candidate words. 26. The device of claim 18 , where, when selecting the at least one sample, the one or more components are to: determine that a first sample within the merged subset and a second sample, within the merged subset, are associated with a lowest level of reliability, randomly select, as the at least one sample, the first sample or the second sample when the first sample and the second sample are associated with the lowest level of reliability, the random selection permitting an equal probability that the at least one sample is associated with the first subset, the second subset, or the third subset. | 0.655212 |
8,682,901 | 1 | 2 | 1. A method of indexing documents of a document collection in an indexing system that includes a plurality of index servers, the method comprising: determining a phrase posting list associated with a first phrase, the phrase posting list identifying documents of the document collection associated with the first phrase; dividing the phrase posting list for the first phrase into a plurality of different shards, each shard identifying a subset of the documents identified by the posting list; storing each different shard of the phrase posting list for the first phrase on a corresponding different index server; storing a plurality of shards of different phrase posting lists on a first index server; storing a plurality of shards of different phrase posting lists on a second index server; and within each of the first and second index servers, for each shard of a phrase posting list, ordering the shard according to document identifiers of the documents included in the shard. | 1. A method of indexing documents of a document collection in an indexing system that includes a plurality of index servers, the method comprising: determining a phrase posting list associated with a first phrase, the phrase posting list identifying documents of the document collection associated with the first phrase; dividing the phrase posting list for the first phrase into a plurality of different shards, each shard identifying a subset of the documents identified by the posting list; storing each different shard of the phrase posting list for the first phrase on a corresponding different index server; storing a plurality of shards of different phrase posting lists on a first index server; storing a plurality of shards of different phrase posting lists on a second index server; and within each of the first and second index servers, for each shard of a phrase posting list, ordering the shard according to document identifiers of the documents included in the shard. 2. The method of claim 1 , wherein the first phrase is a multi-word phrase. | 0.950787 |
9,053,202 | 5 | 6 | 5. The method as recited in claim 1 , further comprising, in response to the user using the particular web property, wherein such user is authorized to provide translations for such particular web property, providing a response for presenting a second translation for a second one of the translatable text strings as a replacement for the second translatable text string within the one or more web pages, wherein the second translation is a best translation of a plurality of translations, provided by a plurality of users of the particular web property, for the second one of the translatable text strings within the context of the one or more web pages of the particular web property. | 5. The method as recited in claim 1 , further comprising, in response to the user using the particular web property, wherein such user is authorized to provide translations for such particular web property, providing a response for presenting a second translation for a second one of the translatable text strings as a replacement for the second translatable text string within the one or more web pages, wherein the second translation is a best translation of a plurality of translations, provided by a plurality of users of the particular web property, for the second one of the translatable text strings within the context of the one or more web pages of the particular web property. 6. The method as recited in claim 5 , wherein the second translatable text string is associated with a variable and the second translation is based at least in part on a current value of the variable for the one or more web pages. | 0.5 |
7,575,433 | 1 | 10 | 1. A sports skill evaluation system, comprising: an inputting section for inputting, while course selection items displayed on a screen are selected, required data for each of the items regarding a user; a basic database for storing personal basic data of the user including a level, a match experience, an age and a sex inputted through said inputting section; a coefficient table in which application coefficients including level-based coefficients, age-based coefficients and sex-based coefficients are stored in advance; application coefficient calculation means for referring to said coefficient table based on the level, age and sex inputted through said inputting section to determine respective individual application coefficients; skill item point calculation means for calculating, from a score according to a result of a match of the user inputted through said inputting section and the individual application coefficients determined by said application coefficient calculation section, a skill item point for each of skills required for the match; skill diagnosis graph production means for producing diagnosis graphs for the individual skills from the skill item points for the individual skills calculated by said skill item point calculation means; comment pattern designation value calculation means for converting the level, match experience, age and sex inputted through said inputting section into numerical values and calculating comment pattern designation values for the individual skill items based on the numerical values in accordance with a predetermined calculation expression; a comment table in which a plurality of comments to be presented each as a comment to a user are stored such that the comments are classified for the individual skill items and are numbered for the individual comments; and comment extraction means for extracting a comment of a number corresponding to each of the comment pattern designation values calculated by said comment pattern designation value calculation means for each of the skill items from said comment table. | 1. A sports skill evaluation system, comprising: an inputting section for inputting, while course selection items displayed on a screen are selected, required data for each of the items regarding a user; a basic database for storing personal basic data of the user including a level, a match experience, an age and a sex inputted through said inputting section; a coefficient table in which application coefficients including level-based coefficients, age-based coefficients and sex-based coefficients are stored in advance; application coefficient calculation means for referring to said coefficient table based on the level, age and sex inputted through said inputting section to determine respective individual application coefficients; skill item point calculation means for calculating, from a score according to a result of a match of the user inputted through said inputting section and the individual application coefficients determined by said application coefficient calculation section, a skill item point for each of skills required for the match; skill diagnosis graph production means for producing diagnosis graphs for the individual skills from the skill item points for the individual skills calculated by said skill item point calculation means; comment pattern designation value calculation means for converting the level, match experience, age and sex inputted through said inputting section into numerical values and calculating comment pattern designation values for the individual skill items based on the numerical values in accordance with a predetermined calculation expression; a comment table in which a plurality of comments to be presented each as a comment to a user are stored such that the comments are classified for the individual skill items and are numbered for the individual comments; and comment extraction means for extracting a comment of a number corresponding to each of the comment pattern designation values calculated by said comment pattern designation value calculation means for each of the skill items from said comment table. 10. A sports skill evaluation system according to claim 1 , wherein said inputting section acquires basic user data of the user including the level, match experience, age and sex through a web site of the Internet, and said comment extraction section presents the extracted comment on the web site. | 0.781845 |
8,892,596 | 1 | 8 | 1. A method comprising: identifying, in a first document and by one or more processors of one or more server devices, a reference to a second document, the second document being different than the first document; identifying, by one or more processors of the one or more server devices, that the reference to the second document is associated with a relation indicator, the relation indicator being associated with a link that references the second document; determining, based on identifying that the reference to the second document is associated with the relation indicator and by one or more processors of the one or more server devices, that content of the second document is related to content of the first document, the determining that the content of the second document is related to the content of the first document comprising: translating the first document to obtain a translated first document, the translated first document being in a language that matches a language of the second document; comparing the translated first document to the second document to obtain a measure of similarity between the translated first document and the second document; and determining, based on the comparing, that the content of the second document is related to the content of the first document when the measure of similarity satisfies a particular similarity threshold; and processing, by one or more processors of the one or more server devices, the second document based on determining that the content of the second document is related to the content of the first document. | 1. A method comprising: identifying, in a first document and by one or more processors of one or more server devices, a reference to a second document, the second document being different than the first document; identifying, by one or more processors of the one or more server devices, that the reference to the second document is associated with a relation indicator, the relation indicator being associated with a link that references the second document; determining, based on identifying that the reference to the second document is associated with the relation indicator and by one or more processors of the one or more server devices, that content of the second document is related to content of the first document, the determining that the content of the second document is related to the content of the first document comprising: translating the first document to obtain a translated first document, the translated first document being in a language that matches a language of the second document; comparing the translated first document to the second document to obtain a measure of similarity between the translated first document and the second document; and determining, based on the comparing, that the content of the second document is related to the content of the first document when the measure of similarity satisfies a particular similarity threshold; and processing, by one or more processors of the one or more server devices, the second document based on determining that the content of the second document is related to the content of the first document. 8. The method of claim 1 , further comprising: identifying selection activity regarding at least one of the first document or the second document, where, when determining that the content of the second document is related to the content of the first document, the method further includes: determining that the content of the second document is related to the content of the first document based on the identified selection activity. | 0.764192 |
7,734,614 | 2 | 3 | 2. The search apparatus according to claim 1 , wherein the indexing term storage unit stores, in association with each of the indexing terms, each document including that indexing term and a partial score corresponding to that indexing term in each document in the index database, and the calculation unit calculates, for each document, the score of that document on the basis of the partial scores corresponding to the first search string and the second search string of each of the search term pairs. | 2. The search apparatus according to claim 1 , wherein the indexing term storage unit stores, in association with each of the indexing terms, each document including that indexing term and a partial score corresponding to that indexing term in each document in the index database, and the calculation unit calculates, for each document, the score of that document on the basis of the partial scores corresponding to the first search string and the second search string of each of the search term pairs. 3. The search apparatus according to claim 2 , wherein the calculation unit calculates the score of the document on the basis of a smaller one of the partial scores corresponding to the first search string and the second search string for each of the search term pairs. | 0.5 |
7,711,573 | 1 | 39 | 1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 39. The system of claim 1 , wherein the resume comprises a replacement resume. | 0.921053 |
8,505,090 | 10 | 13 | 10. A computer-implemented method, comprising: identifying, at an information-capturing system, at least one source document corresponding to at least one rendered document of one or more rendered documents, wherein each text capture indication of one or more text capture indications includes text captured from the at least one source document; and the information-capturing system presenting a list of text capture entries based upon the one or more text capture indications, wherein at least one text capture entry includes an indication of the at least one source document for text of a text capture indication and a number of documents matching the text. | 10. A computer-implemented method, comprising: identifying, at an information-capturing system, at least one source document corresponding to at least one rendered document of one or more rendered documents, wherein each text capture indication of one or more text capture indications includes text captured from the at least one source document; and the information-capturing system presenting a list of text capture entries based upon the one or more text capture indications, wherein at least one text capture entry includes an indication of the at least one source document for text of a text capture indication and a number of documents matching the text. 13. The method of claim 10 , wherein the one or more text capture indications comprises capturing an audio clip of text being read aloud. | 0.503623 |
8,631,028 | 15 | 17 | 15. A non-transitory computer readable medium having a computer product for processing one or more inputted XPath queries against one or more XML documents, which when executed by a computing device having a plurality of hardware processors (CPU) and memory, comprises: program code the execution of which generates a first index that comprises unique root to leaf paths (SUM-Index), a second index that comprises tree nodes grouped by unique path identifiers (PS-Index), and a third index that comprises values of the tree nodes grouped by path identifiers (PV-Index) from the XML document, wherein the SUM-Index and the PS-Index and the PV-Index each have at least one unique path identifier (PID) and are linked together by at least one PID originating from the SUM-Index; program code that annotates the SUM-Index with the PID; program code that distributes the SUM-Index, PS-Index, and PV-Index across a plurality of CPUs addressed by PID; program code that executes parsing and splitting of an XPath query at articulation points into multiple partial queries; program code that determines cursor type index access methods; program code that examines the SUM-Index to generate a list of applicable PID in the PS-Index and the PV-Index that satisfies partial query segments; program code that generates a set of ancestor-descendant PID identifiers list from a SUM-Index tree to initialize a simple cursor or a multi-predicate branching path cursor (MPBPC); program code that accesses a distributed SUM-Index, PS-Index and PV-Index across the plurality of CPUs addressed by PID; program code that generates a result sequence using the simple cursor or MPBPC cursor from a PS-Index tree; program code that filters the result sequence of nodes by using an associated PV-Index tree; and program code that produces one or more outputted XML documents from a final result sequences of nodes. | 15. A non-transitory computer readable medium having a computer product for processing one or more inputted XPath queries against one or more XML documents, which when executed by a computing device having a plurality of hardware processors (CPU) and memory, comprises: program code the execution of which generates a first index that comprises unique root to leaf paths (SUM-Index), a second index that comprises tree nodes grouped by unique path identifiers (PS-Index), and a third index that comprises values of the tree nodes grouped by path identifiers (PV-Index) from the XML document, wherein the SUM-Index and the PS-Index and the PV-Index each have at least one unique path identifier (PID) and are linked together by at least one PID originating from the SUM-Index; program code that annotates the SUM-Index with the PID; program code that distributes the SUM-Index, PS-Index, and PV-Index across a plurality of CPUs addressed by PID; program code that executes parsing and splitting of an XPath query at articulation points into multiple partial queries; program code that determines cursor type index access methods; program code that examines the SUM-Index to generate a list of applicable PID in the PS-Index and the PV-Index that satisfies partial query segments; program code that generates a set of ancestor-descendant PID identifiers list from a SUM-Index tree to initialize a simple cursor or a multi-predicate branching path cursor (MPBPC); program code that accesses a distributed SUM-Index, PS-Index and PV-Index across the plurality of CPUs addressed by PID; program code that generates a result sequence using the simple cursor or MPBPC cursor from a PS-Index tree; program code that filters the result sequence of nodes by using an associated PV-Index tree; and program code that produces one or more outputted XML documents from a final result sequences of nodes. 17. The computer readable medium of claim 15 , wherein the program code that executes the query searches the PV-Index that is a search index that is partitioned on PID, or has a composite key of PID and preorder. | 0.626761 |
7,827,172 | 1 | 16 | 1. A method comprising the steps of: receiving a particular query that comprises one or more terms; in response to receiving the particular query: making a first plurality of comparisons, wherein each comparison in the first plurality of comparisons is based on the particular query and a different query of a plurality of queries, wherein the number of the first plurality of comparisons and the number of the plurality of queries is the same; making a second plurality of comparisons, wherein each comparison in the second plurality of comparisons is based on the particular query and a different query of the plurality of queries; based on the first plurality of comparisons, generating a first numerical value; based on the second plurality of comparisons, generating a second numerical value that is different than the first numerical value; determining a ratio between the first numerical value and the second numerical value; and ranking documents in a document set based, at least in part, on the ratio; wherein the steps are performed by one or more computer systems. | 1. A method comprising the steps of: receiving a particular query that comprises one or more terms; in response to receiving the particular query: making a first plurality of comparisons, wherein each comparison in the first plurality of comparisons is based on the particular query and a different query of a plurality of queries, wherein the number of the first plurality of comparisons and the number of the plurality of queries is the same; making a second plurality of comparisons, wherein each comparison in the second plurality of comparisons is based on the particular query and a different query of the plurality of queries; based on the first plurality of comparisons, generating a first numerical value; based on the second plurality of comparisons, generating a second numerical value that is different than the first numerical value; determining a ratio between the first numerical value and the second numerical value; and ranking documents in a document set based, at least in part, on the ratio; wherein the steps are performed by one or more computer systems. 16. The method of claim 1 , wherein one or more comparisons of the first plurality of comparisons include determinations of whether (1) said each query contains the particular query, (2) the particular query is not equal to said each query, (3) said each query does not begin with the particular query, and (4) said each query does not end with the particular query. | 0.543641 |
8,229,878 | 15 | 16 | 15. A computer implemented method as in claim 13 , wherein said interpretation process is further comprising the steps of: starting by translating, by said at least one computer, each sub-formula of said formulas in a rewriting area, in accordance with the algebraic mechanisms of substitution and replacement, and continues up to a literal formula appears; stopping by reducing said literal formula in said rewriting area of said at least one computer, in accordance with the laws of form calculus of indications for computing its normal form, which is its value; by laws of form, said value is unique. | 15. A computer implemented method as in claim 13 , wherein said interpretation process is further comprising the steps of: starting by translating, by said at least one computer, each sub-formula of said formulas in a rewriting area, in accordance with the algebraic mechanisms of substitution and replacement, and continues up to a literal formula appears; stopping by reducing said literal formula in said rewriting area of said at least one computer, in accordance with the laws of form calculus of indications for computing its normal form, which is its value; by laws of form, said value is unique. 16. A computer implemented method as in claim 15 , wherein said step of translating each sub-formula is further comprising the steps of: applying, by said at least one computer, formal definitions from the tree of all applicable definitions, to sub-formulas of said formula in said rewriting area; considering formal definitions as conditional rewriting rules, to transform said formula while preserving its value; combining and comparing different results from a tree of all applicable definitions, to produce a unique meaningful value; and coding said unique value of said formula, by said at least one computer. | 0.5 |
10,055,686 | 12 | 13 | 12. The system of claim 11 , wherein the objective function increases a conditional likelihood of clicked documents given respective queries. | 12. The system of claim 11 , wherein the objective function increases a conditional likelihood of clicked documents given respective queries. 13. The system of claim 12 , wherein the objective function reduces a conditional likelihood of non-clicked documents given the respective queries. | 0.5 |
7,716,532 | 1 | 13 | 1. A system for increasing the utility of a communication between communicating parties, the system comprising: a reliability analyzer that predicts reliability of communication channels, the reliability analyzer including a reliability predictor that generates a probability that a communication will be completed with predetermined desired transmission qualities and a reliability prediction integrator that updates one or more pieces of information that are employed in selecting a communication channel for communication and updates an expected utility that is computed without regard to reliability; and a channel manager that selects the communication channel based on analyzing extrinsic data in association with the communication channel maximizing utility of communication between the communicating parties as a function of the reliability prediction. | 1. A system for increasing the utility of a communication between communicating parties, the system comprising: a reliability analyzer that predicts reliability of communication channels, the reliability analyzer including a reliability predictor that generates a probability that a communication will be completed with predetermined desired transmission qualities and a reliability prediction integrator that updates one or more pieces of information that are employed in selecting a communication channel for communication and updates an expected utility that is computed without regard to reliability; and a channel manager that selects the communication channel based on analyzing extrinsic data in association with the communication channel maximizing utility of communication between the communicating parties as a function of the reliability prediction. 13. The system of claim 1 , wherein the utility is further based upon preferences of one or more of the communicating parties. | 0.854503 |
8,686,992 | 4 | 5 | 4. A computer based system for 3D shape matching and retrieval, comprising: one or more processors; a 3D model repository configured to store a plurality of 3D models; a model processing engine configured to generate representations of a query 3D model and 3D models in the 3D model repository; and a shape retrieval engine configured to retrieve the matching 3D models from the 3D model repository using at least the representation of the query 3D model and representations of the 3D models in the 3D model repository, the shape retrieval engine comprising: a comparator configured to: calculate a first correlation by combining first coefficients associated with the representation of the query 3D model and second coefficients associated with representations of 3D models in the repository to obtain a first output and calculating an inverse rotational Fourier transform of the first output to obtain the first correlation, wherein a number of the first and second coefficients depends on a specified first bandwidth associated with the transform; calculate a first similarity score based on the first correlation; rank one or more 3D models based on the first similarity score; calculating a second correlation by combining third coefficients associated with the representation of the query 3D model and fourth coefficients associated with representations of 3D models in the repository to obtain a second output and calculating an inverse rotational Fourier transform of the second output to obtain the second correlation, wherein a number of the third and fourth coefficients depends on a specified second bandwidth associated with the transform, the second bandwidth being higher than the first bandwidth; calculating, by the one or more processing devices, a second similarity score based on the second correlation; ranking, by the one or more processing devices, the 3D models used in the second correlation based on the second similarity score. | 4. A computer based system for 3D shape matching and retrieval, comprising: one or more processors; a 3D model repository configured to store a plurality of 3D models; a model processing engine configured to generate representations of a query 3D model and 3D models in the 3D model repository; and a shape retrieval engine configured to retrieve the matching 3D models from the 3D model repository using at least the representation of the query 3D model and representations of the 3D models in the 3D model repository, the shape retrieval engine comprising: a comparator configured to: calculate a first correlation by combining first coefficients associated with the representation of the query 3D model and second coefficients associated with representations of 3D models in the repository to obtain a first output and calculating an inverse rotational Fourier transform of the first output to obtain the first correlation, wherein a number of the first and second coefficients depends on a specified first bandwidth associated with the transform; calculate a first similarity score based on the first correlation; rank one or more 3D models based on the first similarity score; calculating a second correlation by combining third coefficients associated with the representation of the query 3D model and fourth coefficients associated with representations of 3D models in the repository to obtain a second output and calculating an inverse rotational Fourier transform of the second output to obtain the second correlation, wherein a number of the third and fourth coefficients depends on a specified second bandwidth associated with the transform, the second bandwidth being higher than the first bandwidth; calculating, by the one or more processing devices, a second similarity score based on the second correlation; ranking, by the one or more processing devices, the 3D models used in the second correlation based on the second similarity score. 5. The system of claim 4 , wherein the 3D model repository comprises a plurality of user generated models. | 0.87844 |
8,762,161 | 1 | 15 | 1. A computerized method for visualization of an interaction categorization, of an at least one interaction captured within an environment, the method comprising: capturing the at least one interaction by a computing platform executing one or more computer applications; receiving definition of at least two categories related to key-phrases and criteria for an interaction to be assigned to the at least two categories; based on the criteria, categorizing the at least one interaction to the at least two categories; determining by machine learning a category network of connections between the at least two categories; extracting an at least one key-phrase from at least one of the at least two categories; determining a key-phrase network; determining a layout for the key-phrase network; and visualizing the category network by the key-phrases. | 1. A computerized method for visualization of an interaction categorization, of an at least one interaction captured within an environment, the method comprising: capturing the at least one interaction by a computing platform executing one or more computer applications; receiving definition of at least two categories related to key-phrases and criteria for an interaction to be assigned to the at least two categories; based on the criteria, categorizing the at least one interaction to the at least two categories; determining by machine learning a category network of connections between the at least two categories; extracting an at least one key-phrase from at least one of the at least two categories; determining a key-phrase network; determining a layout for the key-phrase network; and visualizing the category network by the key-phrases. 15. The method of claim 1 wherein a connection between two key-phrases is determined according to a key-phrase relations network model. | 0.588415 |
8,117,185 | 7 | 8 | 7. The computer system of claim 6 , wherein the identified additional terms are ranked based at least in part on a relationship network corresponding to search query object. | 7. The computer system of claim 6 , wherein the identified additional terms are ranked based at least in part on a relationship network corresponding to search query object. 8. The computer system of claim 7 , wherein the relationship network is generated from a pre-existing knowledgebase. | 0.623377 |
8,037,003 | 1 | 5 | 1. A computer based system that identifies one or more workflows for a print process, comprising: an intake component that receives an incomplete data set from one or more sources, wherein the incomplete data set is related to a production workflow for a print process; a case classification and recommendation component that maps the incomplete data set into a case log vector in a case constraint space, utilizes a latent semantic index transformation to map the case log vector into a semantic vector with reduced dimensionality, classifies the semantic vector into an existing case cluster whose cluster centroid vector has the largest cosine product with the semantic vector, and returns one or more representative workflows of the existing case cluster as one or more recommended workflow solutions; at least one predefined cluster that is created by mapping previously collected data into one or more data vectors, mapping the one or more data vectors into one or more semantic data vectors and clustering the one or more semantic data vectors into at least one group based at least in part upon one or more mutual correlations, wherein the each of the at least one cluster is associated with at least one solution; and an online recommendation system that provides one or more solutions via correlation of the incomplete data set to one or more predefined data clusters, wherein the solution is a workflow that completely defines a print process automated by at least one automation device. | 1. A computer based system that identifies one or more workflows for a print process, comprising: an intake component that receives an incomplete data set from one or more sources, wherein the incomplete data set is related to a production workflow for a print process; a case classification and recommendation component that maps the incomplete data set into a case log vector in a case constraint space, utilizes a latent semantic index transformation to map the case log vector into a semantic vector with reduced dimensionality, classifies the semantic vector into an existing case cluster whose cluster centroid vector has the largest cosine product with the semantic vector, and returns one or more representative workflows of the existing case cluster as one or more recommended workflow solutions; at least one predefined cluster that is created by mapping previously collected data into one or more data vectors, mapping the one or more data vectors into one or more semantic data vectors and clustering the one or more semantic data vectors into at least one group based at least in part upon one or more mutual correlations, wherein the each of the at least one cluster is associated with at least one solution; and an online recommendation system that provides one or more solutions via correlation of the incomplete data set to one or more predefined data clusters, wherein the solution is a workflow that completely defines a print process automated by at least one automation device. 5. The computer based system according to claim 1 , wherein the one or more recommended workflow solutions are assigned a confidence score, wherein the confidence score is defined as Score ( x ) = 1 + d β‘ ( x , c β‘ ( x ) ) 2 , wherein the semantic vector corresponding to the incoming case is x, the associated cluster centroid vector of x is c(x), and the cosine product between vector x and y in the semantic constraint space is d(x, y). | 0.530983 |
8,230,338 | 13 | 14 | 13. A computer program product comprising a computer usable storage medium storing computer usable program code for game determining tag relevance for social bookmarking, the computer program product comprising: computer usable program code for rendering a game user interface in connection with content in a content browser; computer usable program code for providing a list of tags previously associated with the content in the game user interface for a game participant and receiving relevance values for the tags through the game user interface provided by the game participant for each of the tags; computer usable program code for comparing the relevance values to relevance values provided by others to generate a score for the game participant and presenting the score in the game user interface; and, computer usable program code for applying the received relevance values to the tags to improve quality for each of the tags in association with the content. | 13. A computer program product comprising a computer usable storage medium storing computer usable program code for game determining tag relevance for social bookmarking, the computer program product comprising: computer usable program code for rendering a game user interface in connection with content in a content browser; computer usable program code for providing a list of tags previously associated with the content in the game user interface for a game participant and receiving relevance values for the tags through the game user interface provided by the game participant for each of the tags; computer usable program code for comparing the relevance values to relevance values provided by others to generate a score for the game participant and presenting the score in the game user interface; and, computer usable program code for applying the received relevance values to the tags to improve quality for each of the tags in association with the content. 14. The computer program product of claim 13 , further comprising: computer usable program code for receiving a specification of a new tag in association with the content; and, computer usable program code for adding the new tag to the tags in association with the content to improve a quantity of tags associated with the content. | 0.714162 |
9,537,706 | 14 | 16 | 14. The method of claim 1 wherein populating a successfully paired database with information for each of the successfully paired end user clients includes populating the successfully paired end user clients database with information collected during use of the matching service by the successfully paired end user client and which is indicative of non-profile related end user client interactions via the matching service. | 14. The method of claim 1 wherein populating a successfully paired database with information for each of the successfully paired end user clients includes populating the successfully paired end user clients database with information collected during use of the matching service by the successfully paired end user client and which is indicative of non-profile related end user client interactions via the matching service. 16. The method of claim 14 wherein the non-profile related end user client interactions include a number of messaging related actions. | 0.790625 |
7,552,862 | 1 | 6 | 1. A computer readable storage medium that facilitates user profile management, comprising: a profile component that facilitates creation and storage of an electronic profile of a user based in part on user interaction via electronic-based tools; and a control component that dynamically controls access to portions of the profile as part of an information exchange session based on an active negotiation with a merchant requesting access thereto, the merchant providing an incentive based on an amount of the profile exposed to the merchant wherein a value of the incentive is negotiated based on quality of the user information exposed, the portions of the profile includes one or more spam rules of a spam filter associated with the user that when exposed enable the merchant to dynamically control the spam filter to facilitate transmission of content to the user through the spam filter. | 1. A computer readable storage medium that facilitates user profile management, comprising: a profile component that facilitates creation and storage of an electronic profile of a user based in part on user interaction via electronic-based tools; and a control component that dynamically controls access to portions of the profile as part of an information exchange session based on an active negotiation with a merchant requesting access thereto, the merchant providing an incentive based on an amount of the profile exposed to the merchant wherein a value of the incentive is negotiated based on quality of the user information exposed, the portions of the profile includes one or more spam rules of a spam filter associated with the user that when exposed enable the merchant to dynamically control the spam filter to facilitate transmission of content to the user through the spam filter. 6. The computer readable storage medium of claim 1 , further comprising an aggregation component that receives and stores user interaction data in the profile for control by the control component. | 0.635688 |
9,798,721 | 9 | 12 | 9. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, and the program instructions are readable by a computing device to cause the computing device to perform a method comprising: receiving a QR code based on the encoded representation of the bilingual text; converting the QR code to the encoded representation of the bilingual text; receiving the encoded representation of a bilingual text which comprises a first set of characters in a Latin-based language and a second set of characters in a non Latin-based language; converting the encoded representation of the bilingual text to the first set of characters in the Latin-based language and the second set of characters in the non Latin-based language based on a lookup table; removing prefix characters and postfix characters after the conversion of the encoded representation; and outputting the bilingual text which comprises the first set of characters in the Latin-based language and the second set of characters in the non Latin-based language, wherein the received QR code based on the encoded representation of the bilingual text embeds a higher number of Arabic characters than the received QR code for the same bilingual text based solely on a standard QR encoding scheme. | 9. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, and the program instructions are readable by a computing device to cause the computing device to perform a method comprising: receiving a QR code based on the encoded representation of the bilingual text; converting the QR code to the encoded representation of the bilingual text; receiving the encoded representation of a bilingual text which comprises a first set of characters in a Latin-based language and a second set of characters in a non Latin-based language; converting the encoded representation of the bilingual text to the first set of characters in the Latin-based language and the second set of characters in the non Latin-based language based on a lookup table; removing prefix characters and postfix characters after the conversion of the encoded representation; and outputting the bilingual text which comprises the first set of characters in the Latin-based language and the second set of characters in the non Latin-based language, wherein the received QR code based on the encoded representation of the bilingual text embeds a higher number of Arabic characters than the received QR code for the same bilingual text based solely on a standard QR encoding scheme. 12. The computer program product of claim 9 , wherein the non Latin-based language comprises one of Arabic, Urdu, and Farsi. | 0.619632 |
7,979,376 | 17 | 20 | 17. An automated reasoning system adapted for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, said automated reasoning system comprising: a module adapted to provide a print product description; a module adapted to extract asset metadata from a plurality of resources associated with said print product description; a processor adapted to process said asset metadata through said automated reasoning system to infer predefined characteristics from said asset metadata to form inferred metadata; and a module adapted to utilize said inferred metadata to add and parameterize a process node including said inferred metadata to a process network. | 17. An automated reasoning system adapted for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, said automated reasoning system comprising: a module adapted to provide a print product description; a module adapted to extract asset metadata from a plurality of resources associated with said print product description; a processor adapted to process said asset metadata through said automated reasoning system to infer predefined characteristics from said asset metadata to form inferred metadata; and a module adapted to utilize said inferred metadata to add and parameterize a process node including said inferred metadata to a process network. 20. The automated reasoning system of claim 17 further comprising an ontology-based reasoning module adapted to reference ontology characteristics via description logic. | 0.5 |
9,418,057 | 1 | 3 | 1. A method executed by at least one processor comprising the steps of: receiving, at a system, a profile submitted by a user, the system configured to compare a set of profiles to one another; determining a geographical location from which the profile was submitted; determining that the geographical location from which the profile was submitted is a geographical location associated with fraudulent profile submissions; determining a text score for the profile by comparing a first set of phrases included in the profile to a second set of phrases, the second set of phrases comprising phrases from stored text, the stored text comprising stored text known to be genuine and stored text known to be fraudulent; determining that the profile is fraudulent using the text score and the geographical location from which the profile was submitted; and in response to determining that the profile is fraudulent, preventing the system from comparing the profile to the set of profiles. | 1. A method executed by at least one processor comprising the steps of: receiving, at a system, a profile submitted by a user, the system configured to compare a set of profiles to one another; determining a geographical location from which the profile was submitted; determining that the geographical location from which the profile was submitted is a geographical location associated with fraudulent profile submissions; determining a text score for the profile by comparing a first set of phrases included in the profile to a second set of phrases, the second set of phrases comprising phrases from stored text, the stored text comprising stored text known to be genuine and stored text known to be fraudulent; determining that the profile is fraudulent using the text score and the geographical location from which the profile was submitted; and in response to determining that the profile is fraudulent, preventing the system from comparing the profile to the set of profiles. 3. The method of claim 1 , wherein the stored text is organized in at least one tree structure. | 0.8903 |
7,778,944 | 11 | 12 | 11. The machine-readable medium of claim 10 , wherein the plurality of linear rules have associated weights and are provided as a result of machine learning. | 11. The machine-readable medium of claim 10 , wherein the plurality of linear rules have associated weights and are provided as a result of machine learning. 12. The machine-readable medium of claim 11 , wherein partitioning of the plurality of linear rules further comprises partitioning each of the plurality of the linear rules into a respective one of the plurality of types of rules. | 0.5 |
9,875,022 | 1 | 7 | 1. A handwriting input method of an electronic device using a touch pen, the handwriting input method comprising: displaying an execution screen of an application on a touch screen in response to the application being executed; overlapping a handwriting input layer, which is configured for a handwriting input, with the execution screen; in response to a handwriting image being input on the handwriting input layer by the touch pen, determining a data type for recognizing the handwriting image based on an area in which the handwriting image is input among a plurality of areas of the handwriting input layer, and recognizing the handwriting image as the determined data type; and applying the recognized handwriting image to the application differently according to the determined data type of the handwriting image, wherein, the determining comprises: determining the data type for recognizing the handwriting image as a text in response to the handwriting image being input in a first area among the plurality of areas of the handwriting input layer, and determining the data type for recognizing the handwriting image as an image in response to the handwriting image being input in a second area different from the first area among the plurality of areas of the handwriting input layer. | 1. A handwriting input method of an electronic device using a touch pen, the handwriting input method comprising: displaying an execution screen of an application on a touch screen in response to the application being executed; overlapping a handwriting input layer, which is configured for a handwriting input, with the execution screen; in response to a handwriting image being input on the handwriting input layer by the touch pen, determining a data type for recognizing the handwriting image based on an area in which the handwriting image is input among a plurality of areas of the handwriting input layer, and recognizing the handwriting image as the determined data type; and applying the recognized handwriting image to the application differently according to the determined data type of the handwriting image, wherein, the determining comprises: determining the data type for recognizing the handwriting image as a text in response to the handwriting image being input in a first area among the plurality of areas of the handwriting input layer, and determining the data type for recognizing the handwriting image as an image in response to the handwriting image being input in a second area different from the first area among the plurality of areas of the handwriting input layer. 7. The handwriting input method of claim 1 , wherein in response to the area of the handwriting input layer in which the handwriting image has been input corresponding to a table comprising a plurality of cells in the execution screen, the determining the data type for recognizing the handwriting image further comprises: recognizing the handwriting image as a command which selects at least one of the plurality of cells, and the applying the recognized result of the determined data type to the application comprises: in response to a handwriting image being additionally input on the handwriting input layer using the touch pen, recognizing the additionally input handwriting image as the text or the image to display the text or the image on at least one selected cell. | 0.5 |
9,015,803 | 71 | 75 | 71. The server computer system of claim 70 , wherein the server computer system is capable of storing an indication of the one or more modifications made to the first document. | 71. The server computer system of claim 70 , wherein the server computer system is capable of storing an indication of the one or more modifications made to the first document. 75. The server computer system of claim 71 , wherein the server computer system is capable of verifying the first user based on: (a) information accessible using an authorization key presented by the first user; (b) expiration time for an authorization key presented by the first user; (c) security level of the first user as determined by the server computer system; (d) security level of a device used by the first user to access the server computer system; (e) type of device used by the first user to access the server computer system; (f) identity of device used by the first user to access the server computer system; (g) Internet address from which the first user accessed the server computer system; (h) time of day when the first user accessed the server computer system; or (i) day of week when the first user accessed the server computer system. | 0.5 |
9,354,629 | 1 | 3 | 1. A method comprising: loading an interpretable system-level vendor-independent first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices; and compiling the first script to form a second script with vendor-specific configuration language by identifying one or more lexemes contained in the first script, identifying the tokens contained in the first script based on the identified one or more lexemes, identifying one or more first expressions based on grammatical relationships between the identified tokens, identifying vendor-specific information associated with the process control system from a device database associated with the process control system, and forming the second script based on the identified one or more first expressions and the identified vendor-specific information, to configure the multiple process controllers and process control devices for control. | 1. A method comprising: loading an interpretable system-level vendor-independent first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices; and compiling the first script to form a second script with vendor-specific configuration language by identifying one or more lexemes contained in the first script, identifying the tokens contained in the first script based on the identified one or more lexemes, identifying one or more first expressions based on grammatical relationships between the identified tokens, identifying vendor-specific information associated with the process control system from a device database associated with the process control system, and forming the second script based on the identified one or more first expressions and the identified vendor-specific information, to configure the multiple process controllers and process control devices for control. 3. The method as defined in claim 1 , wherein the first script is constructed in accordance with an extensible markup language. | 0.84321 |
7,734,556 | 1 | 3 | 1. A method for discovering knowledge from a set of text documents using a processor, the method comprising: extracting semi-structured meta-data from the set of text documents using a meta-data extractor, the semi-structured meta-data comprising a plurality of concepts and a plurality of relations between the concepts; filtering the semi-structured meta-data to identify a set of key concepts and a corresponding set of key relations between the key concepts, the set of key concepts corresponding to the plurality of concepts; deriving at least one set of sub-concepts corresponding to the set of key concepts based upon data within a domain knowledge base, using a meta-data transformer; formulating a plurality of training samples, each training sample including a vector representing a sub-concept and a vector representing a key concept; and analyzing the plurality of training samples using an associative discoverer to derive a set of associations between a set of vectors representing a sub-concept and at least one vector representing a key concept, wherein neither the set of text documents nor the semi-structured meta-data mention the set of associations, and wherein the set of associations corresponds to discovered knowledge that is extractable by a knowledge interpreter. | 1. A method for discovering knowledge from a set of text documents using a processor, the method comprising: extracting semi-structured meta-data from the set of text documents using a meta-data extractor, the semi-structured meta-data comprising a plurality of concepts and a plurality of relations between the concepts; filtering the semi-structured meta-data to identify a set of key concepts and a corresponding set of key relations between the key concepts, the set of key concepts corresponding to the plurality of concepts; deriving at least one set of sub-concepts corresponding to the set of key concepts based upon data within a domain knowledge base, using a meta-data transformer; formulating a plurality of training samples, each training sample including a vector representing a sub-concept and a vector representing a key concept; and analyzing the plurality of training samples using an associative discoverer to derive a set of associations between a set of vectors representing a sub-concept and at least one vector representing a key concept, wherein neither the set of text documents nor the semi-structured meta-data mention the set of associations, and wherein the set of associations corresponds to discovered knowledge that is extractable by a knowledge interpreter. 3. The method as in claim 1 , wherein filtering the semi-structured meta-data comprises selecting the set of key concepts according to frequency of appearance of the set of key concepts in the semi-structured meta-data. | 0.611702 |
8,738,470 | 44 | 47 | 44. The method of claim 29 wherein the providing of the information identifying the user-defined first group of multiple items to the user is performed in response to determining that the user-defined group satisfies one or more search criteria specified by the user, the one or more search criteria including an indication of at least one of the determined one or more first categories for the user-defined group. | 44. The method of claim 29 wherein the providing of the information identifying the user-defined first group of multiple items to the user is performed in response to determining that the user-defined group satisfies one or more search criteria specified by the user, the one or more search criteria including an indication of at least one of the determined one or more first categories for the user-defined group. 47. The method of claim 44 wherein the one or more search criteria that the user-defined group satisfies relate to demographic information about an intended recipient. | 0.789141 |
7,533,034 | 1 | 32 | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. 32. The method according to claim 1 , further comprising: maintaining a user suggestion log in memory associated with the processor. | 0.758242 |
9,275,139 | 1 | 6 | 1. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; scoring the speech recognition by use of a soft time window, wherein the soft time window comprises a window definable by a spline function; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M. | 1. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; scoring the speech recognition by use of a soft time window, wherein the soft time window comprises a window definable by a spline function; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M. 6. The method of claim 1 wherein the audio data comprises content-dependent metadata and content-independent metadata. | 0.814465 |
8,094,905 | 1 | 23 | 1. System for providing information to a user, said system Comprising: a screen for showing the information to the user, information generating means for generating at least one of graphical and/or textual information, first selecting means for enabling the user to select at least one of said graphical and/or textual information, first generating means for generating first data which is related to said selected information, wherein said first data is grouped for display to the user according to a first criterion out of a plurality of available criteria, changing means for changing said first criterion to at least one second criterion out of said plurality of available criteria, and triggering means for triggering said changing means upon activation by the user of the system such that upon activation of the triggering means said first data is grouped for display to the user according to said second criterion. | 1. System for providing information to a user, said system Comprising: a screen for showing the information to the user, information generating means for generating at least one of graphical and/or textual information, first selecting means for enabling the user to select at least one of said graphical and/or textual information, first generating means for generating first data which is related to said selected information, wherein said first data is grouped for display to the user according to a first criterion out of a plurality of available criteria, changing means for changing said first criterion to at least one second criterion out of said plurality of available criteria, and triggering means for triggering said changing means upon activation by the user of the system such that upon activation of the triggering means said first data is grouped for display to the user according to said second criterion. 23. The system according to claim 1 , wherein the graphical and/or textual information and/or the data comprise at least one sparkline and/or a label and/or value. | 0.806872 |
9,056,256 | 1 | 9 | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. 9. The method of claim 1 wherein: capturing actions taken by the user includes determining to which online social communities the user belongs; and automatically determining a play personality of the user is based, at least in part, on to which online social communities the user belongs. | 0.580175 |
9,465,879 | 31 | 37 | 31. A non-transitory computer-readable storage medium tangibly storing thereon computer-executable code, that when executed by a processor, perform steps comprising: receiving crawling data from a crawler crawling a content preview source; extracting, in connection with crawling the content preview source, data and a link from the content preview source, the link comprising a link to a target document, the data to be used to create a content preview document previewing the target document, the target document containing content being previewed by the content preview source; creating, in connection with crawling the content preview source, the content preview document using the data extracted from the content preview source, the content preview document being different from the target document and the content preview source, the content preview document being created without using the target document; and making the created content preview document available for searching by a search engine in an index prior to the target document being made available for searching by the search engine in the index. | 31. A non-transitory computer-readable storage medium tangibly storing thereon computer-executable code, that when executed by a processor, perform steps comprising: receiving crawling data from a crawler crawling a content preview source; extracting, in connection with crawling the content preview source, data and a link from the content preview source, the link comprising a link to a target document, the data to be used to create a content preview document previewing the target document, the target document containing content being previewed by the content preview source; creating, in connection with crawling the content preview source, the content preview document using the data extracted from the content preview source, the content preview document being different from the target document and the content preview source, the content preview document being created without using the target document; and making the created content preview document available for searching by a search engine in an index prior to the target document being made available for searching by the search engine in the index. 37. The non-transitory computer-readable storage medium of claim 31 , further comprising: using at least a portion of the extracted data to present the target document as part of search results generated by the search engine in response to a search query. | 0.607692 |
9,317,809 | 12 | 15 | 12. Non-transitory computer readable media for storing executable instructions for controlling the operation of computers on a plurality of segments of an MPP relational database for latent Dirichlet allocation (LDA) processing on said segments in parallel a subset of a dataset, the dataset comprising a plurality of documents, each document being a mixture of topics where each topic is characterized by a probability distribution over a vocabulary of words, said LDA processing comprising: distributing subsets of said documents of said dataset to said plurality of segments, where each one of said documents of a subset is distributed to and stored on one single segment of said relational database; determining in parallel on each segment for each document of the subset on said segment a per-word and a per-document topic count; performing in parallel on each segment LDA analysis using said determined topic counts determine to assign words to a new topic; calculating in parallel on each segment per-word and per-document probability distributions of topic assignments; iterating said determining, said performing, and said calculating steps on each segment until a predetermined stop condition is satisfied, and storing results locally in memory on each segment, said iterating comprises updating topic assignments of words at each iteration by providing on each segment two work tables for holding topic assignments that alternate roles as an input table and as an output table, a first work table storing topic assignments from a previous iteration and serving as an input table of topic assignments to a next iteration, and a second work table serving as an output table for updated topic assignments from said next iteration, and alternating roles of said first and second tables for input and output on each said iteration for updating topic assignments; and aggregating results from said plurality of segments to form an inference model. | 12. Non-transitory computer readable media for storing executable instructions for controlling the operation of computers on a plurality of segments of an MPP relational database for latent Dirichlet allocation (LDA) processing on said segments in parallel a subset of a dataset, the dataset comprising a plurality of documents, each document being a mixture of topics where each topic is characterized by a probability distribution over a vocabulary of words, said LDA processing comprising: distributing subsets of said documents of said dataset to said plurality of segments, where each one of said documents of a subset is distributed to and stored on one single segment of said relational database; determining in parallel on each segment for each document of the subset on said segment a per-word and a per-document topic count; performing in parallel on each segment LDA analysis using said determined topic counts determine to assign words to a new topic; calculating in parallel on each segment per-word and per-document probability distributions of topic assignments; iterating said determining, said performing, and said calculating steps on each segment until a predetermined stop condition is satisfied, and storing results locally in memory on each segment, said iterating comprises updating topic assignments of words at each iteration by providing on each segment two work tables for holding topic assignments that alternate roles as an input table and as an output table, a first work table storing topic assignments from a previous iteration and serving as an input table of topic assignments to a next iteration, and a second work table serving as an output table for updated topic assignments from said next iteration, and alternating roles of said first and second tables for input and output on each said iteration for updating topic assignments; and aggregating results from said plurality of segments to form an inference model. 15. The non-transitory computer readable media of claim 12 further comprising instructions representing each document by a quadruple comprising <docid, wordcount, words, counts>, and distributing and storing each document by a document identifier (<docid>) as a single row in a table on said single segment, and performing Gibbs sampling of a document for said LDA analysis by sampling said single row. | 0.5 |
9,684,843 | 12 | 18 | 12. A computing apparatus comprising: a memory to store instructions; and a processor, operatively coupled to the memory, to execute the instructions, wherein the processor is to: receive information for an identification of a data field in a physical document; receive a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document; select a frame from the plurality of frames in the video stream; identify one or more text regions in the selected frame; process each of the one or more identified text regions of the selected frame to determine data of each of the one or more identified text regions of the selected frame, and to select data of one of the one or more identified text regions that corresponds to a set of attributes associated with the data field; compare the data of the one of the one or more identified text regions of the selected frame with data of one or more text regions of a subsequent frame; update the data of the one of the one or more identified text regions of the selected frame if the data of the one or more text regions of the subsequent frame is a closer match to the set of attributes; and provide a display field comprising the data of the one of the one or more identified text regions for presentation in a user interface. | 12. A computing apparatus comprising: a memory to store instructions; and a processor, operatively coupled to the memory, to execute the instructions, wherein the processor is to: receive information for an identification of a data field in a physical document; receive a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document; select a frame from the plurality of frames in the video stream; identify one or more text regions in the selected frame; process each of the one or more identified text regions of the selected frame to determine data of each of the one or more identified text regions of the selected frame, and to select data of one of the one or more identified text regions that corresponds to a set of attributes associated with the data field; compare the data of the one of the one or more identified text regions of the selected frame with data of one or more text regions of a subsequent frame; update the data of the one of the one or more identified text regions of the selected frame if the data of the one or more text regions of the subsequent frame is a closer match to the set of attributes; and provide a display field comprising the data of the one of the one or more identified text regions for presentation in a user interface. 18. The apparatus of claim 12 , wherein the processor is to invoke the user interface on a mobile phone to assist a user with identifying the data field in the physical document. | 0.915799 |
9,454,597 | 6 | 7 | 6. A document management and retrieval method, comprising: a document index creating step of storing appearance positions of a plurality of words contained in one or more of a plurality of documents; a tag storing step of storing a plurality of tag indexes and an appearance position of each tag in a set of documents of the plurality of documents, each tag index being associated with a respective character string and comprising: a tag associated with its respective character string in one of the plurality of documents, the tag having a tag name and indicating attributes of the character string based upon the meaning of the character string; at least one of a right word string comprising one or more adjacent words that appears to the right of its respective character string and a left word string comprising one or more adjacent words that appears to the left of its respective character string; a combination of the tag with at least one of the left and right word strings; and storing an appearance position of the character string associated with each tag in a set of documents of the plurality of documents; a document retrieval step of receiving as a search query an input of a phrase containing a search tag name and a search word, and returning a list of identified documents that contain the phrase by utilizing the combination entries stored in the tag index store; and using a high-frequency word and a tag name to store a bit string representing a set of documents that contain the high-frequency word and a bit string representing a set of documents that contain a tag, wherein: the tag update step includes updating a bit string in a bit string store based on a tag that has been added or removed through a tag update; and the document retrieval step includes referring to bit strings that have been stored in the bit string storing step with a high-frequency word and tag name contained in the search query, obtaining data representing a set of documents that contain all high-frequency words and tags in the search query, and reading word appearance positions and tag appearance positions in the set of documents of the plurality of documents. | 6. A document management and retrieval method, comprising: a document index creating step of storing appearance positions of a plurality of words contained in one or more of a plurality of documents; a tag storing step of storing a plurality of tag indexes and an appearance position of each tag in a set of documents of the plurality of documents, each tag index being associated with a respective character string and comprising: a tag associated with its respective character string in one of the plurality of documents, the tag having a tag name and indicating attributes of the character string based upon the meaning of the character string; at least one of a right word string comprising one or more adjacent words that appears to the right of its respective character string and a left word string comprising one or more adjacent words that appears to the left of its respective character string; a combination of the tag with at least one of the left and right word strings; and storing an appearance position of the character string associated with each tag in a set of documents of the plurality of documents; a document retrieval step of receiving as a search query an input of a phrase containing a search tag name and a search word, and returning a list of identified documents that contain the phrase by utilizing the combination entries stored in the tag index store; and using a high-frequency word and a tag name to store a bit string representing a set of documents that contain the high-frequency word and a bit string representing a set of documents that contain a tag, wherein: the tag update step includes updating a bit string in a bit string store based on a tag that has been added or removed through a tag update; and the document retrieval step includes referring to bit strings that have been stored in the bit string storing step with a high-frequency word and tag name contained in the search query, obtaining data representing a set of documents that contain all high-frequency words and tags in the search query, and reading word appearance positions and tag appearance positions in the set of documents of the plurality of documents. 7. The document management and retrieval method according to claim 6 , further using an arbitrary character string and enabling a quick reference to a set of tag names that may be attached to the arbitrary character string, wherein: the tag update step includes updating data that represents a relation between a tag name and a character string when a tag is to be attached; and the document retrieval step includes utilizing the quick tag value determining step when a phrase where tag names appear in succession is input as a search query, to read tag appearance positions only for words that contain a specific tag name. | 0.5 |
8,009,915 | 1 | 3 | 1. A machine-implemented method for recognizing a handwritten mathematical expression, the machine-implemented method comprising: partitioning a plurality of strokes of the handwritten mathematical expression, included in a region having at least one non-terminal object, into one or more groups of two regions; repeating the act of partitioning on ones of regions included in the one or more groups of two regions having a non-terminal object; using a first recognizer and a second recognizer to calculate first scores and second scores, respectively, of chart entries representing grammar objects formed from one or more strokes included in the regions; calculating first converted scores and second converted scores from the first scores and the second scores, respectively, each of the converted scores being calculated according to: converted_score = T Γ dir Γ score - m d , where converted score is the converted score, T is a parameter obtained during training for the first recognizer or the second recognizer, correspondingly, score is a score from the first recognizer or the second recognizer, correspondingly, m is a mean score with respect to sample scores of the first recognizer or sample scores of the second recognizer, correspondingly, d is a sample deviation of the sample scores of the first recognizer or the sample scores of the second recognizer, correspondingly, and dir is a direction constant with respect to the first recognizer or the second recognizer, correspondingly; determining a respective converted score for each of the regions based on highest scores selected from corresponding first converted scores and corresponding second converted scores; and recognizing the plurality of strokes of the mathematical expression based on finding highest converted scores of partitioning of the plurality of strokes, wherein the machine-implemented method is performed by at least one processor. | 1. A machine-implemented method for recognizing a handwritten mathematical expression, the machine-implemented method comprising: partitioning a plurality of strokes of the handwritten mathematical expression, included in a region having at least one non-terminal object, into one or more groups of two regions; repeating the act of partitioning on ones of regions included in the one or more groups of two regions having a non-terminal object; using a first recognizer and a second recognizer to calculate first scores and second scores, respectively, of chart entries representing grammar objects formed from one or more strokes included in the regions; calculating first converted scores and second converted scores from the first scores and the second scores, respectively, each of the converted scores being calculated according to: converted_score = T Γ dir Γ score - m d , where converted score is the converted score, T is a parameter obtained during training for the first recognizer or the second recognizer, correspondingly, score is a score from the first recognizer or the second recognizer, correspondingly, m is a mean score with respect to sample scores of the first recognizer or sample scores of the second recognizer, correspondingly, d is a sample deviation of the sample scores of the first recognizer or the sample scores of the second recognizer, correspondingly, and dir is a direction constant with respect to the first recognizer or the second recognizer, correspondingly; determining a respective converted score for each of the regions based on highest scores selected from corresponding first converted scores and corresponding second converted scores; and recognizing the plurality of strokes of the mathematical expression based on finding highest converted scores of partitioning of the plurality of strokes, wherein the machine-implemented method is performed by at least one processor. 3. The machine-implemented method of claim 1 , wherein the converted scores of the regions have at least a near standard normal distribution. | 0.886473 |
9,087,132 | 18 | 32 | 18. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO file; requesting, through said physical network server, said geospatial location information; associating, via a Session Initiation Protocol (SIP) protocol, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. | 18. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO file; requesting, through said physical network server, said geospatial location information; associating, via a Session Initiation Protocol (SIP) protocol, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. 32. The method of tying a geospatial location to a PIDF-LO file according to claim 18 , further comprising: tagging descriptive information relating to said location aware XML content in a <presence . . . > section of said PIDF-LO file. | 0.5 |
9,418,305 | 15 | 16 | 15. The system of claim 11 wherein said instructions are further configured for vertically cropping said image of said license plate prior to sweeping said OCR classifier across said image of said license plate. | 15. The system of claim 11 wherein said instructions are further configured for vertically cropping said image of said license plate prior to sweeping said OCR classifier across said image of said license plate. 16. The system of claim 15 wherein said instructions for inferring characters and their locations with respect to said image of said license plate, further comprise instructions configured for performing a character spacing estimation with respect to said characters. | 0.5 |
7,587,417 | 9 | 12 | 9. A system for generating dynamic queries, comprising: a client computer that provides a properties object which contains settings for a query specified by a user, wherein the properties object is generated at runtime and receives the settings from dynamic user input at runtime; a server computer that communicates with the client computer and a database, the server computer providing a bean associated with the database; and a finder method that specifies the query to be executed against the database, the finder method invoked on the bean provided by the server computer; a descriptor that contains an enable dynamic queries element, wherein the enable dynamic queries element has a value of either true or false for enabling the query, such that invoking queries when the enable dynamic queries element has a value of false results in a remote or local exception being thrown depending on whether the queries submitted after setting the enable dynamic queries element were invoked from a local interface or a remote interface, wherein the dynamic queries element is specifiable by an enable-dynamic-queries parsed character data (PCDATA) tag, wherein said tag signifies that the dynamic queries element contains character data parsed by an extensible markup language (XML) parser; wherein upon invocation of the finder method, the server computer extracts the settings contained in the properties object and parses the finder method in order to dynamically generate the query to be sent to the database; and a collection of results that is returned from the database in response to the finder method, said finder method being invoked on a query home interface used to execute dynamic queries. | 9. A system for generating dynamic queries, comprising: a client computer that provides a properties object which contains settings for a query specified by a user, wherein the properties object is generated at runtime and receives the settings from dynamic user input at runtime; a server computer that communicates with the client computer and a database, the server computer providing a bean associated with the database; and a finder method that specifies the query to be executed against the database, the finder method invoked on the bean provided by the server computer; a descriptor that contains an enable dynamic queries element, wherein the enable dynamic queries element has a value of either true or false for enabling the query, such that invoking queries when the enable dynamic queries element has a value of false results in a remote or local exception being thrown depending on whether the queries submitted after setting the enable dynamic queries element were invoked from a local interface or a remote interface, wherein the dynamic queries element is specifiable by an enable-dynamic-queries parsed character data (PCDATA) tag, wherein said tag signifies that the dynamic queries element contains character data parsed by an extensible markup language (XML) parser; wherein upon invocation of the finder method, the server computer extracts the settings contained in the properties object and parses the finder method in order to dynamically generate the query to be sent to the database; and a collection of results that is returned from the database in response to the finder method, said finder method being invoked on a query home interface used to execute dynamic queries. 12. A system according to claim 9 wherein the bean is an Enterprise Java Bean (EJB) and the size of the EJB deployment descriptor is reduced by dynamically generating the query. | 0.786747 |
9,846,786 | 8 | 14 | 8. A system, comprising: a hardware processor; and a memory device, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations comprising: storing electronic loan documents associated with a borrower of a loan; generating an anonymous shadow copy of the electronic loan documents, the anonymous shadow copy having personally identifying information removed therefrom; storing the anonymous shadow copy as a record in a row of an electronic database; associating the anonymous shadow copy to an access code; storing the access code as another record in the row of the electronic database; storing a database association between the personally identifying information and the access code in a different loan record within in the electronic database; sending the access code to a device associated with the borrower of the loan; receiving a first request sent from a requesting device, the first request requesting the anonymous shadow copy of the electronic loan documents; retrieving the anonymous shadow copy from the row of the electronic database; sending the anonymous shadow copy to the requesting device in response to the first request; receiving a second request sent from the requesting device, the second request requesting the personally identifying information and specifying the access code; querying the electronic database for the access code specified by the second request; retrieving the personally identifying information from the different loan record of the electronic database, the personally identifying information associated with the access code; and sending the personally identifying information to the requesting device in response to the second request; wherein the personally identifying information is separately stored from the row of the electronic database containing the anonymous shadow copy. | 8. A system, comprising: a hardware processor; and a memory device, the memory device storing instructions, the instructions when executed causing the hardware processor to perform operations, the operations comprising: storing electronic loan documents associated with a borrower of a loan; generating an anonymous shadow copy of the electronic loan documents, the anonymous shadow copy having personally identifying information removed therefrom; storing the anonymous shadow copy as a record in a row of an electronic database; associating the anonymous shadow copy to an access code; storing the access code as another record in the row of the electronic database; storing a database association between the personally identifying information and the access code in a different loan record within in the electronic database; sending the access code to a device associated with the borrower of the loan; receiving a first request sent from a requesting device, the first request requesting the anonymous shadow copy of the electronic loan documents; retrieving the anonymous shadow copy from the row of the electronic database; sending the anonymous shadow copy to the requesting device in response to the first request; receiving a second request sent from the requesting device, the second request requesting the personally identifying information and specifying the access code; querying the electronic database for the access code specified by the second request; retrieving the personally identifying information from the different loan record of the electronic database, the personally identifying information associated with the access code; and sending the personally identifying information to the requesting device in response to the second request; wherein the personally identifying information is separately stored from the row of the electronic database containing the anonymous shadow copy. 14. The system of claim 8 , wherein the operations further comprise clearing a data field containing the personally identifying information. | 0.542484 |
8,527,500 | 4 | 6 | 4. The computer-implemented method of claim 2 , wherein the matching further comprises: weighting the one or more matching prefixes, wherein the weighting is based on separate weights for matching the prefix and the trailing context. | 4. The computer-implemented method of claim 2 , wherein the matching further comprises: weighting the one or more matching prefixes, wherein the weighting is based on separate weights for matching the prefix and the trailing context. 6. The computer-implemented method of claim 4 , wherein the weighting comprises a separate weight for matching the preceding context. | 0.5 |
8,520,225 | 15 | 17 | 15. An apparatus for printing to a Web services-enabled printing device, the apparatus comprising a memory storing instructions which, when processed by one or more processors, causes: a print driver executing on a client device and retrieving, from the Web service-enabled printing device, printing device capabilities data that specifies a plurality of features and options currently supported by the Web service-enabled printing device; wherein the printing device capabilities data specifies, for a particular feature and a particular option of the plurality of features and options, a plurality of languages in which the particular feature and the particular option may be displayed; the print driver generating, based at least upon the printing device capabilities data, printer description data that specifies display data that indicates how the particular feature and the particular option are to be displayed, on a graphical user interface, in the plurality of languages; in response to user input, the print driver generating, based at least upon the display data contained in the printer description data and language data, graphical user interface data which, when processed at the client device, causes the particular feature and the particular option to be displayed on a graphical user interface in a particular language of the plurality of languages that is currently selected for the client device, wherein the language data specifies the particular language; the print driver receiving, from an application program, application data generated by the application program; the print driver generating, based at least upon the application data, print data and a print job ticket; and the print driver causing the print data and the print job ticket to be transmitted to the Web service-enabled printing device. | 15. An apparatus for printing to a Web services-enabled printing device, the apparatus comprising a memory storing instructions which, when processed by one or more processors, causes: a print driver executing on a client device and retrieving, from the Web service-enabled printing device, printing device capabilities data that specifies a plurality of features and options currently supported by the Web service-enabled printing device; wherein the printing device capabilities data specifies, for a particular feature and a particular option of the plurality of features and options, a plurality of languages in which the particular feature and the particular option may be displayed; the print driver generating, based at least upon the printing device capabilities data, printer description data that specifies display data that indicates how the particular feature and the particular option are to be displayed, on a graphical user interface, in the plurality of languages; in response to user input, the print driver generating, based at least upon the display data contained in the printer description data and language data, graphical user interface data which, when processed at the client device, causes the particular feature and the particular option to be displayed on a graphical user interface in a particular language of the plurality of languages that is currently selected for the client device, wherein the language data specifies the particular language; the print driver receiving, from an application program, application data generated by the application program; the print driver generating, based at least upon the application data, print data and a print job ticket; and the print driver causing the print data and the print job ticket to be transmitted to the Web service-enabled printing device. 17. The apparatus of claim 15 , wherein the memory stores additional instructions which, when processed by the one or more processors, causes: in response to a particular user logging in to a computer system, causing the language data to specify a second language that is different than the particular language; and in response to second user input, the print driver generating, based at least upon the display data contained in the printer description data and the language data, second graphical user interface data which, when processed at the client device, causes the particular feature and the particular option to be displayed on a second graphical user interface in the second language. | 0.798021 |
7,634,472 | 1 | 7 | 1. A computerized method of scoring data for use in a search engine, comprising: tracking clicks by users on data returned in a search result in response to a query; determining, using a processing device, a user preference for a clicked data in accordance with a physical position of the clicked data in the search result, wherein determining the user preference for the clicked data is performed by: determining a ratio calculating the quotient of actual clicks to the clicked data and a specific query and clicks expected for the clicked data and the specific query, wherein determining clicks expected for the clicked data and the specific query is performed by determining a context dependent user preference score in accordance with at least one weight table that comprises a contextual weight for the clicked data in accordance with physical position, the weight table specifically associated with one of a plurality of user interfaces based on a visual layout of the user interface, the contextual weight indicating a product associated with the clicked data; and using the determined user preference to determine, using the processing device, rankings for display of future search results. | 1. A computerized method of scoring data for use in a search engine, comprising: tracking clicks by users on data returned in a search result in response to a query; determining, using a processing device, a user preference for a clicked data in accordance with a physical position of the clicked data in the search result, wherein determining the user preference for the clicked data is performed by: determining a ratio calculating the quotient of actual clicks to the clicked data and a specific query and clicks expected for the clicked data and the specific query, wherein determining clicks expected for the clicked data and the specific query is performed by determining a context dependent user preference score in accordance with at least one weight table that comprises a contextual weight for the clicked data in accordance with physical position, the weight table specifically associated with one of a plurality of user interfaces based on a visual layout of the user interface, the contextual weight indicating a product associated with the clicked data; and using the determined user preference to determine, using the processing device, rankings for display of future search results. 7. The method of claim 1 , wherein determining a user preference for a clicked data in accordance with a physical position of the data in the search result is performed in accordance with weight values determined by observed user click behavior. | 0.5 |
8,521,764 | 8 | 10 | 8. A system comprising: one or more server devices to: identify entity identifiers, where each of the entity identifiers is associated with a document that was selected, from a plurality of documents, based on a search query including a same variation of an entity name; determine whether a total quantity of selections of the document associated with a particular entity identifier, of the entity identifiers, is greater than a total quantity of selections of each of the documents associated with other ones of the entity identifiers; and store, based on a result of the determining, the same variation of the entity name in a first memory that is used for rewriting search queries or a second memory that is used for suggesting rewritten search queries, where the same variation of the entity name is stored in the second memory when the total quantity of selections of the document associated with the particular entity identifier is greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers, and where the same variation of the entity name is stored in the first memory when the total quantity of selections of the document associated with the particular entity identifier is substantially greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers. | 8. A system comprising: one or more server devices to: identify entity identifiers, where each of the entity identifiers is associated with a document that was selected, from a plurality of documents, based on a search query including a same variation of an entity name; determine whether a total quantity of selections of the document associated with a particular entity identifier, of the entity identifiers, is greater than a total quantity of selections of each of the documents associated with other ones of the entity identifiers; and store, based on a result of the determining, the same variation of the entity name in a first memory that is used for rewriting search queries or a second memory that is used for suggesting rewritten search queries, where the same variation of the entity name is stored in the second memory when the total quantity of selections of the document associated with the particular entity identifier is greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers, and where the same variation of the entity name is stored in the first memory when the total quantity of selections of the document associated with the particular entity identifier is substantially greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers. 10. The system of claim 8 , where, when determining whether the total quantity of selections of the document associated with the particular entity identifier is greater than the total quantity of selections of each of the documents associated with the other ones of the entity identifiers, the one or more server devices are to: determine whether the total quantity of selections of the document associated with the particular entity identifier is peaked with respect to the total quantity of selections of each of the documents associated with the ones of the entity identifiers, and where the one or more server devices are further to: store the same variation of the entity name in the first memory when the total quantity of selections of the document associated with the particular entity identifier is peaked; and store the same variation of the entity name in the second memory, when the total quantity of selections of the document associated with the particular entity identifier is not peaked. | 0.524645 |
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