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8,751,521 | 11 | 17 |
11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges.
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11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. 17. The system of claim 11 , wherein the processors are further operable when executing the instructions to transmit one or more of the recommended queries to the first user.
| 0.713816 |
7,979,362 | 1 | 8 |
1. A non-transitory computer-readable medium storing a program for interactive data mining including programming instructions for: reading in a set of data vectors wherein each data vector comprises a class attribute, and a plurality of additional attributes; counting a plurality of counts of times each particular attribute of said plurality of additional attributes, takes on each of a set of possible values for the particular attribute; and presenting a plurality of histograms on a computer display wherein each of said plurality of histograms includes counts for one of said plurality of additional attributes versus attribute value and wherein said plurality of histograms are presented in a sorted order; wherein said sorted order is based on a sorting-of the histograms according to a metric of non-randomness of distributions shown in said histograms; wherein the metric of non-randomness is a metric of discriminative power with respect to said class attribute.
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1. A non-transitory computer-readable medium storing a program for interactive data mining including programming instructions for: reading in a set of data vectors wherein each data vector comprises a class attribute, and a plurality of additional attributes; counting a plurality of counts of times each particular attribute of said plurality of additional attributes, takes on each of a set of possible values for the particular attribute; and presenting a plurality of histograms on a computer display wherein each of said plurality of histograms includes counts for one of said plurality of additional attributes versus attribute value and wherein said plurality of histograms are presented in a sorted order; wherein said sorted order is based on a sorting-of the histograms according to a metric of non-randomness of distributions shown in said histograms; wherein the metric of non-randomness is a metric of discriminative power with respect to said class attribute. 8. The computer-readable medium according to claim 1 wherein said histograms are augmented by up and down arrows located proximate said histograms to show trend type.
| 0.658436 |
7,716,216 | 1 | 2 |
1. A method, performed by one or more server devices, comprising: identifying, using a processor of the one or more server devices, an implicitly defined semantic structure in a document, where a plurality of rules are associated with the implicitly defined semantic structure, and where the semantic structure includes a list having a header and a plurality of items associated with the header; determining, using a processor of the one or more server devices, a location of a first term and a location of a second term within the list; selecting, using a processor of the one or more server devices, one of the plurality of rules, as a selected rule, based on a relationship of the locations of the first and second terms within the implicitly defined semantic structure, where a first rule of the plurality of rules is selected when the first term is located in one of the plurality of items and the second term is located in a different one of the plurality of items, where a second rule of the plurality of rules, different than the first rule, is selected when the first term is located in one of the plurality of items and the second term is located in the same one of the plurality of items, and where a third rule of the plurality of rules, different than the first rule and the second rule, is selected when the first term is located in the header and the second term is located in one of the plurality of items; determining, using a processor of the one or more server devices, a distance value, reflecting a distance between the first and second terms, using a function based on the selected rule, where the function differs based on whether the selected rule corresponds to the first rule, the second rule, or the third rule; and outputting, using a processor of the one or more server devices, the distance value to rank the document for relevancy to a search query that includes the first term and the second term.
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1. A method, performed by one or more server devices, comprising: identifying, using a processor of the one or more server devices, an implicitly defined semantic structure in a document, where a plurality of rules are associated with the implicitly defined semantic structure, and where the semantic structure includes a list having a header and a plurality of items associated with the header; determining, using a processor of the one or more server devices, a location of a first term and a location of a second term within the list; selecting, using a processor of the one or more server devices, one of the plurality of rules, as a selected rule, based on a relationship of the locations of the first and second terms within the implicitly defined semantic structure, where a first rule of the plurality of rules is selected when the first term is located in one of the plurality of items and the second term is located in a different one of the plurality of items, where a second rule of the plurality of rules, different than the first rule, is selected when the first term is located in one of the plurality of items and the second term is located in the same one of the plurality of items, and where a third rule of the plurality of rules, different than the first rule and the second rule, is selected when the first term is located in the header and the second term is located in one of the plurality of items; determining, using a processor of the one or more server devices, a distance value, reflecting a distance between the first and second terms, using a function based on the selected rule, where the function differs based on whether the selected rule corresponds to the first rule, the second rule, or the third rule; and outputting, using a processor of the one or more server devices, the distance value to rank the document for relevancy to a search query that includes the first term and the second term. 2. The method of claim 1 , where the document is an HTML (Hyper-Text Markup Language) document.
| 0.736111 |
9,711,117 | 1 | 4 |
1. A method for recognising music symbols based on handwritten music notations on computing devices, each computing device comprising a processor and at least one non-transitory computer readable medium for recognizing handwriting input under control of the processor, the method comprising: segmenting the handwritten music notations into a plurality of ink segments; determining at least one music symbol candidate for graphical objects representing groupings of the ink segments based on spatial relationships therebetween, the at least one music symbol candidate having an associated symbol cost; forming one or more graphs including the at least one music symbol candidate and one or more grammar rules applied to the at least one music symbol candidate, each grammar rule applied to at least two music symbol candidates having an associated spatial cost based on the spatial relationships between the graphical objects of the at least two music symbol candidates; and selecting at least one graph of the one or more graphs as representing the handwritten music notations based on the symbol costs and the spatial costs associated with the one or more graphs.
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1. A method for recognising music symbols based on handwritten music notations on computing devices, each computing device comprising a processor and at least one non-transitory computer readable medium for recognizing handwriting input under control of the processor, the method comprising: segmenting the handwritten music notations into a plurality of ink segments; determining at least one music symbol candidate for graphical objects representing groupings of the ink segments based on spatial relationships therebetween, the at least one music symbol candidate having an associated symbol cost; forming one or more graphs including the at least one music symbol candidate and one or more grammar rules applied to the at least one music symbol candidate, each grammar rule applied to at least two music symbol candidates having an associated spatial cost based on the spatial relationships between the graphical objects of the at least two music symbol candidates; and selecting at least one graph of the one or more graphs as representing the handwritten music notations based on the symbol costs and the spatial costs associated with the one or more graphs. 4. The method according to claim 1 , wherein the selecting at least one graph comprises: determining each possible graph representing the handwritten music notations; and choosing a graph having a lowest total cost that is the sum of the associated symbol costs and the associated spatial costs.
| 0.551672 |
10,142,708 | 50 | 51 |
50. The method of claim 25 wherein providing access to one or more narrative segments of a narrative presentation includes providing access to a first subset of a plurality of subsets of the narrative segments or bonus content, and providing access by the respective media content consumer to the at least one of the controlled narrative segment of the narrative presentation or the piece of bonus media content includes providing access to a first subset of a plurality of subsets of the narrative segments or bonus content, the second subset of the narrative segments mutually exclusive of the first subset of the narrative segments.
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50. The method of claim 25 wherein providing access to one or more narrative segments of a narrative presentation includes providing access to a first subset of a plurality of subsets of the narrative segments or bonus content, and providing access by the respective media content consumer to the at least one of the controlled narrative segment of the narrative presentation or the piece of bonus media content includes providing access to a first subset of a plurality of subsets of the narrative segments or bonus content, the second subset of the narrative segments mutually exclusive of the first subset of the narrative segments. 51. The method of claim 50 wherein determining whether the access condition is met includes determining whether at least one social media sharing action by the respective media content consumer has occurred.
| 0.670382 |
8,468,142 | 22 | 27 |
22. One or more non-transitory computer-readable storage media embodying software for execution by one or more computer systems and being operable when executed to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results.
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22. One or more non-transitory computer-readable storage media embodying software for execution by one or more computer systems and being operable when executed to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. 27. The media of claim 22 , wherein to construct one of the third BDDs comprises: represent the page ID of the web page represented by the third BDD in binary format; represent a plurality of binary digits in the page ID with a plurality of variables, each variable representing a different one of the binary digits; and construct the third BDD with the variables as a plurality of decision nodes.
| 0.613813 |
5,435,564 | 1 | 5 |
1. An electronic word building dictionary machine comprising: keyboard means to input a user determined set of letters, a set of words in memory, comparison means to compare said input set of letters with said set of words in memory to provide a set of matching words from said set of words in memory, said comparison means including means for treating said variable letter member as a sequence of letters of the alphabet, said sequence at least one letter of the alphabet and said set of matching words comprising words which consist only of a subset of letters from said input set of letters, ranking means to provide a predetermined score for each of said words in said set of matching words, display means to display on said machine each of said words in the sequence of value of said score together with the score value of the word being displayed, wherein said keyboard means has a second input key representing a variable number of letters to provide a variable letter member of said user determined set of letters.
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1. An electronic word building dictionary machine comprising: keyboard means to input a user determined set of letters, a set of words in memory, comparison means to compare said input set of letters with said set of words in memory to provide a set of matching words from said set of words in memory, said comparison means including means for treating said variable letter member as a sequence of letters of the alphabet, said sequence at least one letter of the alphabet and said set of matching words comprising words which consist only of a subset of letters from said input set of letters, ranking means to provide a predetermined score for each of said words in said set of matching words, display means to display on said machine each of said words in the sequence of value of said score together with the score value of the word being displayed, wherein said keyboard means has a second input key representing a variable number of letters to provide a variable letter member of said user determined set of letters. 5. The electronic word building machine of claim 1 further comprising: second input means to input a user determined second predetermined set of letters in a predetermined sequence as a pattern set, said pattern set being part of said input set of letters, said comparison means including said pattern set as a necessary part of each of said set of matching words.
| 0.5 |
9,384,188 | 15 | 16 |
15. The system according to claim 9 , further comprising: receiving, from a user, request for an alternative to one or more tokens of a response presented to the user.
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15. The system according to claim 9 , further comprising: receiving, from a user, request for an alternative to one or more tokens of a response presented to the user. 16. The system according to claim 15 , further comprising: outputting an alternative for one or more tokens based on evaluation of the multi-arc confusion network.
| 0.5 |
10,078,763 | 3 | 5 |
3. The method of claim 2 , further comprising the step of: registering, indivisibly, the metadata tag with every word in a register file.
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3. The method of claim 2 , further comprising the step of: registering, indivisibly, the metadata tag with every word in a register file. 5. The method of claim 3 , wherein the metadata tags are unbounded to enforce any number of policies at the same time.
| 0.520325 |
7,765,188 | 8 | 12 |
8. A repository system, including: a metadata repository storing metadata including records defining taxonomies and records using the taxonomies to define taxonomy values, the metadata repository having a service interface exposing a data update service for updating the data in records and also exposing a taxonomy search service; and a taxonomy editor arranged as a client of the metadata repository, arranged to call the data update service to edit the definitions of taxonomies and to edit the taxonomy values stored in records; wherein the taxonomy editor is arranged to send a message to the taxonomy search service for at least one called taxonomy to cause the taxonomy search service to search the metadata repository for inconsistency between the at least one called taxonomy and the metadata stored in the repository, the message indicating the at least one called taxonomy; wherein the taxonomy search service is arranged to send a reply message, the reply message indicative of the inconsistency between the at least one called taxonomy and the metadata stored in the repository.
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8. A repository system, including: a metadata repository storing metadata including records defining taxonomies and records using the taxonomies to define taxonomy values, the metadata repository having a service interface exposing a data update service for updating the data in records and also exposing a taxonomy search service; and a taxonomy editor arranged as a client of the metadata repository, arranged to call the data update service to edit the definitions of taxonomies and to edit the taxonomy values stored in records; wherein the taxonomy editor is arranged to send a message to the taxonomy search service for at least one called taxonomy to cause the taxonomy search service to search the metadata repository for inconsistency between the at least one called taxonomy and the metadata stored in the repository, the message indicating the at least one called taxonomy; wherein the taxonomy search service is arranged to send a reply message, the reply message indicative of the inconsistency between the at least one called taxonomy and the metadata stored in the repository. 12. A repository system according to claim 8 wherein each taxonomy has an identity number; and the taxonomy search service is arranged to return any taxonomy having a duplicate identity number to the at least one called taxonomy.
| 0.524896 |
9,148,441 | 1 | 11 |
1. A computer-implemented method for adjusting suspiciousness scores in event-correlation graphs, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: detecting a suspicious event involving a first actor and a second actor within a computing system, wherein the suspicious event could not be individually classified as definitively malicious; constructing, after the suspicious event involving the first actor and the second actor is detected, an event-correlation graph, wherein the event-correlation graph comprises at least: a representation of the first actor; a representation of the suspicious event, wherein the representation of the suspicious event and the representation of the first actor are interconnected; a representation of the second actor, wherein the representation of the second actor and the representation of the suspicious event are interconnected; a representation of an additional suspicious event involving the first actor and an additional actor; a representation of the additional actor, wherein: the representation of the first actor and the representation of the additional suspicious event are interconnected; the representation of the additional actor and the representation of the additional suspicious event are interconnected; the additional suspicious event could not be individually classified as definitively malicious; each suspicious event represented in the event-correlation graph could not be individually classified as definitively malicious; adjusting a suspiciousness score associated with at least one of an actor represented in the event-correlation graph and a suspicious event represented in the event-correlation graph based at least in part on a suspiciousness score associated with at least one other actor or suspicious event represented in the event-correlation graph such that the adjusted suspiciousness score is influenced by the suspiciousness score associated with the at least one other actor or suspicious event.
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1. A computer-implemented method for adjusting suspiciousness scores in event-correlation graphs, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: detecting a suspicious event involving a first actor and a second actor within a computing system, wherein the suspicious event could not be individually classified as definitively malicious; constructing, after the suspicious event involving the first actor and the second actor is detected, an event-correlation graph, wherein the event-correlation graph comprises at least: a representation of the first actor; a representation of the suspicious event, wherein the representation of the suspicious event and the representation of the first actor are interconnected; a representation of the second actor, wherein the representation of the second actor and the representation of the suspicious event are interconnected; a representation of an additional suspicious event involving the first actor and an additional actor; a representation of the additional actor, wherein: the representation of the first actor and the representation of the additional suspicious event are interconnected; the representation of the additional actor and the representation of the additional suspicious event are interconnected; the additional suspicious event could not be individually classified as definitively malicious; each suspicious event represented in the event-correlation graph could not be individually classified as definitively malicious; adjusting a suspiciousness score associated with at least one of an actor represented in the event-correlation graph and a suspicious event represented in the event-correlation graph based at least in part on a suspiciousness score associated with at least one other actor or suspicious event represented in the event-correlation graph such that the adjusted suspiciousness score is influenced by the suspiciousness score associated with the at least one other actor or suspicious event. 11. The computer-implemented method of claim 1 , wherein adjusting the suspiciousness score comprises applying a heat-diffusion algorithm to the event-correlation graph.
| 0.865446 |
7,788,204 | 11 | 15 |
11. A computer-readable storage medium, comprising program instructions computer-executable to implement: selecting a navigation path of an interview-based application, wherein the navigation path comprises a plurality of prompts associated with a tax topic on a tax return; displaying a prompt to a user, wherein the plurality of prompts includes the prompt; receiving, from the user and in response to displaying the prompt, a request for help associated with the tax topic; obtaining a knowledge profile comprising a numerical knowledge subscale score, wherein the numerical knowledge subscale score is associated with the tax topic, and wherein the knowledge profile is associated with the user; lowering, in response to the request for help associated with the tax topic, the numerical knowledge subscale score associated with the tax topic; selecting, in response to lowering the numerical knowledge subscale score, an alternate navigation path of the interview-based application, wherein the alternate path comprises an alternate plurality of prompts regarding the tax topic; displaying an alternate prompt to the user, wherein the alternate plurality of prompts includes the prompt; receiving, from the user, a value in response to displaying the alternate prompt; and populating a field of the tax return based on the value.
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11. A computer-readable storage medium, comprising program instructions computer-executable to implement: selecting a navigation path of an interview-based application, wherein the navigation path comprises a plurality of prompts associated with a tax topic on a tax return; displaying a prompt to a user, wherein the plurality of prompts includes the prompt; receiving, from the user and in response to displaying the prompt, a request for help associated with the tax topic; obtaining a knowledge profile comprising a numerical knowledge subscale score, wherein the numerical knowledge subscale score is associated with the tax topic, and wherein the knowledge profile is associated with the user; lowering, in response to the request for help associated with the tax topic, the numerical knowledge subscale score associated with the tax topic; selecting, in response to lowering the numerical knowledge subscale score, an alternate navigation path of the interview-based application, wherein the alternate path comprises an alternate plurality of prompts regarding the tax topic; displaying an alternate prompt to the user, wherein the alternate plurality of prompts includes the prompt; receiving, from the user, a value in response to displaying the alternate prompt; and populating a field of the tax return based on the value. 15. The computer-readable storage medium of claim 11 , wherein the program instructions are further executable to implement: obtaining a numerical knowledge score requirement corresponding to a task of the tax topic; and displaying additional help content to the user in response to the numerical knowledge score requirement exceeding the numerical knowledge subscale score.
| 0.5 |
9,519,872 | 1 | 4 |
1. A system for determining a business ontology, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to: perform an analysis of a plurality of business documents, wherein the analysis comprises: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents.
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1. A system for determining a business ontology, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to: perform an analysis of a plurality of business documents, wherein the analysis comprises: establishing an analysis scope that includes the plurality of business documents; determining a plurality of sentences within the plurality of business documents within the analysis scope, including separating the sentences for analysis; identifying terms and associations between terms within each separated sentence of the plurality of sentences, including determining a proximity between at least two of the terms within at least one sentence of the separated sentences, the proximity including a sentence proximity association for terms of the identified terms occurring in the same sentence but not in a same term group, a term proximity association for identifying actions acted upon terms of the identified terms by other terms, and a document proximity association for all verbs in the same business document of the plurality of business documents; analyzing the associations including the sentence proximity association, the term proximity association, and the document proximity association; after analyzing the terms and associations, identifying frequently-used terms and associations within the plurality of sentences used most within the scope; and determining a business ontology based on the identified frequently-used terms and associations within the plurality of sentences among the plurality of business documents. 4. The system according to claim 1 , wherein the processor determines an association by a proximity between at least two of the terms within at least one document.
| 0.5 |
9,767,095 | 12 | 13 |
12. A computer storage device storing computer-executable instructions that, when executed by a computing device, cause the computing device to perform actions comprising: receiving a source text in a source language; parsing the source text into separate portions; displaying on a graphical user environment (“GUE”) of the computing device, in response to the parsing, the separate portions in a translator workspace field, the translator workspace field editable by a human translator; selecting a portion of the separate portions in response to receiving a selection from the human translator indicative of one of the separate portions, wherein the selection from the human translator results in changes to the GUE; displaying a translation of the selected portion in a target language, a term for term translation of the selected portion in the target language, and the selected portion in the translator workspace field, wherein the term for term translation in the target language is displayed in a term order of the source text, a first term in the source text comprises a first format different from a second format of a second term in the source text, the first and second terms being adjacent to one another, a third term in the target language comprising the first format, the third term being the translation for the first term, and a fourth term in the target language comprising the second format, the fourth term being the translation for the second term, the first and second format comprise one or more of highlighted text, non-highlighted text, bolded text, non-bolded text, underlined text, non-underlined text, and text color, the human translator selectively applies the second format to the second term in the source text, and the second format is applied to the fourth term in response to the human translator selectively applying the second format to the second term; and enabling the human translator to override the translation for the selected portion by updating the translation for the selected portion with changes via the translator workspace field and displaying the updates on the GUE.
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12. A computer storage device storing computer-executable instructions that, when executed by a computing device, cause the computing device to perform actions comprising: receiving a source text in a source language; parsing the source text into separate portions; displaying on a graphical user environment (“GUE”) of the computing device, in response to the parsing, the separate portions in a translator workspace field, the translator workspace field editable by a human translator; selecting a portion of the separate portions in response to receiving a selection from the human translator indicative of one of the separate portions, wherein the selection from the human translator results in changes to the GUE; displaying a translation of the selected portion in a target language, a term for term translation of the selected portion in the target language, and the selected portion in the translator workspace field, wherein the term for term translation in the target language is displayed in a term order of the source text, a first term in the source text comprises a first format different from a second format of a second term in the source text, the first and second terms being adjacent to one another, a third term in the target language comprising the first format, the third term being the translation for the first term, and a fourth term in the target language comprising the second format, the fourth term being the translation for the second term, the first and second format comprise one or more of highlighted text, non-highlighted text, bolded text, non-bolded text, underlined text, non-underlined text, and text color, the human translator selectively applies the second format to the second term in the source text, and the second format is applied to the fourth term in response to the human translator selectively applying the second format to the second term; and enabling the human translator to override the translation for the selected portion by updating the translation for the selected portion with changes via the translator workspace field and displaying the updates on the GUE. 13. The computer storage device of claim 12 , wherein the term for term translation comprises a first term in the target language, the first term corresponding to a second term in the source language, wherein the first term is a translation of the second term, and wherein one or more of the first term and the second term comprise two or more words.
| 0.5 |
8,625,154 | 3 | 4 |
3. The apparatus of claim 2 , wherein the color information correction module comprises: a preference color input module which inputs a preference color to be corrected among preference colors constituting the input image; and a color component correction module which corrects a color component of the input preference color.
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3. The apparatus of claim 2 , wherein the color information correction module comprises: a preference color input module which inputs a preference color to be corrected among preference colors constituting the input image; and a color component correction module which corrects a color component of the input preference color. 4. The apparatus of claim 3 , wherein the color component correction module displays an image of the corrected result of the color component using soft-proofing.
| 0.5 |
8,990,070 | 14 | 15 |
14. The system of claim 9 where the operations further comprise identifying at least one child node within the grammar that is directly traversable from a parent node within the grammar, where the parent node is a non-terminal element within the grammar corresponding to a non-terminal display object in the displayed expression, and where the child node is one of a terminal element within the grammar and a non-terminal element within the grammar.
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14. The system of claim 9 where the operations further comprise identifying at least one child node within the grammar that is directly traversable from a parent node within the grammar, where the parent node is a non-terminal element within the grammar corresponding to a non-terminal display object in the displayed expression, and where the child node is one of a terminal element within the grammar and a non-terminal element within the grammar. 15. The system of claim 14 where the operations further comprise identifying the child node responsive to receiving selection of the non-terminal display object within the displayed expression.
| 0.5 |
9,043,413 | 12 | 13 |
12. The information processing system of claim 11 further comprising: providing tooling on the user interface to enable user manipulation of the search-based content.
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12. The information processing system of claim 11 further comprising: providing tooling on the user interface to enable user manipulation of the search-based content. 13. The information processing system of claim 12 wherein ranking the current objects of interest comprises sorting said current objects of interest based on at least one parameter selected from a group consisting of: time, type of object, history of interaction, buzzyness, and overall popularity.
| 0.514658 |
10,120,861 | 7 | 13 |
7. The method of claim 1 , wherein determining the normalized relevance scores for the input query text corresponding to the multiple domains comprises, for a domain of the multiple domains: sequencing the input query text into at least one sequence of substrings; tokenizing the at least one sequence of substrings into a set of token sequences comprising at least one token sequence with respect to the domain based on the ontology of the query model for the domain; obtaining a set of normalized relevance measures with respect to the domain, each normalized relevance measures corresponding to one token sequence of the set of token sequences of the domain based on trigrams appearing in the one token sequence and the trigram corpus of the domain; and determining, as one of the normalized relevance scores for the input query text corresponding to the multiple domains, a normalized relevance score with respect to the domain for the input query text based on the set of normalized relevance measures with respect to the domain.
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7. The method of claim 1 , wherein determining the normalized relevance scores for the input query text corresponding to the multiple domains comprises, for a domain of the multiple domains: sequencing the input query text into at least one sequence of substrings; tokenizing the at least one sequence of substrings into a set of token sequences comprising at least one token sequence with respect to the domain based on the ontology of the query model for the domain; obtaining a set of normalized relevance measures with respect to the domain, each normalized relevance measures corresponding to one token sequence of the set of token sequences of the domain based on trigrams appearing in the one token sequence and the trigram corpus of the domain; and determining, as one of the normalized relevance scores for the input query text corresponding to the multiple domains, a normalized relevance score with respect to the domain for the input query text based on the set of normalized relevance measures with respect to the domain. 13. The method of claim 7 , wherein determining the normalized relevance measure with respect to the domain for the input query text comprises determining as the normalized relevance measure for the input query text a maximum relevance measure among the set of normalized relevance measures with respect to the domain each corresponding to one token sequence of the set of token sequences.
| 0.630228 |
8,775,162 | 17 | 19 |
17. A method in accordance with claim 16 wherein: the scoring is on a scale ranging from negative to neutral to positive.
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17. A method in accordance with claim 16 wherein: the scoring is on a scale ranging from negative to neutral to positive. 19. A method in accordance with claim 17 wherein: the scoring involves persons.
| 0.746795 |
9,195,760 | 8 | 13 |
8. A computer program product embodied on a non-transitory computer readable medium, the computer program product including computer code adapted to be executed by a computer to perform a method comprising: receiving, from a user system at a host system having a processor system including at least one processor and a memory system, user input for conducting a search, the user input including one or more input terms; automatically searching, by the processor system, a storage area in the memory system at the host system for stored search strings recorded from prior searches that are similar to the user input, the search strings each having one or more search terms; identifying a subset of the stored search strings that are similar to the user input, as a result of the searching; automatically determining, by the host system, a score for each of the search strings in the subset, the score being a value that indicates an expected likelihood that the user will be interested in the search string, wherein the score for each of the search strings is based on a plurality of factors including: a count of a number of the input terms in the user input that are the same as the one or more the search terms in the search string, a relevancy of a collection of documents found when a search is performed using the search string, and how often users have chosen the search string when suggested by the host system; ranking the search strings in the subset, in accordance with the determined scores; and sending, from the host system to the user system, the search strings in the subset, listed in order of the ranking as search suggestions.
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8. A computer program product embodied on a non-transitory computer readable medium, the computer program product including computer code adapted to be executed by a computer to perform a method comprising: receiving, from a user system at a host system having a processor system including at least one processor and a memory system, user input for conducting a search, the user input including one or more input terms; automatically searching, by the processor system, a storage area in the memory system at the host system for stored search strings recorded from prior searches that are similar to the user input, the search strings each having one or more search terms; identifying a subset of the stored search strings that are similar to the user input, as a result of the searching; automatically determining, by the host system, a score for each of the search strings in the subset, the score being a value that indicates an expected likelihood that the user will be interested in the search string, wherein the score for each of the search strings is based on a plurality of factors including: a count of a number of the input terms in the user input that are the same as the one or more the search terms in the search string, a relevancy of a collection of documents found when a search is performed using the search string, and how often users have chosen the search string when suggested by the host system; ranking the search strings in the subset, in accordance with the determined scores; and sending, from the host system to the user system, the search strings in the subset, listed in order of the ranking as search suggestions. 13. The computer program product of claim 8 , wherein the score for each search string is further based on a total number of words that make up the search string.
| 0.85192 |
7,650,272 | 34 | 35 |
34. An apparatus for automatically evaluating Bayesian network models for decision support as set forth in claim 33 , wherein the BN model further includes at least one auxiliary node causally linked between at least one evidence node and at least one conclusion node.
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34. An apparatus for automatically evaluating Bayesian network models for decision support as set forth in claim 33 , wherein the BN model further includes at least one auxiliary node causally linked between at least one evidence node and at least one conclusion node. 35. An apparatus for automatically evaluating Bayesian network models for decision support as set forth in claim 34 , wherein the sampling is performed by a Monte Carlo algorithm.
| 0.5 |
8,676,565 | 34 | 37 |
34. A method implemented by one or more computer processors, the method comprising: clustering a plurality of semantic graphs that were formed based on a linguistic analysis of a corpus of user utterances into a plurality of semantic clusters through use of one or more proximity metrics; identifying which of the plurality of semantic clusters include divergent sub-clusters; and offering the identified semantic clusters for review in a user interface.
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34. A method implemented by one or more computer processors, the method comprising: clustering a plurality of semantic graphs that were formed based on a linguistic analysis of a corpus of user utterances into a plurality of semantic clusters through use of one or more proximity metrics; identifying which of the plurality of semantic clusters include divergent sub-clusters; and offering the identified semantic clusters for review in a user interface. 37. A method as described in claim 34 , wherein the clustering is performed to form sub-clusters that are obtained using clustering criteria that are tuned to a level of specificity of the semantic graphs.
| 0.689394 |
7,788,099 | 16 | 17 |
16. An apparatus comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes computer usable program code; and a processing unit connected to the bus system, wherein the processing unit executes the computer usable program code to annotate a corpus of multimodal content simultaneously using annotations from a plurality of vocabularies to form a set of common annotations; identify relationships between a first vocabulary associated with a first modality and a second vocabulary associated with a second modality using the set of common annotations to form a multimodal vocabulary mapping; and map items in the first vocabulary associated with the first modality to items in the second vocabulary associated with the second modality using the multimodal vocabulary mapping.
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16. An apparatus comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes computer usable program code; and a processing unit connected to the bus system, wherein the processing unit executes the computer usable program code to annotate a corpus of multimodal content simultaneously using annotations from a plurality of vocabularies to form a set of common annotations; identify relationships between a first vocabulary associated with a first modality and a second vocabulary associated with a second modality using the set of common annotations to form a multimodal vocabulary mapping; and map items in the first vocabulary associated with the first modality to items in the second vocabulary associated with the second modality using the multimodal vocabulary mapping. 17. The apparatus of claim 16 wherein the processor unit further executes the computer usable program code to identify a set of items in the second vocabulary that are mapped to query items associated with the first vocabulary to form a set of mapped items in a second modality in response to receiving a query to search for content that includes the query items associated with the first vocabulary and add the set of mapped items in the second modality to the query to form an expanded query, wherein the expanded query can be used to search for content in the first modality and the second modality simultaneously.
| 0.5 |
9,583,100 | 1 | 5 |
1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising the steps of: (a) receiving speech in a vehicle from a vehicle occupant using an audio user interface that is separate from the mobile device, wherein the audio user interface is communicatively linked directly to the mobile device via a short-range wireless connection; (b) recording the speech using the mobile device; (c) transmitting the recorded speech from the mobile device to a cloud speech service; (d) receiving automatic speech recognition (ASR) results from the cloud speech service at the mobile device; (e) determining that the received ASR results at the mobile device contain one or more error conditions; (f) obtaining a local speech recognition result, in response to the determination in step (e), by performing speech recognition on the speech received at the vehicle using a speech recognition resource that includes vehicle-related and/or user-related data that was not used by the cloud speech service in generating the ASR results; and (g) providing the local speech recognition result to the cloud speech service for use in improving subsequent recognition by the cloud speech service, wherein the local speech recognition result addresses the determined one or more error conditions.
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1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising the steps of: (a) receiving speech in a vehicle from a vehicle occupant using an audio user interface that is separate from the mobile device, wherein the audio user interface is communicatively linked directly to the mobile device via a short-range wireless connection; (b) recording the speech using the mobile device; (c) transmitting the recorded speech from the mobile device to a cloud speech service; (d) receiving automatic speech recognition (ASR) results from the cloud speech service at the mobile device; (e) determining that the received ASR results at the mobile device contain one or more error conditions; (f) obtaining a local speech recognition result, in response to the determination in step (e), by performing speech recognition on the speech received at the vehicle using a speech recognition resource that includes vehicle-related and/or user-related data that was not used by the cloud speech service in generating the ASR results; and (g) providing the local speech recognition result to the cloud speech service for use in improving subsequent recognition by the cloud speech service, wherein the local speech recognition result addresses the determined one or more error conditions. 5. The method of claim 1 , wherein the speech recognition resource includes a local speech recognition grammar.
| 0.767782 |
8,768,917 | 9 | 13 |
9. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying a candidate n-gram that includes two or more consecutive terms of a search query; determining a first quantity of search results that (i) were identified as responsive to the search query, and (ii) have been selected by other users; determining a second quantity of the search results that (i) were identified as responsive to the search query, (ii) have been selected by the other users, and (iii) are associated with text in which the candidate n-gram occurs; determining a value using the first quantity and the second quantity; and classifying the candidate n-gram as a particular type of n-gram, from among multiple types of n-grams, based on the determined value.
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9. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying a candidate n-gram that includes two or more consecutive terms of a search query; determining a first quantity of search results that (i) were identified as responsive to the search query, and (ii) have been selected by other users; determining a second quantity of the search results that (i) were identified as responsive to the search query, (ii) have been selected by the other users, and (iii) are associated with text in which the candidate n-gram occurs; determining a value using the first quantity and the second quantity; and classifying the candidate n-gram as a particular type of n-gram, from among multiple types of n-grams, based on the determined value. 13. The computer-readable medium of claim 9 , wherein the particular type of n-gram includes a combination of n terms that has a different meaning in combination than the n terms do separately.
| 0.660211 |
7,810,026 | 19 | 21 |
19. The method of claim 18 , wherein the optimized source document comprises reflowable content.
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19. The method of claim 18 , wherein the optimized source document comprises reflowable content. 21. The method of claim 19 , wherein each page record of content comprises a word table including a list of the words in the page of content.
| 0.753497 |
7,881,934 | 44 | 52 |
44. A system adjusting a voice prompt based upon a state of a user of the system, the system comprising: means for obtaining utterance parameters from utterance received from the user, the utterance parameters indicating the state of the user; means for determining the state of the user based upon the utterance parameters; and means for adjusting the voice prompt by adjusting at least one of a tone of voice of the voice prompt, a content of the voice prompt, a prosody of the voice prompt, and a gender of the voice prompt based upon the determined state of the user, wherein the means for obtaining utterance parameters comprises: means for partitioning the utterance into segments; and means for assigning one of a plurality of classifications to each segment, each classification corresponding to at least one of a plurality of states of the user, wherein the means for determining the state of the user based upon the utterance comprises: means for generating an utterance parameter vector based upon the utterance parameter by (1) determining the number of segments for each classification, and (2) dividing the number of segments for each classification by a total number of segments in the utterance.
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44. A system adjusting a voice prompt based upon a state of a user of the system, the system comprising: means for obtaining utterance parameters from utterance received from the user, the utterance parameters indicating the state of the user; means for determining the state of the user based upon the utterance parameters; and means for adjusting the voice prompt by adjusting at least one of a tone of voice of the voice prompt, a content of the voice prompt, a prosody of the voice prompt, and a gender of the voice prompt based upon the determined state of the user, wherein the means for obtaining utterance parameters comprises: means for partitioning the utterance into segments; and means for assigning one of a plurality of classifications to each segment, each classification corresponding to at least one of a plurality of states of the user, wherein the means for determining the state of the user based upon the utterance comprises: means for generating an utterance parameter vector based upon the utterance parameter by (1) determining the number of segments for each classification, and (2) dividing the number of segments for each classification by a total number of segments in the utterance. 52. The system of claim 44 , wherein the system is an on-board computer used in an automobile or a navigation system used in an automobile.
| 0.820876 |
8,762,152 | 1 | 8 |
1. A method of performing speech recognition using an electronic interactive agent, comprising: forming a communications link between a client device and a server system adapted for streaming speech data; providing a distributed speech recognition engine using resources from both the client device and the server system; presenting the electronic interactive agent in a form perceptible to a user of the client device; soliciting natural language speech utterance data in the form of continuous speech from the user of the device using the electronic interactive agent; recognizing said speech utterance data using said distributed speech recognition engine to generate a recognized speech statement and processing said recognized speech statement using a natural language engine to identify a best response to said recognized speech statement among a number of predefined, stored queries and associated answers, the natural language engine being adapted to consider words not in said queries and associated answers to determine the best response; if the best response is not identified with a specified confidence level using the natural language engine, presenting the recognized speech statement to one or more additional natural language engines; controlling the electronic interactive agent to communicate the best response to the recognized speech statement generated by the server system; wherein the electronic interactive agent is adapted to mimic behavior of a human agent through a natural language query session conducted with the user.
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1. A method of performing speech recognition using an electronic interactive agent, comprising: forming a communications link between a client device and a server system adapted for streaming speech data; providing a distributed speech recognition engine using resources from both the client device and the server system; presenting the electronic interactive agent in a form perceptible to a user of the client device; soliciting natural language speech utterance data in the form of continuous speech from the user of the device using the electronic interactive agent; recognizing said speech utterance data using said distributed speech recognition engine to generate a recognized speech statement and processing said recognized speech statement using a natural language engine to identify a best response to said recognized speech statement among a number of predefined, stored queries and associated answers, the natural language engine being adapted to consider words not in said queries and associated answers to determine the best response; if the best response is not identified with a specified confidence level using the natural language engine, presenting the recognized speech statement to one or more additional natural language engines; controlling the electronic interactive agent to communicate the best response to the recognized speech statement generated by the server system; wherein the electronic interactive agent is adapted to mimic behavior of a human agent through a natural language query session conducted with the user. 8. The method of claim 1 , wherein the method further comprises determining the resources available at the server.
| 0.636943 |
5,524,065 | 49 | 57 |
49. A method according to claim 48, further comprising a confidence level determining step determining step for determining confidence level of said plural candidates based on the distance values provided by the different distance functions.
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49. A method according to claim 48, further comprising a confidence level determining step determining step for determining confidence level of said plural candidates based on the distance values provided by the different distance functions. 57. A method according to claim 49, further comprising the step of providing a reject signal in a case where the confidence level is low.
| 0.684332 |
9,455,891 | 1 | 3 |
1. A method to determine a first network efficacy of a first social networking site to facilitate delivery of an advertisement to a user of the first social networking site, the method comprising: accessing, by executing an instruction with a processor, interaction data and contact data for the user of the first social networking site via an interface provided by the first social networking site; determining, by executing an instruction with the processor, a connectedness for the user based on the contact data; determining, by executing an instruction with the processor, an interactivity for the user based on the interaction data; determining, by executing an instruction with the processor, a network constancy for the user by determining a ratio of (a) connections between contacts of the user of the first social networking site to (b) at least one of: (1) broken connections between the contacts of the user in response to removal of the user from the first social networking site; or (2) connections between the contacts of the user that exhibit changed degrees of connection in response to removal of the user from the first social networking site; determining, by executing an instruction with the processor, the first network efficacy of the first social networking site based on the connectedness, the interactivity, and the network constancy, the network constancy being based on the ratio; and transmitting the first network efficacy from the processor to an advertising server to facilitate delivery of the advertisement from the advertising server to the user of the first social networking site.
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1. A method to determine a first network efficacy of a first social networking site to facilitate delivery of an advertisement to a user of the first social networking site, the method comprising: accessing, by executing an instruction with a processor, interaction data and contact data for the user of the first social networking site via an interface provided by the first social networking site; determining, by executing an instruction with the processor, a connectedness for the user based on the contact data; determining, by executing an instruction with the processor, an interactivity for the user based on the interaction data; determining, by executing an instruction with the processor, a network constancy for the user by determining a ratio of (a) connections between contacts of the user of the first social networking site to (b) at least one of: (1) broken connections between the contacts of the user in response to removal of the user from the first social networking site; or (2) connections between the contacts of the user that exhibit changed degrees of connection in response to removal of the user from the first social networking site; determining, by executing an instruction with the processor, the first network efficacy of the first social networking site based on the connectedness, the interactivity, and the network constancy, the network constancy being based on the ratio; and transmitting the first network efficacy from the processor to an advertising server to facilitate delivery of the advertisement from the advertising server to the user of the first social networking site. 3. The method as defined in claim 1 , wherein the determining of the connectedness is based on a number of first-degree contacts of the user and a number of second-degree contacts of the user, and the determining of the connectedness includes assigning a first weight to a first one of the first-degree contacts who has restricted a connection with the user, and assigning a second weight to a second one of the first-degree contacts who has not restricted a connection with the user.
| 0.60522 |
8,797,266 | 1 | 15 |
1. An apparatus comprising: an input device having input elements; and a processor programmed to receive an input code having component blocks that correspond to activation groupings of input elements of the input device, translate the input code to first text, check the first text against a dictionary, and when the first text does not match an entry in the dictionary, process the component blocks to generate one or more permutations that have different activation groupings of the input elements of the input device, translate the input code to second text, which is different than the first text, in accordance with the one or more permutations, and check the second text against the dictionary to determine if the second text is usable to replace the first text, wherein the processor is programmed to replace a component block having two digits with two new component blocks each having one digit, when the first text does not match an entry in the dictionary.
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1. An apparatus comprising: an input device having input elements; and a processor programmed to receive an input code having component blocks that correspond to activation groupings of input elements of the input device, translate the input code to first text, check the first text against a dictionary, and when the first text does not match an entry in the dictionary, process the component blocks to generate one or more permutations that have different activation groupings of the input elements of the input device, translate the input code to second text, which is different than the first text, in accordance with the one or more permutations, and check the second text against the dictionary to determine if the second text is usable to replace the first text, wherein the processor is programmed to replace a component block having two digits with two new component blocks each having one digit, when the first text does not match an entry in the dictionary. 15. The apparatus of claim 1 , wherein the processor is programmed to predict third text based on output text preferred by a user in response to activating an input element, wherein the third text includes the second text.
| 0.5 |
8,402,021 | 19 | 21 |
19. A computer-implemented method comprising: receiving a request requesting a search of discussion forums and a search query; receiving information from a search engine identifying a plurality of resources that each satisfy the search query; identifying a plurality of discussion thread web pages among the plurality of resources that each satisfy the search query, wherein each discussion thread web page is in a particular discussion forum; grouping the discussion thread web pages into a plurality of discussion forums; extracting information about each of the plurality of discussion forums from the discussion thread web pages in the respective discussion forum; and providing the respective extracted information together with a link to each of the plurality of discussion forums to a user device for display to a user as part of a response to the search query.
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19. A computer-implemented method comprising: receiving a request requesting a search of discussion forums and a search query; receiving information from a search engine identifying a plurality of resources that each satisfy the search query; identifying a plurality of discussion thread web pages among the plurality of resources that each satisfy the search query, wherein each discussion thread web page is in a particular discussion forum; grouping the discussion thread web pages into a plurality of discussion forums; extracting information about each of the plurality of discussion forums from the discussion thread web pages in the respective discussion forum; and providing the respective extracted information together with a link to each of the plurality of discussion forums to a user device for display to a user as part of a response to the search query. 21. The method of claim 19 , wherein each discussion thread web page includes one or more posts to a corresponding discussion forum, and wherein the search engine has determined that at least one post included in a discussion thread web page satisfies the search query.
| 0.773569 |
10,120,866 | 14 | 17 |
14. A computer-implemented method for behavior evaluation of a user in a conversation session, comprising: receiving, by a processor of a computer as part of the conversation session, a message from a user device, wherein the conversation session is between the user and an electronic conversational agent; determining, based on the message and one or more factors associated with the conversation session, a behavior measure associated with the user; determining, based on analyzing the behavior measure in relation to one or more historical factors associated with a subset of other users of the electronic conversational agent, whether the user is exhibiting anomalous behavior; when it is determined that the user is exhibiting anomalous behavior, automatically adapting the electronic conversational agent based on the determined anomalous behavior; and continuing the conversation session based on the adapted electronic conversational agent.
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14. A computer-implemented method for behavior evaluation of a user in a conversation session, comprising: receiving, by a processor of a computer as part of the conversation session, a message from a user device, wherein the conversation session is between the user and an electronic conversational agent; determining, based on the message and one or more factors associated with the conversation session, a behavior measure associated with the user; determining, based on analyzing the behavior measure in relation to one or more historical factors associated with a subset of other users of the electronic conversational agent, whether the user is exhibiting anomalous behavior; when it is determined that the user is exhibiting anomalous behavior, automatically adapting the electronic conversational agent based on the determined anomalous behavior; and continuing the conversation session based on the adapted electronic conversational agent. 17. The computer-implemented method of claim 14 , wherein automatically adapting the electronic conversational agent based on the determined anomalous behavior comprises: providing a challenge to the user device, wherein the challenge comprises at least a first part and a second part, wherein the first part is associated with an expected response; receiving, from the user device, a challenge response, wherein the challenge response comprises a first response part associated with the first part and a second response part associated with the second part; and determining, based on comparing the first response part to the expected response, a validity for the second response part.
| 0.5 |
9,875,737 | 1 | 6 |
1. A pre-training apparatus for speech recognition, the pre-training apparatus comprising: a memory and at least one processor coupled to the memory; a set of units configured to pre-train a deep neural network, the set of units comprising: an input unit configured to receive speech data; a model generation unit configured to initialize a connection weight of a deep neural network, based on the speech data; and an output unit configured to output information about the connection weight; wherein in order for a state of a phoneme unit corresponding to the speech data to be output, the model generation unit trains the connection weight by piling a plurality of hidden layers according to a determined structure of the deep neural network, applies an output layer to a certain layer between the plurality of hidden layers to correct the trained connection weight in each of the plurality of hidden layers, thereby initializing the connection weight, wherein when generating a structure of deep neural network by piling a plurality of hidden layers, the model generation unit applies the output layer to one hidden layer to correct a connection weight of the one hidden layer, removes the output layer, piles another hidden layer, applies the output layer to the other hidden layer to correct a connection weight of the other hidden layer, sequentially performs the application and correction on a next hidden layer to a last hidden layer to correct a connection weight of each of the hidden layers subsequent to the other hidden layer, thereby initializing the connection weight.
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1. A pre-training apparatus for speech recognition, the pre-training apparatus comprising: a memory and at least one processor coupled to the memory; a set of units configured to pre-train a deep neural network, the set of units comprising: an input unit configured to receive speech data; a model generation unit configured to initialize a connection weight of a deep neural network, based on the speech data; and an output unit configured to output information about the connection weight; wherein in order for a state of a phoneme unit corresponding to the speech data to be output, the model generation unit trains the connection weight by piling a plurality of hidden layers according to a determined structure of the deep neural network, applies an output layer to a certain layer between the plurality of hidden layers to correct the trained connection weight in each of the plurality of hidden layers, thereby initializing the connection weight, wherein when generating a structure of deep neural network by piling a plurality of hidden layers, the model generation unit applies the output layer to one hidden layer to correct a connection weight of the one hidden layer, removes the output layer, piles another hidden layer, applies the output layer to the other hidden layer to correct a connection weight of the other hidden layer, sequentially performs the application and correction on a next hidden layer to a last hidden layer to correct a connection weight of each of the hidden layers subsequent to the other hidden layer, thereby initializing the connection weight. 6. The pre-training apparatus of claim 1 , wherein the input unit performs communication over a wired network or a wireless network to receive the speech data, receives the speech data from a storage medium, or directly receives a speech and digitalizes the speech to convert the speech into speech data.
| 0.744538 |
9,118,618 | 8 | 12 |
8. A system, comprising: a packet buffer; and a hardware-based packet editor comprising a control memory and a control module, wherein the packet editor: receives a packet editing script comprising one or more script entries indicating modifications to be applied to a data packet and a data block comprising data for the modified packet; and stores the packet editing script in the control memory, wherein the control module: retrieves each given script entry stored in the control memory; copies data in the data block at a location and a size identified in the given script entry into the packet buffer; and generates a modified data packet with the data in the packet buffer, wherein copying ( 4 ) the data in the data block at the location and the size identified in the given script entry into the packet buffer, the control module: determines whether the given script entry is a first script entry for the modified data packet; and in response to determining that the given script entry is the first script entry for the modified data packet, reserves the packet buffer for the modified data packet; copies the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer; determines whether the given script entry is a last script entry for the modified data packet; and in response to determining that the given script entry is not the last script entry for the modified data packet, performs, for the next given script entry of the packet editing script, the copying of the data in the data block at the block location and with the block length identified in the given script entry into the packet buffer and the determining whether the given script entry is a last script entry for the modified data packet for the next given script entry of the packet editing script.
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8. A system, comprising: a packet buffer; and a hardware-based packet editor comprising a control memory and a control module, wherein the packet editor: receives a packet editing script comprising one or more script entries indicating modifications to be applied to a data packet and a data block comprising data for the modified packet; and stores the packet editing script in the control memory, wherein the control module: retrieves each given script entry stored in the control memory; copies data in the data block at a location and a size identified in the given script entry into the packet buffer; and generates a modified data packet with the data in the packet buffer, wherein copying ( 4 ) the data in the data block at the location and the size identified in the given script entry into the packet buffer, the control module: determines whether the given script entry is a first script entry for the modified data packet; and in response to determining that the given script entry is the first script entry for the modified data packet, reserves the packet buffer for the modified data packet; copies the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer; determines whether the given script entry is a last script entry for the modified data packet; and in response to determining that the given script entry is not the last script entry for the modified data packet, performs, for the next given script entry of the packet editing script, the copying of the data in the data block at the block location and with the block length identified in the given script entry into the packet buffer and the determining whether the given script entry is a last script entry for the modified data packet for the next given script entry of the packet editing script. 12. The system of claim 8 wherein in generating the modified data packet with the data in the packet buffer, the control module: in response to determining that the given script entry is the last script entry for the modified data packet, generates the modified data packet with the data in the packet buffer.
| 0.746305 |
8,645,372 | 19 | 23 |
19. A computing system comprising: a memory; a processor; an enhancement level setter module stored in the memory and configured, when executed by the processor, to: determine whether a name of a designated entity is likely to lead to relevancy errors when used in a search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; and when determined that the name of the designated entity is likely to lead to relevancy errors, determine an enhancement level for an initial query designated to be run against a keyword-based search engine API by performing a test to determine if a name of a designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; one or more enhancer modules stored in the memory and configured, when executed by the processor, to receive the determined enhancement level from the enhancement level setter module and produce a query strategy containing one or more subqueries that enhance the initial query using one or more of an entity-specific enhancement and/or a facet-specific enhancement to reduce ambiguity such that more on-topic results will be more likely to be produced; and a result retriever module stored in the memory and configured, when executed by the processor, to: receive the query strategy from the one or more enhancer modules and formulate enhanced subqueries in the syntax of the keyword-based search engine API; run the formulated enhanced subqueries using the keyword-based search engine API until sufficient results are obtained; and return the results.
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19. A computing system comprising: a memory; a processor; an enhancement level setter module stored in the memory and configured, when executed by the processor, to: determine whether a name of a designated entity is likely to lead to relevancy errors when used in a search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; and when determined that the name of the designated entity is likely to lead to relevancy errors, determine an enhancement level for an initial query designated to be run against a keyword-based search engine API by performing a test to determine if a name of a designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; one or more enhancer modules stored in the memory and configured, when executed by the processor, to receive the determined enhancement level from the enhancement level setter module and produce a query strategy containing one or more subqueries that enhance the initial query using one or more of an entity-specific enhancement and/or a facet-specific enhancement to reduce ambiguity such that more on-topic results will be more likely to be produced; and a result retriever module stored in the memory and configured, when executed by the processor, to: receive the query strategy from the one or more enhancer modules and formulate enhanced subqueries in the syntax of the keyword-based search engine API; run the formulated enhanced subqueries using the keyword-based search engine API until sufficient results are obtained; and return the results. 23. The system of claim 19 further comprising instructions stored in the memory of the computing system that are executed by the processor to effectuate the actions of the enhancement level setter module, the one or more enhancer modules, and the result retriever module.
| 0.5 |
8,145,654 | 1 | 8 |
1. A computer-implemented method for keyword searching, the method comprising: generating, by a server, tokens for a plurality of keywords in a document collection, wherein the generating further comprises determining a keyword position of a keyword in a document of the document collection, and determining a number of noisy keywords preceding the keyword in the document; merging the tokens to create an index; receiving a search query, wherein the search query includes at least one search phrase; receiving, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; searching the index for the at least one search phrase based on the indication received from the user; and when the indication from the user specifies a noiseless phrase search, performing the noiseless phrase search at least in part by subtracting a value of the keyword position by the number of noisy keywords preceding the keyword.
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1. A computer-implemented method for keyword searching, the method comprising: generating, by a server, tokens for a plurality of keywords in a document collection, wherein the generating further comprises determining a keyword position of a keyword in a document of the document collection, and determining a number of noisy keywords preceding the keyword in the document; merging the tokens to create an index; receiving a search query, wherein the search query includes at least one search phrase; receiving, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; searching the index for the at least one search phrase based on the indication received from the user; and when the indication from the user specifies a noiseless phrase search, performing the noiseless phrase search at least in part by subtracting a value of the keyword position by the number of noisy keywords preceding the keyword. 8. The computer-implemented method of claim 1 , wherein the noisy keywords offer limited value in search processing while introducing additional processing costs.
| 0.839286 |
5,488,725 | 1 | 7 |
1. In a computer system for identifying a predetermined number of documents of a document collection containing representations that have high probabilities of matching a query containing a plurality of concepts, in which the system has a database containing identifications of documents in the document collection and defining a plurality of representations representing the contents of the documents, the collection comprising a plurality of documents, and query means for defining the query, apparatus comprising: sample selection means for iteratively selecting successive samples of a plurality of documents from the collection, each sample containing fewer documents than the entire collection and each successive sample containing documents different from each previous sample; processing means responsive to the sample selection means for calculating, during each iteration, probabilities that documents contained in the sample contain representations that match the query and for identifying a preselected number of documents having the highest probabilities, the documents being identified during an iteration from a group consisting of the respective sample of documents and the documents identified during the next previous iteration, the preselected number being different for each iteration and no greater than the predetermined number; and output means outputting the identifications of the predetermined number of documents identified by the processing means.
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1. In a computer system for identifying a predetermined number of documents of a document collection containing representations that have high probabilities of matching a query containing a plurality of concepts, in which the system has a database containing identifications of documents in the document collection and defining a plurality of representations representing the contents of the documents, the collection comprising a plurality of documents, and query means for defining the query, apparatus comprising: sample selection means for iteratively selecting successive samples of a plurality of documents from the collection, each sample containing fewer documents than the entire collection and each successive sample containing documents different from each previous sample; processing means responsive to the sample selection means for calculating, during each iteration, probabilities that documents contained in the sample contain representations that match the query and for identifying a preselected number of documents having the highest probabilities, the documents being identified during an iteration from a group consisting of the respective sample of documents and the documents identified during the next previous iteration, the preselected number being different for each iteration and no greater than the predetermined number; and output means outputting the identifications of the predetermined number of documents identified by the processing means. 7. The apparatus according to claim 1 wherein the processing means includes a result list ranking the identified documents in probability order.
| 0.90137 |
8,155,960 | 8 | 9 |
8. A system comprising: a processor; a memory storing instructions for controlling the processor to perform steps comprising: identifying, in a database of utterances, first transcribed utterances and first un-transcribed utterances; identifying transcription candidate utterances from the first un-transcribed utterances; predicting likely recognition error utterances from the transcription candidate utterances; forwarding the likely recognition error utterances to a transcriber, to yield additional transcribed utterances; adding the additional transcribed utterances to the database of utterances, to yield an updated database of second transcribed utterances and second un-transcribed utterances; and if word accuracy has converged, modifying an automatic speech recognition system by providing both the second transcribed utterances and the second un-transcribed utterances to the automatic speech recognition system.
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8. A system comprising: a processor; a memory storing instructions for controlling the processor to perform steps comprising: identifying, in a database of utterances, first transcribed utterances and first un-transcribed utterances; identifying transcription candidate utterances from the first un-transcribed utterances; predicting likely recognition error utterances from the transcription candidate utterances; forwarding the likely recognition error utterances to a transcriber, to yield additional transcribed utterances; adding the additional transcribed utterances to the database of utterances, to yield an updated database of second transcribed utterances and second un-transcribed utterances; and if word accuracy has converged, modifying an automatic speech recognition system by providing both the second transcribed utterances and the second un-transcribed utterances to the automatic speech recognition system. 9. The system of claim 8 , wherein identifying transcription candidate utterances further comprises using confidence scores of the un-transcribed utterances.
| 0.712454 |
9,858,054 | 16 | 17 |
16. A system for optimizing a binary code in a language having access to a binary coded decimal (hereinafter referred to as BCD) variable by converting a BCD operation to a decimal floating point (hereinafter referred to as DFP) operation, the system comprising: a memory; a processor coupled to the memory; a module for optimizing a binary code communicatively coupled to the memory and the processor to carry out the steps of: generating a first compiler expression of the binary code; analyzing a use-definition chain and/or a definition-use chain for the first compiler expression; identifying logical BCD variables in the first compiler expression on the basis of a result of the analysis; generating a second compiler expression by assigning temporary variables to the identified logical BCD variables, wherein the second compiler expression includes packed decimal operations and the assigned temporary variables; and generating a third compiler expression by converting at least one of the packed decimal operations in the second compiler expression and at least one of the assigned temporary variables to the DFP operation if sign information and precision information are not lost by the conversion from the BCD operation to the DFP operation, wherein identifying logical BCD variables in the first compiler expression on the basis of a result of the analysis further includes: regarding an operand of definition (def) and an operand of use (use) as the same logical BCD variables in the use-definition and/or definition-use chains of operands in the first compiler expression, and wherein, regarding the operands as the same logical BCD variables, if, in the use-definition and/or definition-use chains of the operands in the first compiler expression, there is a use (use) dominated by a definition (def), there is not another definition (def) for the use (use) in any path between the definition (def) and the use (use), and the use (use) exists for the definition (def) as only one use, regarding operands of the use (use) and the definition (def) as the same logical BCD variables if: right-end addresses of the operands of the use (use) and the definition (def) are the same; the operands of the use (use) and the definition (def) are the same BCD type; a size of the operand of use (use) is larger than the size of the operand of definition (def); and zero is put in an area where the operand of use (use) and the operand of definition (def) do not overlap.
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16. A system for optimizing a binary code in a language having access to a binary coded decimal (hereinafter referred to as BCD) variable by converting a BCD operation to a decimal floating point (hereinafter referred to as DFP) operation, the system comprising: a memory; a processor coupled to the memory; a module for optimizing a binary code communicatively coupled to the memory and the processor to carry out the steps of: generating a first compiler expression of the binary code; analyzing a use-definition chain and/or a definition-use chain for the first compiler expression; identifying logical BCD variables in the first compiler expression on the basis of a result of the analysis; generating a second compiler expression by assigning temporary variables to the identified logical BCD variables, wherein the second compiler expression includes packed decimal operations and the assigned temporary variables; and generating a third compiler expression by converting at least one of the packed decimal operations in the second compiler expression and at least one of the assigned temporary variables to the DFP operation if sign information and precision information are not lost by the conversion from the BCD operation to the DFP operation, wherein identifying logical BCD variables in the first compiler expression on the basis of a result of the analysis further includes: regarding an operand of definition (def) and an operand of use (use) as the same logical BCD variables in the use-definition and/or definition-use chains of operands in the first compiler expression, and wherein, regarding the operands as the same logical BCD variables, if, in the use-definition and/or definition-use chains of the operands in the first compiler expression, there is a use (use) dominated by a definition (def), there is not another definition (def) for the use (use) in any path between the definition (def) and the use (use), and the use (use) exists for the definition (def) as only one use, regarding operands of the use (use) and the definition (def) as the same logical BCD variables if: right-end addresses of the operands of the use (use) and the definition (def) are the same; the operands of the use (use) and the definition (def) are the same BCD type; a size of the operand of use (use) is larger than the size of the operand of definition (def); and zero is put in an area where the operand of use (use) and the operand of definition (def) do not overlap. 17. The system according to claim 16 , wherein if, in the use-definition and/or definition-use chains of the operands in the first compiler expression, there is a use (use) dominated by a definition (def), there is not another definition (def) for the use (use) in any path between the definition (def) and the use (use), and the use (use) exists for the definition (def) as only one use, regarding operands of the use (use) and the definition (def) as the same logical BCD variables if: right-end addresses of the operands of the use (use) and the definition (def) are the same; the operands of the use (use) and the definition (def) are the same BCD type; and sizes of the operands of the use (use) and the definition (def) are the same.
| 0.584364 |
9,836,455 | 4 | 5 |
4. The non-transitory computer readable medium of claim 3 , wherein the at least one characteristic further includes a combination of words, and wherein the processing arrangement is further configured to generate the information by removing each word and every combination of words from the at least one document when performing procedures (c) and (d).
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4. The non-transitory computer readable medium of claim 3 , wherein the at least one characteristic further includes a combination of words, and wherein the processing arrangement is further configured to generate the information by removing each word and every combination of words from the at least one document when performing procedures (c) and (d). 5. The non-transitory computer readable medium of claim 4 , wherein the processing arrangement is further configured to omit at least some of the words or at least some combination of words when performing procedures (c) and (d).
| 0.5 |
9,916,307 | 14 | 20 |
14. A method for dynamically evaluating an electronic communication comprising: observing an electronic communication; upon detecting of movement of indicia proximal to a phrase in the communication, activating an idiom search application; the activated application: identifying an idiom within the phrase; searching a corpus for a translation of the idiom and one or more associated characteristics; in response to detection of the translation, collecting profile metadata related to the observed communication, comparing the one or more characteristics with the collected profile metadata, and storing the identified idiom and the collected profile metadata in the corpus; and in response to absence of the translation, dynamically translating the idiom, and presenting the translated idiom proximal to the evaluated expression.
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14. A method for dynamically evaluating an electronic communication comprising: observing an electronic communication; upon detecting of movement of indicia proximal to a phrase in the communication, activating an idiom search application; the activated application: identifying an idiom within the phrase; searching a corpus for a translation of the idiom and one or more associated characteristics; in response to detection of the translation, collecting profile metadata related to the observed communication, comparing the one or more characteristics with the collected profile metadata, and storing the identified idiom and the collected profile metadata in the corpus; and in response to absence of the translation, dynamically translating the idiom, and presenting the translated idiom proximal to the evaluated expression. 20. The method of claim 14 , further comprising: parsing the phrase and isolating two or more component phrases; comparing a structure of the isolated component phrases to a structure of stored idioms in the corpus; detecting a match between at least one of the isolated component phrases and a stored idiom in the corpus; and identifying the translation utilizing the detected match.
| 0.5 |
6,154,222 | 9 | 11 |
9. The method of claim 8 further including the step of defining a plurality of said major animation parameters, wherein each of said major animation parameters presents a different animation sequence.
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9. The method of claim 8 further including the step of defining a plurality of said major animation parameters, wherein each of said major animation parameters presents a different animation sequence. 11. The method of claim 9 further including the step of defining a plurality of said major animation parameters, wherein each of said major animation parameters presents a different human expression.
| 0.644643 |
7,698,652 | 1 | 8 |
1. An apparatus having a user interface assisting in searching for information from items of an ordered list in a data array, the items having descriptions, the apparatus comprising: a display; an array scroller for sequentially displaying on the display the descriptions from the ordered list on the user interface responsive to user actuation; and a helper character-generator operative to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the displaying of the helper character being responsive to continued user actuation of the array scroller, wherein the helper character is displayed in a size which is larger than a size of the descriptions, wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation.
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1. An apparatus having a user interface assisting in searching for information from items of an ordered list in a data array, the items having descriptions, the apparatus comprising: a display; an array scroller for sequentially displaying on the display the descriptions from the ordered list on the user interface responsive to user actuation; and a helper character-generator operative to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the displaying of the helper character being responsive to continued user actuation of the array scroller, wherein the helper character is displayed in a size which is larger than a size of the descriptions, wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation. 8. The data processing apparatus of claim 1 , wherein the descriptions include alphabetical entries, and the helper character consist of a first alphabetical character of the description of the item in the ordered list being displayed on a display, and wherein deactivating and reactivating the array scroller adds to the display a next alphabetical character of the description.
| 0.5 |
9,189,471 | 12 | 14 |
12. An emotion recognition method comprising: using a processor, extracting, from input data for emotion recognition, sampling data corresponding to a time period, wherein the input data comprises a facial image of a user, a voice of the user, text input by the user, a temperature of the user, a location of the user, or a kind of an application being used by the user; using the processor, accumulatively segmenting the sampling data based on one or more predetermined time-domain windows to form a plurality of data segments, wherein each of the data segments subsequent to a first data segment, among the plurality of data segments, includes portions of the sampling data from a current sampling time period and all previous sampling time periods; creating, using the processor, a plurality of emotional segments that comprise a plurality of emotions corresponding to each of the respective data segments; and deciding, using the processor, at least two emotional segments of the respective data segments as the user's complex emotion.
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12. An emotion recognition method comprising: using a processor, extracting, from input data for emotion recognition, sampling data corresponding to a time period, wherein the input data comprises a facial image of a user, a voice of the user, text input by the user, a temperature of the user, a location of the user, or a kind of an application being used by the user; using the processor, accumulatively segmenting the sampling data based on one or more predetermined time-domain windows to form a plurality of data segments, wherein each of the data segments subsequent to a first data segment, among the plurality of data segments, includes portions of the sampling data from a current sampling time period and all previous sampling time periods; creating, using the processor, a plurality of emotional segments that comprise a plurality of emotions corresponding to each of the respective data segments; and deciding, using the processor, at least two emotional segments of the respective data segments as the user's complex emotion. 14. The emotion recognition method of claim 12 , further comprising calculating a plurality of probability values of a plurality of candidate emotions for each of the respective data segments.
| 0.5 |
4,710,130 | 15 | 16 |
15. A learning method, comprising: presenting an auditory stimulus to one ear of a person; presenting a first auditory responses to said stimulus, to the other ear of the person, at substantially the same time as the presentation of said stimulus; pausing momentarily; and presenting a second auditory response to said stimulus to both ears of the person, said second response being a reproduction of said first response.
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15. A learning method, comprising: presenting an auditory stimulus to one ear of a person; presenting a first auditory responses to said stimulus, to the other ear of the person, at substantially the same time as the presentation of said stimulus; pausing momentarily; and presenting a second auditory response to said stimulus to both ears of the person, said second response being a reproduction of said first response. 16. A learning method as in claim 15 wherein said stimulus comprises one or more words of a language known to the person, and and first response is a foreign language translation of said stimulus.
| 0.604839 |
7,912,702 | 1 | 9 |
1. A method of generating a statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases, the method comprising the steps of: (a) providing a set of content words which can be associated with user questions in the task domain; and using a computer system: (b) determining semantic variants for each word in said set of content words; wherein said semantic variants include at least synonyms; (c) forming a semantic set of questions related to said user questions based on said synonyms; (d) performing semantic decoding on said semantic set of questions, to identify a disambiguated set of questions; and (e) configuring n-gram probabilities for words and phrases in said SLM grammar based on said set of disambiguated questions; wherein said SLM grammar is configured to recognize semantic variants of questions posed to a natural language speech recognition engine.
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1. A method of generating a statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases, the method comprising the steps of: (a) providing a set of content words which can be associated with user questions in the task domain; and using a computer system: (b) determining semantic variants for each word in said set of content words; wherein said semantic variants include at least synonyms; (c) forming a semantic set of questions related to said user questions based on said synonyms; (d) performing semantic decoding on said semantic set of questions, to identify a disambiguated set of questions; and (e) configuring n-gram probabilities for words and phrases in said SLM grammar based on said set of disambiguated questions; wherein said SLM grammar is configured to recognize semantic variants of questions posed to a natural language speech recognition engine. 9. The method of claim 1 , wherein said topic questions are derived automatically by analyzing said content of said task domain.
| 0.721739 |
9,213,768 | 14 | 24 |
14. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: cause a query to be transmitted via a network to a query answering system, wherein the query is in an imprecise syntax and includes a word having multiple meanings or senses; receive query results that are based on a first meaning or sense of the word in response to the query, wherein: when the word is not recognized by the query answering system, the query answering system: determines, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, one or more entities to which the word corresponds, or chooses, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, the first meaning or sense; when the word is recognized by the query answering system and the word refers to multiple entities, the query answering system determines, with one or more computing devices, the entities to which the word corresponds; when the word corresponds to multiple entities in a same category, the query answering system ranks, with one or more computing devices, the multiple entities in the same category to which the word corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, the multiple meanings or senses of the word based on attributes of a user; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, one or more meanings or senses of the word based on a measure of popularity of the one or more meanings or senses; and when the word corresponds to multiple entities in a same category, or the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system chooses, with one or more computing devices, the first meaning or sense based on the rankings; receive an indication of the first meaning or sense of the word in response to the query, wherein the first meaning or sense corresponds to an entity in a category; receive a user interface mechanism to permit selection of another meaning or sense from a set of one or more meanings or senses different than the first meaning or sense in response to the query; and cause the query results, the indication of the first meaning or sense of the word, and the user interface mechanism to be displayed on a display device, wherein a list of entities in the same category to which the word corresponds are displayed in an order according to a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories.
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14. A tangible, non-transitory storage medium having stored thereon machine executable instructions, the machine executable instructions, when executed by one or more machines, cause the one or more machines to: cause a query to be transmitted via a network to a query answering system, wherein the query is in an imprecise syntax and includes a word having multiple meanings or senses; receive query results that are based on a first meaning or sense of the word in response to the query, wherein: when the word is not recognized by the query answering system, the query answering system: determines, based at least in part on relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, one or more entities to which the word corresponds, or chooses, based at least in part on the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word, the first meaning or sense; when the word is recognized by the query answering system and the word refers to multiple entities, the query answering system determines, with one or more computing devices, the entities to which the word corresponds; when the word corresponds to multiple entities in a same category, the query answering system ranks, with one or more computing devices, the multiple entities in the same category to which the word corresponds using a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, the multiple meanings or senses of the word based on attributes of a user; when the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system ranks, with one or more computing devices, one or more meanings or senses of the word based on a measure of popularity of the one or more meanings or senses; and when the word corresponds to multiple entities in a same category, or the word is recognized by the query answering system and the word has multiple meanings or senses, the query answering system chooses, with one or more computing devices, the first meaning or sense based on the rankings; receive an indication of the first meaning or sense of the word in response to the query, wherein the first meaning or sense corresponds to an entity in a category; receive a user interface mechanism to permit selection of another meaning or sense from a set of one or more meanings or senses different than the first meaning or sense in response to the query; and cause the query results, the indication of the first meaning or sense of the word, and the user interface mechanism to be displayed on a display device, wherein a list of entities in the same category to which the word corresponds are displayed in an order according to a set of attributes common to entities in the category, wherein the set of attributes is different than other sets of attributes common to entities in other categories. 24. The tangible, non-transitory storage medium according to claim 14 , wherein when the word is not recognized by the query answering system, the query results are determined from a keyword generated based on an analysis of the relative placement of alphabetic characters, numeric characters, and non-alphanumeric characters of the word.
| 0.5 |
6,088,698 | 21 | 38 |
21. A computer-readable medium carrying one or more sequences of one or more instructions for selectively generating a display of a region of an image from a description of the image, the one or more sequences of one or more instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving a request from a client for at least part of said image; in response to receiving said request, performing the steps of: (A) determining a field of view of said client relative to said image; (B) selecting a portion of said description based on said field of view; (C) generating a source text based on the portion of said description that was selected based on said field of view; and (D) delivering the source text to the client.
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21. A computer-readable medium carrying one or more sequences of one or more instructions for selectively generating a display of a region of an image from a description of the image, the one or more sequences of one or more instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving a request from a client for at least part of said image; in response to receiving said request, performing the steps of: (A) determining a field of view of said client relative to said image; (B) selecting a portion of said description based on said field of view; (C) generating a source text based on the portion of said description that was selected based on said field of view; and (D) delivering the source text to the client. 38. The computer-readable medium recited in claim 21, further comprising sequences of instructions for performing the steps of: receiving a source definition of the image; parsing the source definition into node values for a plurality of nodes that define elements of the image; and storing the node values in the description.
| 0.664609 |
9,466,031 | 7 | 9 |
7. A method carried out by a computer system having one or more processors and stored in one or more computer-readable media, the method comprising: receiving a set of feedback statistics, each feedback statistic represents a level of user satisfaction with a belief; calculating weighted statistics of the feedback statistics; calculates an entropy of the weighted statistics based on frequencies of occurrence of the weighted statistics; calculating a confidence value for the belief based on the entropy of the weighted statistics associated with the belief; calculating an updated belief based on the confidence value, the belief, and an average of the weighted statistics; and replacing the belief with the updated belief in the one or more computer-readable media.
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7. A method carried out by a computer system having one or more processors and stored in one or more computer-readable media, the method comprising: receiving a set of feedback statistics, each feedback statistic represents a level of user satisfaction with a belief; calculating weighted statistics of the feedback statistics; calculates an entropy of the weighted statistics based on frequencies of occurrence of the weighted statistics; calculating a confidence value for the belief based on the entropy of the weighted statistics associated with the belief; calculating an updated belief based on the confidence value, the belief, and an average of the weighted statistics; and replacing the belief with the updated belief in the one or more computer-readable media. 9. The method of claim 7 , wherein calculating the weighted statistics further comprises calculating a time-dependent weighted mean of the feedback statistics.
| 0.764095 |
8,417,288 | 7 | 9 |
7. A system comprising: a communication device comprising a microphone, a speaker, an input device, a display, and an antenna; a voice communicating implementer, wherein voice communication is implemented with another device in a wireless fashion; a caller's information displaying implementer, wherein upon receiving a phone call, a caller's information which indicates the phone number and/or name of the caller is displayed; an icon software implementer, wherein the software program indicated by an icon selected by the user is executed; and a multiple language mode implementer, wherein the language mode selected by the user is implemented, wherein said language mode selected is one of a plurality of language modes including a first language mode and a second language mode; wherein when said first language mode is selected by the user, a first command which is the command for the user to manipulate said communication device in a first manner and a second command which is the command for the user to manipulate said communication device in a second manner are displayed by utilizing a first language data; wherein when said second language mode is selected by the user, said first command which is the command for the user to manipulate said communication device in said first manner and said second command which is the command for the user to manipulate said communication device in said second manner are displayed by utilizing a second language data; wherein when said communication device is powered off under said first language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said first language data; and wherein when said communication device is powered off under said second language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said second language data.
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7. A system comprising: a communication device comprising a microphone, a speaker, an input device, a display, and an antenna; a voice communicating implementer, wherein voice communication is implemented with another device in a wireless fashion; a caller's information displaying implementer, wherein upon receiving a phone call, a caller's information which indicates the phone number and/or name of the caller is displayed; an icon software implementer, wherein the software program indicated by an icon selected by the user is executed; and a multiple language mode implementer, wherein the language mode selected by the user is implemented, wherein said language mode selected is one of a plurality of language modes including a first language mode and a second language mode; wherein when said first language mode is selected by the user, a first command which is the command for the user to manipulate said communication device in a first manner and a second command which is the command for the user to manipulate said communication device in a second manner are displayed by utilizing a first language data; wherein when said second language mode is selected by the user, said first command which is the command for the user to manipulate said communication device in said first manner and said second command which is the command for the user to manipulate said communication device in said second manner are displayed by utilizing a second language data; wherein when said communication device is powered off under said first language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said first language data; and wherein when said communication device is powered off under said second language mode and powered on thereafter, said first command and said second command after said communication device is powered on are automatically displayed by utilizing said second language data. 9. The system of claim 7 , wherein said communication device is a handheld audiovisual communication device.
| 0.698324 |
8,332,434 | 1 | 5 |
1. A computer-implemented method to map a set of words to a set of ontology terms, the method comprising: determining a starting point for each of a plurality of ontology contexts, each of the starting points including terms matching a set of words, the set of words including a plurality of words; determining a term set corresponding to the set of words in the ontology context of each of the starting points; ranking the starting points and selectively using a predetermined number of the ranked starting points; ranking the term sets determined for all of the starting points; and providing an output of the term sets in a ranked order.
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1. A computer-implemented method to map a set of words to a set of ontology terms, the method comprising: determining a starting point for each of a plurality of ontology contexts, each of the starting points including terms matching a set of words, the set of words including a plurality of words; determining a term set corresponding to the set of words in the ontology context of each of the starting points; ranking the starting points and selectively using a predetermined number of the ranked starting points; ranking the term sets determined for all of the starting points; and providing an output of the term sets in a ranked order. 5. The computer-implemented method of claim 1 , wherein the determining of a starting point further comprises determining a cover rate for an ontology by: generating a semantically-related term list for each word in the set of words; collecting, in a data structure, all of the different namespaces appearing in the terms in each semantically-related term list generated for each word; and determining a number of the set of words covered by a namespace ontology based on the number of occurrences of the namespace in each data structure.
| 0.548658 |
7,734,823 | 1 | 10 |
1. A computer-implemented method performed on a server in a network, comprising: storing in the server a structured document associated with an application that is executable on the server, the structured document defining a request URL mapping to the application and at least one rule for composing an instance of the application on the server using a set of one or more components, each of the components being defined in the structured document by a URI-addressable path and being one of: a presentation component, a code component and a data component; responsive to receipt at the server of a client request from a client, evaluating the client request; if the client request includes the request URL mapping to the application, retrieving the structured document associated with the application; using the structured document to compose an instance of the application on the server that includes the one or more components as defined in the structured document; generating a response to the client request using the instance of the application that has been composed on the server upon receipt of the client request; delivering the response to the client; after a given time period following delivery of the response, invalidating at least one component in the instance of the application so that the instance of the application is no longer available to respond to new client requests received at the server; and automatically invalidating any other component that was derived from the at least one component when the instance of the application was composed.
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1. A computer-implemented method performed on a server in a network, comprising: storing in the server a structured document associated with an application that is executable on the server, the structured document defining a request URL mapping to the application and at least one rule for composing an instance of the application on the server using a set of one or more components, each of the components being defined in the structured document by a URI-addressable path and being one of: a presentation component, a code component and a data component; responsive to receipt at the server of a client request from a client, evaluating the client request; if the client request includes the request URL mapping to the application, retrieving the structured document associated with the application; using the structured document to compose an instance of the application on the server that includes the one or more components as defined in the structured document; generating a response to the client request using the instance of the application that has been composed on the server upon receipt of the client request; delivering the response to the client; after a given time period following delivery of the response, invalidating at least one component in the instance of the application so that the instance of the application is no longer available to respond to new client requests received at the server; and automatically invalidating any other component that was derived from the at least one component when the instance of the application was composed. 10. The method as described in claim 1 wherein the instance of the application is composed by using a code component to process a data component to generate a derived data component.
| 0.542714 |
9,576,042 | 24 | 25 |
24. The system of claim 23 , wherein the search term is categorized as a type that is provided for registration to a user with recognized association with the search term if the ratio of the number of times the search result was selected subsequent to receiving the search term to the number of times that the search term appears in the search history exceeds a third threshold value greater than the first threshold value.
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24. The system of claim 23 , wherein the search term is categorized as a type that is provided for registration to a user with recognized association with the search term if the ratio of the number of times the search result was selected subsequent to receiving the search term to the number of times that the search term appears in the search history exceeds a third threshold value greater than the first threshold value. 25. The system of claim 24 , wherein the search term is categorized as a type that is excluded from registration if the ratio of the number of times the search result was selected subsequent to receiving the search term to the number of times that the search term appears in the search history does not exceed the third threshold value.
| 0.5 |
9,804,687 | 12 | 19 |
12. A method of controlling a digital television, the method comprising: displaying, via a display unit, a keypad including a plurality of key buttons which are assigned with different alphabet characters, respectively, and a text window; receiving, via a controller, a first signal selecting a first key button of the plurality of key buttons; displaying, via a controller, a first alphabet character assigned with the first key button in the text window, and displaying a first sub key button assigned with a second alphabet character on a region adjacent to the first key button of the keypad, in response to the first signal, the first sub key button partially overlapping a second key button neighboring to the first key button; receiving, via a controller, a second signal selecting the first sub key button; and displaying, via a controller, the second alphabet character next to the first alphabet character in the text window, and displaying a second sub key button assigned with a third alphabet character on the same region adjacent to the first key button of the keypad, in response to the second signal, the second sub key button partially overlapping the same second key button neighboring to the first key button, wherein the second alphabet character is predicted as a next character of the first alphabet character, and wherein the third alphabet character is predicted as a next character of the first and second alphabet characters.
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12. A method of controlling a digital television, the method comprising: displaying, via a display unit, a keypad including a plurality of key buttons which are assigned with different alphabet characters, respectively, and a text window; receiving, via a controller, a first signal selecting a first key button of the plurality of key buttons; displaying, via a controller, a first alphabet character assigned with the first key button in the text window, and displaying a first sub key button assigned with a second alphabet character on a region adjacent to the first key button of the keypad, in response to the first signal, the first sub key button partially overlapping a second key button neighboring to the first key button; receiving, via a controller, a second signal selecting the first sub key button; and displaying, via a controller, the second alphabet character next to the first alphabet character in the text window, and displaying a second sub key button assigned with a third alphabet character on the same region adjacent to the first key button of the keypad, in response to the second signal, the second sub key button partially overlapping the same second key button neighboring to the first key button, wherein the second alphabet character is predicted as a next character of the first alphabet character, and wherein the third alphabet character is predicted as a next character of the first and second alphabet characters. 19. The method of claim 12 , further comprising: concurrently displaying both the second sub key button assigned with the third alphabet character and a fourth key button assigned with the same third alphabet character.
| 0.5 |
8,065,196 | 2 | 5 |
2. The computer-implemented method of claim 1 , further comprising: receiving, from the user, personalization data comprising a personalized message, a name and an address of a stationery recipient, a user-selected stationery formatting option for the one of the stationery templates selected by the user.
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2. The computer-implemented method of claim 1 , further comprising: receiving, from the user, personalization data comprising a personalized message, a name and an address of a stationery recipient, a user-selected stationery formatting option for the one of the stationery templates selected by the user. 5. The computer-implemented method of claim 2 , further comprising: applying the personalization data to the one of the stationery templates selected by the user to generate the personalized stationery design.
| 0.646959 |
6,084,536 | 4 | 7 |
4. An apparatus as claimed in claim 1, the apparatus further comprising sync word generator means for generating a sync word for a block of p consecutive code words in the modulated signal, the sync word generator means being adapted to generate said sync word from the following set of available sync words: 11100011111110, 10100011111110, 01100011111110 and 11000100000001, the sync word generator means being adapted to select one of the sync words in dependence upon the coding state.
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4. An apparatus as claimed in claim 1, the apparatus further comprising sync word generator means for generating a sync word for a block of p consecutive code words in the modulated signal, the sync word generator means being adapted to generate said sync word from the following set of available sync words: 11100011111110, 10100011111110, 01100011111110 and 11000100000001, the sync word generator means being adapted to select one of the sync words in dependence upon the coding state. 7. An apparatus as claimed in claim 4, wherein the sync words generated present bit patterns that cannot occur in the bit sequence of the codewords.
| 0.5 |
8,327,320 | 10 | 11 |
10. The method of claim 9 , wherein the ordered sequence includes a third process element assigned the process identifier and the process state identifier followed by at least one process element assigned the process identifier and the sequence identifier.
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10. The method of claim 9 , wherein the ordered sequence includes a third process element assigned the process identifier and the process state identifier followed by at least one process element assigned the process identifier and the sequence identifier. 11. The method of claim 10 , wherein the ordered sequence includes a fourth process element assigned the process identifier and the process state change identifier that precedes at least one process element assigned the process identifier and the process state identifier.
| 0.5 |
8,380,705 | 4 | 5 |
4. The method of claim 1 , further comprising combining additional click data with the combined weighted click data to generate the score, wherein the additional click data indicates how frequently the document was selected when the document was presented in search results for the search query.
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4. The method of claim 1 , further comprising combining additional click data with the combined weighted click data to generate the score, wherein the additional click data indicates how frequently the document was selected when the document was presented in search results for the search query. 5. The method of claim 4 , wherein the combined weighted click data is adjusted by a blending factor before it is combined with the additional click data, wherein the blending factor indicates a degree to which the click data for the document and the one or more related search queries reliably indicates user behavior with regard to the search query.
| 0.5 |
8,370,364 | 18 | 19 |
18. The computer program product of claim 14 , further including a sixth executable portion for, previous to querying the plurality of time zone offsets, determining if a time zone setting is known.
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18. The computer program product of claim 14 , further including a sixth executable portion for, previous to querying the plurality of time zone offsets, determining if a time zone setting is known. 19. The computer program product of claim 18 , further including a seventh executable portion for, if the time zone setting is known, selecting the time zone setting to format a time stamped output.
| 0.5 |
10,140,880 | 16 | 18 |
16. A non-transitory computer-readable medium that includes computer-readable instructions stored thereon that are executable by a processor to perform or control performance of operations comprising: locating a plurality of occurrences of a knowledge point in a learning material; selecting one or more candidate initial points from the plurality of occurrences of the knowledge point; setting a first candidate initial point of the one or more candidate initial points as a first initial point; creating a first window in the learning material that includes the first initial point, wherein the first window includes a first-window size that corresponds to one or more basic units; creating a second window in the learning material, wherein a start of the second window follows a start of the first window by a first separation size, and wherein the second window includes a second-window size that corresponds to the one or more basic units; calculating a window similarity between first-window content of the first window and second-window content of the second window; in response to the window similarity between the first-window content of the first window and the second-window content of the second window meeting a similarity threshold, generating a first segment with first-segment content that includes at least the first-window content and the second-window content; detecting a position for a first segment border of the first segment that indicates an end of the first segment in which the detecting includes: sliding the first window and the second window through the learning material by a step size to create a first new window and a second new window such that the second-window content of the second window is the same as a first new-window content of the first new window; and determining whether a new-window similarity between the first new-window content and a second new-window content meet the similarity threshold; calculating a first-segment consistency measurement for the first segment based on a first-segment similarity between the first-segment content in the first segment and the knowledge point; ranking, according to one or more computer-executable expressions, the first segment with respect to one or more of the following: a second segment in the learning material and a third segment in a different learning material, wherein the ranking of the first segment is based on one or more of the following: a quality measurement, a learning material type of the learning material, a length of the first segment, and the first-segment consistency measurement of the first segment; and recommending the first segment to a learner based on the ranking of the first segment.
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16. A non-transitory computer-readable medium that includes computer-readable instructions stored thereon that are executable by a processor to perform or control performance of operations comprising: locating a plurality of occurrences of a knowledge point in a learning material; selecting one or more candidate initial points from the plurality of occurrences of the knowledge point; setting a first candidate initial point of the one or more candidate initial points as a first initial point; creating a first window in the learning material that includes the first initial point, wherein the first window includes a first-window size that corresponds to one or more basic units; creating a second window in the learning material, wherein a start of the second window follows a start of the first window by a first separation size, and wherein the second window includes a second-window size that corresponds to the one or more basic units; calculating a window similarity between first-window content of the first window and second-window content of the second window; in response to the window similarity between the first-window content of the first window and the second-window content of the second window meeting a similarity threshold, generating a first segment with first-segment content that includes at least the first-window content and the second-window content; detecting a position for a first segment border of the first segment that indicates an end of the first segment in which the detecting includes: sliding the first window and the second window through the learning material by a step size to create a first new window and a second new window such that the second-window content of the second window is the same as a first new-window content of the first new window; and determining whether a new-window similarity between the first new-window content and a second new-window content meet the similarity threshold; calculating a first-segment consistency measurement for the first segment based on a first-segment similarity between the first-segment content in the first segment and the knowledge point; ranking, according to one or more computer-executable expressions, the first segment with respect to one or more of the following: a second segment in the learning material and a third segment in a different learning material, wherein the ranking of the first segment is based on one or more of the following: a quality measurement, a learning material type of the learning material, a length of the first segment, and the first-segment consistency measurement of the first segment; and recommending the first segment to a learner based on the ranking of the first segment. 18. The non-transitory computer-readable medium of claim 16 , wherein selecting the one or more candidate initial points from the plurality of occurrences of the knowledge point includes selecting, as a candidate initial point, an occurrence of the knowledge point located in: a title of a video included in the learning material, a transcript of the video, a title of an article included in the learning material, or a title corresponding to one or more slides included in the learning material.
| 0.821068 |
7,672,922 | 2 | 8 |
2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation).
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2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation). 8. The pointer-oriented object acquisition method according to claim 2 , characterized in that the diverse parts of a sentence, for example the object, the subject, the predicate, the attributes, the adverbial modifiers, the local modifier, the temporal modifier etc., which consist of several words, are initialized by the computer system of Artificial Intelligence of a cyborg or an android in interpreting with the other variables defined previously and provided with a value.
| 0.61557 |
8,024,327 | 1 | 5 |
1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value.
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1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value. 5. The method according to claim 1 , wherein the act of normalizing further comprises an act of calculating a standard deviation of an expected statistical distribution of the at least one identifying characteristic.
| 0.756757 |
8,775,406 | 1 | 13 |
1. A method of predicting content of a news story with a computing system comprising: a) identifying a first event described in first content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically determining a plurality of different alternative predicted states for said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; wherein prior published content describing said prior events is processed to generate new predicted content describing said plurality of different alternative predicted states for said first event; c) automatically generating queries to said knowledge domain and/or at least one search engine to locate published new content associated with said plurality of different predicted states; d) presenting search results or news stories to a user with the computing system which includes at least some of said new published content when such is identified at step (c).
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1. A method of predicting content of a news story with a computing system comprising: a) identifying a first event described in first content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically determining a plurality of different alternative predicted states for said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; wherein prior published content describing said prior events is processed to generate new predicted content describing said plurality of different alternative predicted states for said first event; c) automatically generating queries to said knowledge domain and/or at least one search engine to locate published new content associated with said plurality of different predicted states; d) presenting search results or news stories to a user with the computing system which includes at least some of said new published content when such is identified at step (c). 13. The method of claim 1 further including a step of presenting advertising within said interface based on an expected mental state of said user predicted based on a state of an event identified in said first topic news content.
| 0.598246 |
9,280,340 | 15 | 19 |
15. A computer program product in a non-transitory computer readable storage medium for use in a computing entity, the computer program product holding computer program instructions which, when executed, generate a software system pipeline comprising a set of elements, the computer program instructions comprising: code to store dependency data for one or more elements, the dependency data for at least a particular element having been derived from a data model generated as a result of executing at least one other pipeline in which the particular element was included; code to identify a first element; code to associate a second element to the first element to form a portion of the software system pipeline, wherein the particular element is one of the first and second elements; code to retrieve dependency data for at least one of the first and second elements, at least some of the retrieved dependency data being dependency data that was derived from the data model; and code to automatically generate descriptor data for the software system pipeline based on the retrieved dependency data.
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15. A computer program product in a non-transitory computer readable storage medium for use in a computing entity, the computer program product holding computer program instructions which, when executed, generate a software system pipeline comprising a set of elements, the computer program instructions comprising: code to store dependency data for one or more elements, the dependency data for at least a particular element having been derived from a data model generated as a result of executing at least one other pipeline in which the particular element was included; code to identify a first element; code to associate a second element to the first element to form a portion of the software system pipeline, wherein the particular element is one of the first and second elements; code to retrieve dependency data for at least one of the first and second elements, at least some of the retrieved dependency data being dependency data that was derived from the data model; and code to automatically generate descriptor data for the software system pipeline based on the retrieved dependency data. 19. The computer program product as described in claim 15 wherein the first element is identified using a visual editor.
| 0.808917 |
9,317,491 | 1 | 10 |
1. A method of generating an adaptable and interactive network document, comprising: extracting a visual layout of an interactive network document having a plurality of discrete interactive elements and published in a network accessible storage to be available to a plurality of web browsers installed on a plurality of client terminals; automatically calculating for said extracted visual layout, plurality of relative arrangement rules ranked according to an hierarchical order each one of said plurality of relative arrangement rules defining a relation between a layout parameter of one of said plurality of discrete interactive elements and a respective layout parameter of another of said plurality of discrete interactive elements; storing said plurality of relative arrangement rules in association with said interactive network document; receiving instructions to change said visual layout; and applying said instructions to change said visual layout of said interactive network document for generating accordingly a layout adjusted interactive network document having an adapted version of said visual layout wherein layout parameters of said plurality of discrete interactive elements are adapted according to said instructions such that said plurality of discrete interactive elements comply with said plurality of relative arrangement rules in said hierarchical order; and replacing said interactive network document with said layout adjusted interactive network document in said network accessible storage such that said layout adjusted interactive network document is available to said plurality of web browsers.
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1. A method of generating an adaptable and interactive network document, comprising: extracting a visual layout of an interactive network document having a plurality of discrete interactive elements and published in a network accessible storage to be available to a plurality of web browsers installed on a plurality of client terminals; automatically calculating for said extracted visual layout, plurality of relative arrangement rules ranked according to an hierarchical order each one of said plurality of relative arrangement rules defining a relation between a layout parameter of one of said plurality of discrete interactive elements and a respective layout parameter of another of said plurality of discrete interactive elements; storing said plurality of relative arrangement rules in association with said interactive network document; receiving instructions to change said visual layout; and applying said instructions to change said visual layout of said interactive network document for generating accordingly a layout adjusted interactive network document having an adapted version of said visual layout wherein layout parameters of said plurality of discrete interactive elements are adapted according to said instructions such that said plurality of discrete interactive elements comply with said plurality of relative arrangement rules in said hierarchical order; and replacing said interactive network document with said layout adjusted interactive network document in said network accessible storage such that said layout adjusted interactive network document is available to said plurality of web browsers. 10. A non-transitory computer readable medium comprising computer executable instructions adapted to perform the method of claim 1 .
| 0.801802 |
9,318,105 | 11 | 12 |
11. The system of claim 8 , wherein the phonetic similarity threshold is calculated by comparing a phonetic representation of strings in the grammars for the return value and the alternative return value.
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11. The system of claim 8 , wherein the phonetic similarity threshold is calculated by comparing a phonetic representation of strings in the grammars for the return value and the alternative return value. 12. The system of claim 11 , wherein the phonetic similarity threshold is calculated using a dynamic programming algorithm.
| 0.5 |
8,745,077 | 1 | 3 |
1. A method implemented by a computer comprising at least one processor and at least one memory for facilitating searching and matching of data, comprising: receiving an input data string including one or more ideographic elements; converting the input data string to a Latin-based input data string at least in part by deconstructing the one or more ideographic elements into constituent radicals or strokes and cross-referencing a constituent radical or stroke to a pre-defined Latin character so as to generate one or more sets of Latin characters; generating one or more input keys based on the Latin-based input data string, including replacing any element in the Latin-based input data string that has a corresponding sounds-alike element to generate a phonetic key; searching, using the one or more input keys, a reference database stored in a memory device for one or more candidate records, wherein similar records in the database are indexed by a common lookup key; and if the one or more candidate records are found, determining a match score of the one or more candidate records.
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1. A method implemented by a computer comprising at least one processor and at least one memory for facilitating searching and matching of data, comprising: receiving an input data string including one or more ideographic elements; converting the input data string to a Latin-based input data string at least in part by deconstructing the one or more ideographic elements into constituent radicals or strokes and cross-referencing a constituent radical or stroke to a pre-defined Latin character so as to generate one or more sets of Latin characters; generating one or more input keys based on the Latin-based input data string, including replacing any element in the Latin-based input data string that has a corresponding sounds-alike element to generate a phonetic key; searching, using the one or more input keys, a reference database stored in a memory device for one or more candidate records, wherein similar records in the database are indexed by a common lookup key; and if the one or more candidate records are found, determining a match score of the one or more candidate records. 3. The method of claim 1 wherein the converting the input data string to the Latin-based input data string comprises converting the input data string to one or more phonetic spellings of the one or more ideographic elements.
| 0.539095 |
8,065,303 | 16 | 18 |
16. A method of searching a database for different types of digital assets, the method comprising: storing data in a memory that is read by a computer, the data comprising a server application program and only one single document type definition (DTD) for use in storing, retrieving, searching, or tracking at least three different types of digital assets stored in a single database, each digital asset of the digital assets including content and metadata, the metadata including rights management information, the server application program including modules for a parser, a query language utility, and a style sheet processor; receiving a demand containing user entered search parameters for information pertaining to the at least three different types of digital assets; accessing the DTD by executing the server application program, the DTD defining declared elements for the at least three different types of digital assets and defining elements and attributes for rights management of the at least three different types of digital assets, the at least three different types of digital assets including photographs, promotional announcements, and at least one of movies, video recordings, audio recordings, voiceovers, graphics, artwork, or text documents, wherein the rights management elements and attributes comprise metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier, wherein the DTD defines metadata for photographs and metadata attributes for the photograph metadata, the photograph-metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions, wherein the DTD defines metadata for promotional announcements and metadata attributes for the promotional announcements metadata, the promotional-announcements-metadata attributes comprising at least one of: a definition for title, a definition for airmaster number, a definition for writer/producer, a definition for duration, a definition for announcer, a definition for trailer, a definition for kill date, a definition for comments, or a definition for Internet rights; converting the demand into a query to be transmitted to the database by using the query language utility; searching the at least three different types of the digital assets in accordance with the converted demand and the accessed DTD; and converting search results returned from the database into a style sheet for input to a client application by using the style sheet processor.
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16. A method of searching a database for different types of digital assets, the method comprising: storing data in a memory that is read by a computer, the data comprising a server application program and only one single document type definition (DTD) for use in storing, retrieving, searching, or tracking at least three different types of digital assets stored in a single database, each digital asset of the digital assets including content and metadata, the metadata including rights management information, the server application program including modules for a parser, a query language utility, and a style sheet processor; receiving a demand containing user entered search parameters for information pertaining to the at least three different types of digital assets; accessing the DTD by executing the server application program, the DTD defining declared elements for the at least three different types of digital assets and defining elements and attributes for rights management of the at least three different types of digital assets, the at least three different types of digital assets including photographs, promotional announcements, and at least one of movies, video recordings, audio recordings, voiceovers, graphics, artwork, or text documents, wherein the rights management elements and attributes comprise metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier, wherein the DTD defines metadata for photographs and metadata attributes for the photograph metadata, the photograph-metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions, wherein the DTD defines metadata for promotional announcements and metadata attributes for the promotional announcements metadata, the promotional-announcements-metadata attributes comprising at least one of: a definition for title, a definition for airmaster number, a definition for writer/producer, a definition for duration, a definition for announcer, a definition for trailer, a definition for kill date, a definition for comments, or a definition for Internet rights; converting the demand into a query to be transmitted to the database by using the query language utility; searching the at least three different types of the digital assets in accordance with the converted demand and the accessed DTD; and converting search results returned from the database into a style sheet for input to a client application by using the style sheet processor. 18. A computer system for performing the method of claim 16 , the system comprising: a server comprising the single database; a first computer readable storage medium comprising the DTD; and a second computer readable storage medium comprising the server application program.
| 0.5 |
8,364,686 | 19 | 22 |
19. A method performed by one or more computer devices, the method comprising: sampling, by at least one of the one or more computer devices, a document to obtain a plurality of sampled blocks; generating, by at least one of the one or more computer devices, a set of checksum values from the plurality of sampled blocks, where each checksum value, in the set of checksum values, identifies a respective one of a plurality of bits of a fingerprint for the document; and generating, by at least one of the one or more computer devices, the fingerprint, for the document, by flipping each bit, of the plurality of bits of the fingerprint, a quantity of times based on a quantity of checksum values, in the set of checksum values, that identify the bit.
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19. A method performed by one or more computer devices, the method comprising: sampling, by at least one of the one or more computer devices, a document to obtain a plurality of sampled blocks; generating, by at least one of the one or more computer devices, a set of checksum values from the plurality of sampled blocks, where each checksum value, in the set of checksum values, identifies a respective one of a plurality of bits of a fingerprint for the document; and generating, by at least one of the one or more computer devices, the fingerprint, for the document, by flipping each bit, of the plurality of bits of the fingerprint, a quantity of times based on a quantity of checksum values, in the set of checksum values, that identify the bit. 22. The method of claim 19 , where the set of checksum values is a subset of checksum values generated for the document, and where the method further comprises: selecting the subset of checksum values as a particular number of largest, unique checksum values of the checksum values generated for the document.
| 0.501613 |
8,219,275 | 1 | 3 |
1. A diagnosis engine ( 100 ) configured for estimating a status of an entity ( 150 , 200 ) with a plurality of components (c 1 , . . . , c n ) wherein at least one of the components is assumed to be in either a fault-free mode or be in exactly one of at least two fault modes, the diagnosis engine ( 100 ) comprising a processing unit ( 110 ) configured to receive first (D) and second (E) listings of respective diagnostic expressions (D 1 , . . . , D n ) and (E 1 , . . . , E m ) indicating at least one of said modes for at least one of said components (c 1 , . . . , c n ), and generate a status report (R) based on said first (D) and second (E) listings of respective diagnostic expressions (D 1 , . . . , D n ) and (E 1 , . . . , E m ), wherein the diagnosis engine ( 100 ) comprises: a first storage area ( 120 ) configured to store said first listing (D) of diagnostic expressions (D 1 , . . . , D n ) constituting a first part of said diagnostic expressions, and store said second listing (E) of diagnostic expressions (E 1 , . . . , E m ) constituting a second part of said diagnostic expressions; and a second storage area ( 130 ) configured to store a listing of enhanced diagnostic expressions (Q) indicating at least one of said modes for at least one of said components (c 1 , . . . , c n ), and the processing unit ( 110 ) is configured to: receive said first listing (D) of diagnostic expressions (D 1 , . . . , D n ); receive said second listing (E) of diagnostic expressions (E 1 , . . . , E m ); store said first and second listings (D; E) in the first storage area ( 120 ); create an empty listing of enhanced diagnostic expressions (Q) by clearing any contents of the second storage area ( 130 ), and thereafter, for each combination of diagnostic expressions (D i , E j ) in said first and second listings (D; E); generate a current joint diagnostic expression (Q new ) representing a conjunction of a first diagnostic expression (D i ) from said first listing (D) of diagnostic expressions (D 1 , . . . , D n ) and a second diagnostic expression (E j ) from said second listing (E) of diagnostic expressions (E 1 , . . . , E m ); compare the current joint diagnostic expression (Q new ) with each diagnostic expression in the listing of enhanced diagnostic expressions (Q) stored in the second storage area ( 130 ); discard the current joint diagnostic expression (Q new ), if there exists a previous expression (Q k ) in the listing of enhanced diagnostic expressions (Q), and the current joint diagnostic expression (Q new ) implies the previous expression (Q k ); discard the current joint diagnostic expression (Q new ), if there exists a first diagnostic expression (D k ) in said first listing (D) of diagnostic expressions (D 1 , . . . , D n ), the first diagnostic expression (D k ) having not yet been included in a joint diagnostic expression and the current joint diagnostic expression (Q new ) implies the first diagnostic expression (D k ); discard the current joint diagnostic expression (Q new ), if there exists a second diagnostic expression (E k ) in said second listing (E) of diagnostic expressions (E 1 , . . . , E m ), the second diagnostic expression (E k ) having not yet been included in a joint diagnostic expression and the current joint diagnostic expression (Q new ) implies the second diagnostic expression (E k ); otherwise store the joint diagnostic expression (Q new ) as an addition to the listing of enhanced diagnostic expressions (Q) in the second storage area ( 130 ); and generate a status report (R) based on the listing of enhanced diagnostic expressions (Q).
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1. A diagnosis engine ( 100 ) configured for estimating a status of an entity ( 150 , 200 ) with a plurality of components (c 1 , . . . , c n ) wherein at least one of the components is assumed to be in either a fault-free mode or be in exactly one of at least two fault modes, the diagnosis engine ( 100 ) comprising a processing unit ( 110 ) configured to receive first (D) and second (E) listings of respective diagnostic expressions (D 1 , . . . , D n ) and (E 1 , . . . , E m ) indicating at least one of said modes for at least one of said components (c 1 , . . . , c n ), and generate a status report (R) based on said first (D) and second (E) listings of respective diagnostic expressions (D 1 , . . . , D n ) and (E 1 , . . . , E m ), wherein the diagnosis engine ( 100 ) comprises: a first storage area ( 120 ) configured to store said first listing (D) of diagnostic expressions (D 1 , . . . , D n ) constituting a first part of said diagnostic expressions, and store said second listing (E) of diagnostic expressions (E 1 , . . . , E m ) constituting a second part of said diagnostic expressions; and a second storage area ( 130 ) configured to store a listing of enhanced diagnostic expressions (Q) indicating at least one of said modes for at least one of said components (c 1 , . . . , c n ), and the processing unit ( 110 ) is configured to: receive said first listing (D) of diagnostic expressions (D 1 , . . . , D n ); receive said second listing (E) of diagnostic expressions (E 1 , . . . , E m ); store said first and second listings (D; E) in the first storage area ( 120 ); create an empty listing of enhanced diagnostic expressions (Q) by clearing any contents of the second storage area ( 130 ), and thereafter, for each combination of diagnostic expressions (D i , E j ) in said first and second listings (D; E); generate a current joint diagnostic expression (Q new ) representing a conjunction of a first diagnostic expression (D i ) from said first listing (D) of diagnostic expressions (D 1 , . . . , D n ) and a second diagnostic expression (E j ) from said second listing (E) of diagnostic expressions (E 1 , . . . , E m ); compare the current joint diagnostic expression (Q new ) with each diagnostic expression in the listing of enhanced diagnostic expressions (Q) stored in the second storage area ( 130 ); discard the current joint diagnostic expression (Q new ), if there exists a previous expression (Q k ) in the listing of enhanced diagnostic expressions (Q), and the current joint diagnostic expression (Q new ) implies the previous expression (Q k ); discard the current joint diagnostic expression (Q new ), if there exists a first diagnostic expression (D k ) in said first listing (D) of diagnostic expressions (D 1 , . . . , D n ), the first diagnostic expression (D k ) having not yet been included in a joint diagnostic expression and the current joint diagnostic expression (Q new ) implies the first diagnostic expression (D k ); discard the current joint diagnostic expression (Q new ), if there exists a second diagnostic expression (E k ) in said second listing (E) of diagnostic expressions (E 1 , . . . , E m ), the second diagnostic expression (E k ) having not yet been included in a joint diagnostic expression and the current joint diagnostic expression (Q new ) implies the second diagnostic expression (E k ); otherwise store the joint diagnostic expression (Q new ) as an addition to the listing of enhanced diagnostic expressions (Q) in the second storage area ( 130 ); and generate a status report (R) based on the listing of enhanced diagnostic expressions (Q). 3. The diagnosis engine ( 100 ) according to claim 1 , wherein the processing unit ( 110 ) is configured to receive at least one of said first and second listings (D; E) from at least one auxiliary diagnosis engine being associated with at least a sub-group of said components (c 1 , . . . , c n ), said at least one listing (D; E) including status reports in respect of the sub-group of said components (c 1 , . . . , c n ) to which the at least one auxiliary diagnosis engine is associated.
| 0.5 |
8,626,613 | 1 | 15 |
1. A pegboard organization system for locating at least four products on a pegboard display, wherein each product among the at least four products is positioned according to a respective peg, the respective peg comprising at least one peg shaft for holding a product and at least one peg foot for coupling the peg to the pegboard display, the system comprising: a first strip comprising at least two first color bars, the first strip configured to be positioned in a first direction; and at least two second strips for positioning the at least four products, wherein each second strip is configured to be positioned in a second direction different from the first direction, and wherein each second strip is configured to position at least two products among the at least four products, each second strip comprising: a second color bar, and for each product positioned by each second strip: a product identifier for identifying the product, and a peg indicator for indicating a position of the respective peg on the pegboard display at which the respective peg is to be positioned, wherein the peg indicator comprises at least one first marker for indicating a position of the at least one peg shaft on the pegboard display such that a location for the product identified by the product identifier is indicated by the at least one first marker, wherein each first color bar respectively indicates a position of each second strip, wherein each first color bar is configured to respectively correspond to the second color bar on each second strip.
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1. A pegboard organization system for locating at least four products on a pegboard display, wherein each product among the at least four products is positioned according to a respective peg, the respective peg comprising at least one peg shaft for holding a product and at least one peg foot for coupling the peg to the pegboard display, the system comprising: a first strip comprising at least two first color bars, the first strip configured to be positioned in a first direction; and at least two second strips for positioning the at least four products, wherein each second strip is configured to be positioned in a second direction different from the first direction, and wherein each second strip is configured to position at least two products among the at least four products, each second strip comprising: a second color bar, and for each product positioned by each second strip: a product identifier for identifying the product, and a peg indicator for indicating a position of the respective peg on the pegboard display at which the respective peg is to be positioned, wherein the peg indicator comprises at least one first marker for indicating a position of the at least one peg shaft on the pegboard display such that a location for the product identified by the product identifier is indicated by the at least one first marker, wherein each first color bar respectively indicates a position of each second strip, wherein each first color bar is configured to respectively correspond to the second color bar on each second strip. 15. The system according to claim 1 , wherein the product identifier comprises a bar code for identifying the product.
| 0.731818 |
9,031,863 | 18 | 19 |
18. At least one non-transitory computer readable storage medium having computer program instructions stored thereon that are arranged to perform the following operations: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes a plurality of web pages that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining a corresponding set of terms; and providing the obtained terms for selection of one of a plurality of advertisements for displaying via the web page, the advertisement term list being separate from the plurality of advertisements.
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18. At least one non-transitory computer readable storage medium having computer program instructions stored thereon that are arranged to perform the following operations: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes a plurality of web pages that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining a corresponding set of terms; and providing the obtained terms for selection of one of a plurality of advertisements for displaying via the web page, the advertisement term list being separate from the plurality of advertisements. 19. The at least one computer readable storage medium of claim 18 , wherein the mapping comprises learning the mapping model based, at least in part, on a plurality of terms from the plurality of web pages.
| 0.762673 |
8,175,865 | 11 | 13 |
11. A text script generator for a corpus-based text-to-speech system configured with a computing device for text script searching and processing and a memory device for corpus storage, comprising: a search criteria selector constructed in said computing device for searching in a source corpus being stored in said memory device and having L sentences, and selecting N sentences with a best integrated efficiency as N best cases, L and N being natural numbers, N≦L; a performance index constructor constructed in said computing device and coupled to said search criteria selector, for providing covering rate and hit rate corresponding to all unit types in said source corpus; and a termination criteria detector constructed in said computing device and coupled to said search criteria selector, for generating a best case in the N traced cases as a text script upon detecting a termination criterion is reached; wherein said best integrated efficiency depends on a function of combining the covering rate efficiency of unit types, the hit rate efficiency of unit types, and the size of said text script.
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11. A text script generator for a corpus-based text-to-speech system configured with a computing device for text script searching and processing and a memory device for corpus storage, comprising: a search criteria selector constructed in said computing device for searching in a source corpus being stored in said memory device and having L sentences, and selecting N sentences with a best integrated efficiency as N best cases, L and N being natural numbers, N≦L; a performance index constructor constructed in said computing device and coupled to said search criteria selector, for providing covering rate and hit rate corresponding to all unit types in said source corpus; and a termination criteria detector constructed in said computing device and coupled to said search criteria selector, for generating a best case in the N traced cases as a text script upon detecting a termination criterion is reached; wherein said best integrated efficiency depends on a function of combining the covering rate efficiency of unit types, the hit rate efficiency of unit types, and the size of said text script. 13. The text script generator for a corpus-based text-to-speech system according to claim 11 , wherein said termination criterion is a function of at least one of threshold for text script size, covering rate of unit types, hit rate of unit types, and integrated rate.
| 0.591463 |
8,650,484 | 3 | 4 |
3. The method of claim 2 , wherein objects of the set of objects remain accessible for use via a panel that allows those objects to be accessed in the second editing context.
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3. The method of claim 2 , wherein objects of the set of objects remain accessible for use via a panel that allows those objects to be accessed in the second editing context. 4. The method of claim 3 , further comprising, in the second editing context: receiving a gesture to associate a second object with the first object; and in response to receiving the gesture, associating the second object with the first object and allowing the second object to be edited in the second editing context.
| 0.5 |
9,727,925 | 25 | 31 |
25. A system, comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements a process for, identifying an internal social network for an enterprise, collecting a set of messages from the internal social network, performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise, performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages, identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points, as a result of the performed semantic analysis, clustering together messages that are similar to each other, categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages, associating each category of the plurality of categories with one or more tags, associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages, determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations, and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word.
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25. A system, comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements a process for, identifying an internal social network for an enterprise, collecting a set of messages from the internal social network, performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise, performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages, identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points, as a result of the performed semantic analysis, clustering together messages that are similar to each other, categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages, associating each category of the plurality of categories with one or more tags, associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages, determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations, and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. 31. The system of claim 25 , in which analysis results are used by company management to tailor communications to employees.
| 0.614907 |
9,245,361 | 1 | 6 |
1. A method for consolidating a glyph of a font, comprising: normalizing a first contour in the glyph and a second contour in the glyph to generate a first normalized contour and a second normalized contour; comparing the first normalized contour to the second normalized contour, comprising at least one of comparing a first number of points of the first normalized contour to a second number of points of the second normalized contour, comparing a first position of points of the first normalized contour to a second position of points of the second normalized contour or comparing a first order of points of the first normalized contour to a second order of points of the second normalized contour; based upon the comparing, determining that the first normalized contour and the second normalized contour comprise at least one of a same number of points, a same position of points or a same order of points indicating that the first contour and the second contour correspond to a common contour; and based upon the determining, replacing the first contour with a first reference to a common simple glyph for the common contour and replacing the second contour with a second reference to the common simple glyph to consolidate the glyph.
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1. A method for consolidating a glyph of a font, comprising: normalizing a first contour in the glyph and a second contour in the glyph to generate a first normalized contour and a second normalized contour; comparing the first normalized contour to the second normalized contour, comprising at least one of comparing a first number of points of the first normalized contour to a second number of points of the second normalized contour, comparing a first position of points of the first normalized contour to a second position of points of the second normalized contour or comparing a first order of points of the first normalized contour to a second order of points of the second normalized contour; based upon the comparing, determining that the first normalized contour and the second normalized contour comprise at least one of a same number of points, a same position of points or a same order of points indicating that the first contour and the second contour correspond to a common contour; and based upon the determining, replacing the first contour with a first reference to a common simple glyph for the common contour and replacing the second contour with a second reference to the common simple glyph to consolidate the glyph. 6. The method of claim 1 , comprising: determining whether a desired consolidation threshold is met; and consolidating the glyph merely if the desired consolidation threshold is met.
| 0.547264 |
8,156,414 | 2 | 3 |
2. The method of claim 1 wherein a candidate character value is added to the set of candidate character values by: responsive to the location of the message string being contained within the first set of character positions and the location of the message string being contained within the second set of character positions, adding a character value at the location within the first string to the set of candidate character values and associating the first similarity value weight with the character value.
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2. The method of claim 1 wherein a candidate character value is added to the set of candidate character values by: responsive to the location of the message string being contained within the first set of character positions and the location of the message string being contained within the second set of character positions, adding a character value at the location within the first string to the set of candidate character values and associating the first similarity value weight with the character value. 3. The method of claim 2 wherein an exclusion character value is added to the set of exclusion character values by: responsive to the location of the message string being contained within the first set of character positions and the location of the message string not being contained within the second set of character positions, adding a character value at the location within the first string to the set of exclusion character values and associating a similarity value weight with the character value; and responsive to the location of the message string not being contained within the first set of character positions and the location of the message string being contained within the second set of character positions, adding a character value at the location within the second string to the set of exclusion character values and associating a similarity value weight with the character value.
| 0.5 |
9,547,689 | 9 | 10 |
9. The method of claim 7 , further comprising indexing the new security descriptor based upon the one or more users.
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9. The method of claim 7 , further comprising indexing the new security descriptor based upon the one or more users. 10. The method of claim 9 , wherein indexing includes performing indexing when a number of security descriptors is below a certain threshold.
| 0.5 |
7,778,866 | 1 | 24 |
1. A computerized system for developing software programs by conducting competitions using a communications server and a review board subsystem, the system comprising: a communications server for communicating as part of a first competition for a design of a software program a specification for the design of a software program to a first plurality of developers and for receiving from each of a subset of the first plurality of software developers, in response to the communicated specification, respective designs for the software program; a review board subsystem for facilitating a design review process for scoring each of the received designs using an electronic document scorecard and selecting one design from the received designs based at least in part on its score in the design review process; and wherein the communications server is also for communicating the selected design to a second plurality of software developers as part of a second competition for development of the software program designed in the first competition and receiving from each of a subset of the second plurality of software developers, in response to the communicated design, respective software programs; and wherein the review board subsystem is also for facilitating a software review process for scoring each of the received programs using an electronic document scorecard; and selecting one program from the received programs based at least in part on its score in the software review process.
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1. A computerized system for developing software programs by conducting competitions using a communications server and a review board subsystem, the system comprising: a communications server for communicating as part of a first competition for a design of a software program a specification for the design of a software program to a first plurality of developers and for receiving from each of a subset of the first plurality of software developers, in response to the communicated specification, respective designs for the software program; a review board subsystem for facilitating a design review process for scoring each of the received designs using an electronic document scorecard and selecting one design from the received designs based at least in part on its score in the design review process; and wherein the communications server is also for communicating the selected design to a second plurality of software developers as part of a second competition for development of the software program designed in the first competition and receiving from each of a subset of the second plurality of software developers, in response to the communicated design, respective software programs; and wherein the review board subsystem is also for facilitating a software review process for scoring each of the received programs using an electronic document scorecard; and selecting one program from the received programs based at least in part on its score in the software review process. 24. The system of claim 1 wherein the received program comprises one or more of source code, object code, and compiled code.
| 0.834225 |
9,684,643 | 1 | 3 |
1. A system for managing building plan documents, comprising: one or more computing devices; non-transitory computer readable memory storing program code that when executed by the one or more computing devices is configured to cause the system to perform operations comprising: receiving an electronic building plan document including a plurality of plan sheets; providing a first of the plurality of plan sheets for display; providing a user interface via which a user can select, via a predefined standard comments library, a first comment, the first comment comprising text, and associate a document to the first comment; providing a user interface via which the user can associate at least one of project type or discipline metadata with the first comment; storing a first plurality of comments in association with respective metadata; providing for display a comments list in association with the first plan sheet, the comments list including a second plurality of comments; at least partly in response to the user selecting a second comment with a specified plan sheet coordinate in the comments lists, providing the second comment for display over the first plan sheet at the plan sheet coordinate and causing the portion of the first plan sheet corresponding to the specified plan sheet to be substantially centered in a sheet review display pane; enabling the user to search for comments by specifying, via a search user interface, project type or discipline metadata, generating and providing comments search results in response to a search query received via the search user interface; providing a user interface via which the user can select a plurality of comments to be included in a plan correction list; generating a correction list of items that need to be corrected in order for at least one approval document to be issued, the correction list including a plurality of comments specified by a plurality of users wherein the correction list includes: a category value, associated comments, and respective sheet identifiers for comments included in the correction list; transmitting the correction list to at least one user; tracking approval status of one or more building-related approval documents and providing the approval status to one or more users.
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1. A system for managing building plan documents, comprising: one or more computing devices; non-transitory computer readable memory storing program code that when executed by the one or more computing devices is configured to cause the system to perform operations comprising: receiving an electronic building plan document including a plurality of plan sheets; providing a first of the plurality of plan sheets for display; providing a user interface via which a user can select, via a predefined standard comments library, a first comment, the first comment comprising text, and associate a document to the first comment; providing a user interface via which the user can associate at least one of project type or discipline metadata with the first comment; storing a first plurality of comments in association with respective metadata; providing for display a comments list in association with the first plan sheet, the comments list including a second plurality of comments; at least partly in response to the user selecting a second comment with a specified plan sheet coordinate in the comments lists, providing the second comment for display over the first plan sheet at the plan sheet coordinate and causing the portion of the first plan sheet corresponding to the specified plan sheet to be substantially centered in a sheet review display pane; enabling the user to search for comments by specifying, via a search user interface, project type or discipline metadata, generating and providing comments search results in response to a search query received via the search user interface; providing a user interface via which the user can select a plurality of comments to be included in a plan correction list; generating a correction list of items that need to be corrected in order for at least one approval document to be issued, the correction list including a plurality of comments specified by a plurality of users wherein the correction list includes: a category value, associated comments, and respective sheet identifiers for comments included in the correction list; transmitting the correction list to at least one user; tracking approval status of one or more building-related approval documents and providing the approval status to one or more users. 3. The system as defined in claim 1 , wherein the search user interface further includes fields via which the user can specify search filter conditions including a reviewer identifier, comment type, and submittal iteration and wherein the system utilizes the search filter conditions in generating comments search results.
| 0.574074 |
9,563,694 | 1 | 2 |
1. A specialized computer system, the system comprising: a) a specialized computer processor the specialized computer processor receiving search strings and user preferences dictating a display of search results, wherein the user preferences comprise specific instructions corresponding to at least one of font size, text color, and background of output information; b) a specialized non-transitory computer readable medium in communication with the specialized computer processor and the specialized non-transitory computer readable medium storing the search strings and the user preferences; c) a specialized server in communication with the specialized computer processor and in communication with a patent database, wherein the specialized server searches for patent documents within the patent database and wherein the specialized server retrieves patent documents and sends patent documents to the specialized computer processor, and wherein each patent document discloses a technology; d) upon receipt of patent documents the specialized computer processor creates search result documents and analyzes the search result documents to: identify identities of key individuals involved in developing the technology disclosed; perform at least one of: sorting the search result documents based on user defined criteria; and ranking of the search result documents based on the disclosed technology, the search result documents comprising cross reference and triangulation information pertaining to the search criteria, a textual description of each of the search result documents, the identities of the identified key individuals, and a statistical representation of one or more of the search result documents in a single view, in conformance with the user preferences stored within the specialized non-transitory computer readable medium, wherein the search result documents comprise a user selected search criteria selected from a group comprising financial data based upon an entity's portfolio of intellectual property, search result documents cross referenced to the entity, and user selected category of user selected criteria; and e) the search result documents are then transmitted to a consumer screen.
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1. A specialized computer system, the system comprising: a) a specialized computer processor the specialized computer processor receiving search strings and user preferences dictating a display of search results, wherein the user preferences comprise specific instructions corresponding to at least one of font size, text color, and background of output information; b) a specialized non-transitory computer readable medium in communication with the specialized computer processor and the specialized non-transitory computer readable medium storing the search strings and the user preferences; c) a specialized server in communication with the specialized computer processor and in communication with a patent database, wherein the specialized server searches for patent documents within the patent database and wherein the specialized server retrieves patent documents and sends patent documents to the specialized computer processor, and wherein each patent document discloses a technology; d) upon receipt of patent documents the specialized computer processor creates search result documents and analyzes the search result documents to: identify identities of key individuals involved in developing the technology disclosed; perform at least one of: sorting the search result documents based on user defined criteria; and ranking of the search result documents based on the disclosed technology, the search result documents comprising cross reference and triangulation information pertaining to the search criteria, a textual description of each of the search result documents, the identities of the identified key individuals, and a statistical representation of one or more of the search result documents in a single view, in conformance with the user preferences stored within the specialized non-transitory computer readable medium, wherein the search result documents comprise a user selected search criteria selected from a group comprising financial data based upon an entity's portfolio of intellectual property, search result documents cross referenced to the entity, and user selected category of user selected criteria; and e) the search result documents are then transmitted to a consumer screen. 2. The system of claim 1 wherein the specialized computer processor is configured to repeat past patent document searches based upon criteria stored within the specialized non-transitory computer readable medium and then transmit updated search result documents to the consumer screen.
| 0.5 |
8,671,099 | 13 | 15 |
13. A computer program product for clustering devices in an Internet of Things (‘IoT’), the computer program product disposed upon a computer readable storage medium, wherein the computer readable storage medium is not a signal, the computer program product comprising computer program instructions that, when executed, cause a computer to carry out the steps of: receiving, by a device clustering module, a characteristic set for a device, wherein the characteristic set specifies one or more device attributes and an attribute value for each device attribute; clustering, by the device clustering module, the device into an attribute level cluster based on the one or more device attributes specified in the characteristic set for the device; and clustering, by the device clustering module, the device into a value level cluster based on the attribute value for each device attribute, wherein the value level cluster is a subset of the attribute level cluster.
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13. A computer program product for clustering devices in an Internet of Things (‘IoT’), the computer program product disposed upon a computer readable storage medium, wherein the computer readable storage medium is not a signal, the computer program product comprising computer program instructions that, when executed, cause a computer to carry out the steps of: receiving, by a device clustering module, a characteristic set for a device, wherein the characteristic set specifies one or more device attributes and an attribute value for each device attribute; clustering, by the device clustering module, the device into an attribute level cluster based on the one or more device attributes specified in the characteristic set for the device; and clustering, by the device clustering module, the device into a value level cluster based on the attribute value for each device attribute, wherein the value level cluster is a subset of the attribute level cluster. 15. The computer program product of claim 13 wherein clustering the device into an attribute level cluster based on the one or more device attributes specified in the characteristic set for the device further comprises: calculating, by the device clustering module, a commonality index between the device and a cluster representative for each attribute level cluster, wherein the cluster representative specifies a union of all attributes of each device in the attribute level cluster; and assigning, by the device clustering module, the device to the attribute level cluster with the highest commonality index.
| 0.5 |
8,666,928 | 18 | 22 |
18. A computer-implemented method for facilitating addition to a knowledge base, the knowledge base comprising first knowledge represented in a structured, machine-readable format which encodes meaning and is distinct from natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities, the method comprising: providing at least one interface by which a first untrained, general internet user may enter information which is not in the structured, machine-readable format, at least some of the information being in a particular natural language, the at least one interface being operable to transmit the information to at least one remote computing device for generation of second knowledge represented in the machine-readable format for addition to the knowledge base, wherein generation of the second knowledge includes translating the input from the users to factual assertions compatible with the structured, machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input from the users, and wherein addition of the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base; and presenting responses to knowledge requests using one or more of the first knowledge, the second knowledge, or third knowledge not represented in the knowledge base, the third knowledge being inferred from one or more of the first knowledge or the second knowledge.
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18. A computer-implemented method for facilitating addition to a knowledge base, the knowledge base comprising first knowledge represented in a structured, machine-readable format which encodes meaning and is distinct from natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities, the method comprising: providing at least one interface by which a first untrained, general internet user may enter information which is not in the structured, machine-readable format, at least some of the information being in a particular natural language, the at least one interface being operable to transmit the information to at least one remote computing device for generation of second knowledge represented in the machine-readable format for addition to the knowledge base, wherein generation of the second knowledge includes translating the input from the users to factual assertions compatible with the structured, machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input from the users, and wherein addition of the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base; and presenting responses to knowledge requests using one or more of the first knowledge, the second knowledge, or third knowledge not represented in the knowledge base, the third knowledge being inferred from one or more of the first knowledge or the second knowledge. 22. The method of claim 18 wherein the responses to selected ones of the knowledge requests include search results comprising a plurality of natural language documents retrieved using a conventional search engine.
| 0.693966 |
9,142,217 | 19 | 26 |
19. A system for facilitating the exchange of streamed speech recognition and transcription among users, the system comprising: (a) at least one system transaction manager using a uniform system protocol, including at least one post processing manager, wherein transaction manager is i) adapted to receive a streamed speech information request from at least one user employing a first user legacy protocol and flag the information request as requiring post processing, and, ii) configured to route a requested response to a speech information request to one or more users employing a second user legacy protocol, the speech information request comprised of spoken text and commands, including spoken commands, wherein the requested response comprises a transcription of spoken text and the post processed information requested, and wherein the post processing manager is configured to i) receive structured transcription from a speech recognition and/or transcription engine, ii) operate upon the transcribed speech, including spoken commands in accordance with the speech information request, and, iii) rout the requested response to a post processing application, if designated in the speech information request; (b) at least one application service adapter configured to provide bi-directional communication between the first user legacy protocol and the uniform system protocol, and between the second user legacy protocol and the uniform system protocol, and capable of bi-directional communication with the system transaction manager; and, (c) at least one speech recognition and/or transcription engine communicating with the system transaction manager, wherein the speech recognition and/or transcription engine is configured to receive the flagged streamed speech information request containing spoken text and commands, including spoken commands, from the system transaction manager, to generate a transcription in response to the speech information request and to route the response comprised of transcribed spoken text and transcribed spoken commands to the post processing manager.
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19. A system for facilitating the exchange of streamed speech recognition and transcription among users, the system comprising: (a) at least one system transaction manager using a uniform system protocol, including at least one post processing manager, wherein transaction manager is i) adapted to receive a streamed speech information request from at least one user employing a first user legacy protocol and flag the information request as requiring post processing, and, ii) configured to route a requested response to a speech information request to one or more users employing a second user legacy protocol, the speech information request comprised of spoken text and commands, including spoken commands, wherein the requested response comprises a transcription of spoken text and the post processed information requested, and wherein the post processing manager is configured to i) receive structured transcription from a speech recognition and/or transcription engine, ii) operate upon the transcribed speech, including spoken commands in accordance with the speech information request, and, iii) rout the requested response to a post processing application, if designated in the speech information request; (b) at least one application service adapter configured to provide bi-directional communication between the first user legacy protocol and the uniform system protocol, and between the second user legacy protocol and the uniform system protocol, and capable of bi-directional communication with the system transaction manager; and, (c) at least one speech recognition and/or transcription engine communicating with the system transaction manager, wherein the speech recognition and/or transcription engine is configured to receive the flagged streamed speech information request containing spoken text and commands, including spoken commands, from the system transaction manager, to generate a transcription in response to the speech information request and to route the response comprised of transcribed spoken text and transcribed spoken commands to the post processing manager. 26. The system of claim 19 wherein the speech information request comprises previously transcribed formatted spoken text.
| 0.907066 |
7,653,604 | 1 | 9 |
1. An interaction system for enabling interaction with at least one of several information systems belonging to a single application domain, the at least one information system configured to execute a set of actions on a set of objects characterized by a set of attributes; wherein the interaction system comprises: at least one adapter module configured to access said actions, objects and attributes classifiable in action types, object types and attribute categories specific to each one of said at least one information system, and in action classes, object classes and attribute classes common to said several information systems of said application domain; at least one domain module for containing the object classes, attribute classes and action classes common to said several information systems of a single application domain, and phrase setups; each phrase setup having a structure comprising a selection of said object classes, attribute classes and action classes and being provided to be tailored to said at least one information system by applying in the phrase setup: a) the specific object types, action types and attribute categories of said at least one information system corresponding to, respectively, the object, action and attribute classes in said phrase setup, and b) object, action and attribute instantiations obtained from said at least one information system corresponding to, respectively, the object, action and attribute classes in said phrase setup, in order to define a grammar essentially consisting of a set of term elements comprising the object, attribute and action instantiations obtained from said at least one information system and a set of rules governing the use of these term elements in a set of valid user query phrases for interaction between the user and said at least one information system through said recognition and interaction systems; at least one generic module, connected to the at least one domain module and connectable to said at least one recognition system, for converting said sets of term elements and rules and/or a set of valid user query phrases generated using said sets of term elements and rules into a digital form suitable for being processed by the recognition system for the recognition of user queries and for converting a digital form of a used query, produced by said recognition system in response to said user query and suitable for being processed by a computer, into a phrase according to said grammar and/or into term elements and rules from said sets of term elements and rules; wherein the interaction system is connectable to said at least one information system and to a user interface comprising at least one recognition system, so as to enable the user to interact with the at least one information system by means of user queries processed by said at least one recognition system.
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1. An interaction system for enabling interaction with at least one of several information systems belonging to a single application domain, the at least one information system configured to execute a set of actions on a set of objects characterized by a set of attributes; wherein the interaction system comprises: at least one adapter module configured to access said actions, objects and attributes classifiable in action types, object types and attribute categories specific to each one of said at least one information system, and in action classes, object classes and attribute classes common to said several information systems of said application domain; at least one domain module for containing the object classes, attribute classes and action classes common to said several information systems of a single application domain, and phrase setups; each phrase setup having a structure comprising a selection of said object classes, attribute classes and action classes and being provided to be tailored to said at least one information system by applying in the phrase setup: a) the specific object types, action types and attribute categories of said at least one information system corresponding to, respectively, the object, action and attribute classes in said phrase setup, and b) object, action and attribute instantiations obtained from said at least one information system corresponding to, respectively, the object, action and attribute classes in said phrase setup, in order to define a grammar essentially consisting of a set of term elements comprising the object, attribute and action instantiations obtained from said at least one information system and a set of rules governing the use of these term elements in a set of valid user query phrases for interaction between the user and said at least one information system through said recognition and interaction systems; at least one generic module, connected to the at least one domain module and connectable to said at least one recognition system, for converting said sets of term elements and rules and/or a set of valid user query phrases generated using said sets of term elements and rules into a digital form suitable for being processed by the recognition system for the recognition of user queries and for converting a digital form of a used query, produced by said recognition system in response to said user query and suitable for being processed by a computer, into a phrase according to said grammar and/or into term elements and rules from said sets of term elements and rules; wherein the interaction system is connectable to said at least one information system and to a user interface comprising at least one recognition system, so as to enable the user to interact with the at least one information system by means of user queries processed by said at least one recognition system. 9. The interaction system according to claim 1 , wherein said interaction system is also connectable to at least one output generation module for transmitting to said at least one output generation module a digital form, suitable for being processed by said at least one output generation module, of an output of said at least one information system in the form of an output phrase also according to said grammar or of its component term elements and at least one rule from said grammar governing the use of said term elements in an output phrase.
| 0.5 |
8,271,939 | 1 | 7 |
1. A computer system comprising: a processor for executing instructions stored in a computer-readable medium on one or more devices providing an application development tool; wherein the application development tool comprises one or more modules configured to perform operations comprising: receiving an input modifying source code of an application, the source code providing one or more elements of the application when executed at runtime; determining that the input specifies a reference in the source code to data returned by an interaction with a data source at runtime; and responsive to determining that the input specifies the reference to the data returned by the interaction with the data source: querying the data source and receiving a returned data sample comprising one or more data parameters in response to the query, wherein the one or more data parameters are communicated between the application and the data source at runtime to access data associated with the one or more data parameters; characterizing the returned data sample, wherein characterizing the returned data sample comprises determining, from the returned data sample, a data structure definition for the returned data sample and a source code element for referring to the one or more data parameters; and providing output comprising a suggested type characterization for the data returned by the interaction, wherein the suggested type characterization comprises at least one of (i) one or more options for completing an incomplete reference in the source code to the one or more data parameters and (ii) a suggested syntax of a source code segment referencing the one or more data parameters.
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1. A computer system comprising: a processor for executing instructions stored in a computer-readable medium on one or more devices providing an application development tool; wherein the application development tool comprises one or more modules configured to perform operations comprising: receiving an input modifying source code of an application, the source code providing one or more elements of the application when executed at runtime; determining that the input specifies a reference in the source code to data returned by an interaction with a data source at runtime; and responsive to determining that the input specifies the reference to the data returned by the interaction with the data source: querying the data source and receiving a returned data sample comprising one or more data parameters in response to the query, wherein the one or more data parameters are communicated between the application and the data source at runtime to access data associated with the one or more data parameters; characterizing the returned data sample, wherein characterizing the returned data sample comprises determining, from the returned data sample, a data structure definition for the returned data sample and a source code element for referring to the one or more data parameters; and providing output comprising a suggested type characterization for the data returned by the interaction, wherein the suggested type characterization comprises at least one of (i) one or more options for completing an incomplete reference in the source code to the one or more data parameters and (ii) a suggested syntax of a source code segment referencing the one or more data parameters. 7. The computer system of claim 1 , wherein determining the source code element comprises applying one or more heuristics to data in the returned data sample to determine a data structure of the returned data sample.
| 0.782258 |
8,966,439 | 19 | 21 |
19. The system of claim 17 , wherein the one or more second modules are further configured to generate an output that is (i) mathematically related to the formula and (ii) separate from the answer.
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19. The system of claim 17 , wherein the one or more second modules are further configured to generate an output that is (i) mathematically related to the formula and (ii) separate from the answer. 21. The system of claim 19 , wherein the one or more second modules are further configured to analyze the user input in the imprecise syntax to determine a correspondence between (i) the one or more parameter values in the user input in the imprecise syntax and (ii) one or more parameters of the formula.
| 0.515873 |
8,886,518 | 1 | 3 |
1. A method for capitalizing translated text comprising: executing a translator module stored on a device to automatically translate a capitalized source text to a target text, wherein prior to translation the capitalized source text is converted to lower case and then translated; and capitalizing the target text according to capitalization information in the capitalized source text and the target text, wherein the step of capitalizing the target text according to capitalization information in the capitalized source text includes: generating one or more capitalization configurations for the target text; computing a configuration probability for each of the one or more capitalization configurations, the configuration probability computed from capitalization information in the capitalized source text and at least one capitalization model feature function based on an alignment between the capitalized source text and the target text or the capitalized source text and the capitalization configuration; and selecting the best capitalization configuration based on the highest configuration probability.
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1. A method for capitalizing translated text comprising: executing a translator module stored on a device to automatically translate a capitalized source text to a target text, wherein prior to translation the capitalized source text is converted to lower case and then translated; and capitalizing the target text according to capitalization information in the capitalized source text and the target text, wherein the step of capitalizing the target text according to capitalization information in the capitalized source text includes: generating one or more capitalization configurations for the target text; computing a configuration probability for each of the one or more capitalization configurations, the configuration probability computed from capitalization information in the capitalized source text and at least one capitalization model feature function based on an alignment between the capitalized source text and the target text or the capitalized source text and the capitalization configuration; and selecting the best capitalization configuration based on the highest configuration probability. 3. The method of claim 1 further comprising capitalizing the target text using conditional random fields.
| 0.827303 |
8,738,403 | 41 | 42 |
41. The at least one computer-readable storage medium of claim 39 , wherein the updating further comprises adding the generated text to a location, in the textual representation of the free-form narration, specified by the user.
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41. The at least one computer-readable storage medium of claim 39 , wherein the updating further comprises adding the generated text to a location, in the textual representation of the free-form narration, specified by the user. 42. The at least one computer-readable storage medium of claim 41 , wherein the updating further comprises adjusting the generated text in accordance with the location specified by the user.
| 0.5 |
10,127,913 | 35 | 67 |
35. A method of encoding of syntactic elements of a data stream, wherein: before beginning of encoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of the cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of encoding of at least a portion of bits of the data stream: a group of context models is selected that comprises at least two context models of different size; values of at least two context elements associated the selected group of context models are calculated; selection of the cells in context models is carried out using values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, which data is used for entropy encoding of a current bit of the data stream, and/or for selecting a mode of writing encoded bits into the data stream directly; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met.
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35. A method of encoding of syntactic elements of a data stream, wherein: before beginning of encoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of the cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of encoding of at least a portion of bits of the data stream: a group of context models is selected that comprises at least two context models of different size; values of at least two context elements associated the selected group of context models are calculated; selection of the cells in context models is carried out using values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, which data is used for entropy encoding of a current bit of the data stream, and/or for selecting a mode of writing encoded bits into the data stream directly; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met. 67. An encoder for encoding of syntactic elements of a data stream for carrying out the method of encoding of the syntactic elements of the data stream according to claim 35 , comprising: an entropy coder, an input data buffer, a binarized data buffer, a context model group selector, a context model group repository, a context model group processor, context element formers, a model update module, and a context mixing module.
| 0.54661 |
7,805,452 | 7 | 8 |
7. A data processing apparatus according to claim 2 , further comprising: means for allowing the user to input an instruction to add new data to the data thus integrated and presented by said presenting means, and an instruction to remove a part of the data; and means for adding or removing the information, which is stored in the first data file and which serves as a key, according to the instruction thus input.
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7. A data processing apparatus according to claim 2 , further comprising: means for allowing the user to input an instruction to add new data to the data thus integrated and presented by said presenting means, and an instruction to remove a part of the data; and means for adding or removing the information, which is stored in the first data file and which serves as a key, according to the instruction thus input. 8. A data processing apparatus according to claim 7 , further comprising: means for allowing the user to input an instruction to edit the data thus integrated and presented by said presenting means; and means for modifying the second data file that stores the data, according to the editing instruction.
| 0.5 |
9,920,855 | 1 | 6 |
1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly.
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1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly. 6. The system of claim 1 , wherein the second architecture layer is configured to calculate a value for a performance indicator from the data and to communicate the value to the network in the second format.
| 0.751202 |
8,266,068 | 1 | 3 |
1. A method to interview a candidate, comprising: providing a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtaining a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjusting the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collecting, using the processor, a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyzing the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively presenting the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information.
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1. A method to interview a candidate, comprising: providing a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtaining a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjusting the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collecting, using the processor, a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyzing the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively presenting the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. 3. The method of claim 1 , wherein at least one selected from a group consisting of the interview plan and the candidate screening criteria is custom defined based on the target requirement.
| 0.890173 |
8,954,539 | 9 | 11 |
9. The system of claim 8 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected.
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9. The system of claim 8 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected. 11. The system of claim 9 , wherein the behavioral information is stored in a cookie.
| 0.522472 |
7,996,375 | 23 | 26 |
23. A method for delivery of content from a corpus of data, the method implemented by a computer system including a search engine, a result processor, an interface, and a memory, the method comprising: receiving a search query for searching the corpus; generating a result set in response to the search query, the search query result set including one or more items from the corpus; identifying a characteristic corresponding to a plurality of items in the search query result set; identifying a rule corresponding to said characteristic, said rule defining a content presentation action; determining a percentage of items in the search query result set that correspond to said characteristic; comparing the determined percentage of items to a threshold percentage, wherein the threshold percentage is a predetermined percentage of the total number of items in the search query result set; and presenting content in accordance with the content specification action when the determined percentage of items exceeds the threshold percentage.
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23. A method for delivery of content from a corpus of data, the method implemented by a computer system including a search engine, a result processor, an interface, and a memory, the method comprising: receiving a search query for searching the corpus; generating a result set in response to the search query, the search query result set including one or more items from the corpus; identifying a characteristic corresponding to a plurality of items in the search query result set; identifying a rule corresponding to said characteristic, said rule defining a content presentation action; determining a percentage of items in the search query result set that correspond to said characteristic; comparing the determined percentage of items to a threshold percentage, wherein the threshold percentage is a predetermined percentage of the total number of items in the search query result set; and presenting content in accordance with the content specification action when the determined percentage of items exceeds the threshold percentage. 26. The method of claim 23 , wherein presenting content in accordance with the content specification action comprises adding items to the search query result set that do not satisfy the search query.
| 0.509852 |
5,517,637 | 8 | 16 |
8. A method for testing an integrated circuit, the method comprising the steps of: a) receiving integrated circuit topology information of the integrated circuit, wherein the integrated circuit has a test architecture which allows the integrated circuit to participate in system-level testing operations, the integrated circuit topology information including test architecture topology information, the integrated circuit topology information being stored as a circuit netlist via computer-readable media; b) obtaining a boundary scan description of the test architecture of the integrated circuit wherein the boundary scan description defines various physical features of the test architecture and is stored via computer readable media; c) generating, based on the boundary scan description, test parameters for use by a logic simulation, wherein the logic simulation is used to test the integrated circuit; d) exercising the integrated circuit via the logic simulation and the monitoring the excerising of the integrated circuit for any occurrence of an error the error being detected based on at least a portion of the test parameters; and e) obtaining an error correction for the error in response to the error being detected.
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8. A method for testing an integrated circuit, the method comprising the steps of: a) receiving integrated circuit topology information of the integrated circuit, wherein the integrated circuit has a test architecture which allows the integrated circuit to participate in system-level testing operations, the integrated circuit topology information including test architecture topology information, the integrated circuit topology information being stored as a circuit netlist via computer-readable media; b) obtaining a boundary scan description of the test architecture of the integrated circuit wherein the boundary scan description defines various physical features of the test architecture and is stored via computer readable media; c) generating, based on the boundary scan description, test parameters for use by a logic simulation, wherein the logic simulation is used to test the integrated circuit; d) exercising the integrated circuit via the logic simulation and the monitoring the excerising of the integrated circuit for any occurrence of an error the error being detected based on at least a portion of the test parameters; and e) obtaining an error correction for the error in response to the error being detected. 16. The method of claim 8, wherein the step of obtaining the boundary scan description further comprises obtaining the boundary scan description from an external source.
| 0.573232 |
9,904,522 | 1 | 4 |
1. A development method for a web application system, comprising: in a running state of the web application system, performing the following steps at a server of the web application system: providing a developer interface to a remote client developer device for the web application system; generating or modifying a script code used to perform a predetermined function; parsing, by a script parser, the generated script code or the modified script code to correspondingly generate an object type which performs a new function, or to modify an object type which performs an existing function; generating a new function object or modifying an existing function object, by an object manager, according to the generated object type which performs the new function or the modified object type which performs the existing function; assigning a unique identifier to each generated or modified object type; organizing, by the object manager invoking relationships between the new function object and other objects, or invoking relationships between the modified function object and other objects by setting the invoking relationships using the assigned unique identifiers; and allowing the web application system to perform the predetermined function based on the generated new function object or the modified existing function object while remaining in the running state.
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1. A development method for a web application system, comprising: in a running state of the web application system, performing the following steps at a server of the web application system: providing a developer interface to a remote client developer device for the web application system; generating or modifying a script code used to perform a predetermined function; parsing, by a script parser, the generated script code or the modified script code to correspondingly generate an object type which performs a new function, or to modify an object type which performs an existing function; generating a new function object or modifying an existing function object, by an object manager, according to the generated object type which performs the new function or the modified object type which performs the existing function; assigning a unique identifier to each generated or modified object type; organizing, by the object manager invoking relationships between the new function object and other objects, or invoking relationships between the modified function object and other objects by setting the invoking relationships using the assigned unique identifiers; and allowing the web application system to perform the predetermined function based on the generated new function object or the modified existing function object while remaining in the running state. 4. The development method for the web application system according to claim 1 , wherein the step of generating or modifying the script code used to perform a predetermined function comprises: receiving a presentation effect of the function in a visual manner, wherein the script code is modified or generated corresponding to the received presentation effect of the function.
| 0.636628 |
9,104,700 | 1 | 6 |
1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request.
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1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request. 6. The computer-implemented method of claim 1 , wherein the one or more words correspond to at least one of (i) a name of a product, (ii) a brand name of the product, (iii) a model name of the product, (iv) a model number of the product, or (v) a product code of the product.
| 0.5 |
10,025,848 | 5 | 7 |
5. The communication device of claim 1 , wherein the operations further comprise: receiving an indication for including an audio file of the voicemail message with the portion of the information; and transmitting the indication for including the audio file to the server for delivery of the audio file to the intended recipient with the portion of the information.
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5. The communication device of claim 1 , wherein the operations further comprise: receiving an indication for including an audio file of the voicemail message with the portion of the information; and transmitting the indication for including the audio file to the server for delivery of the audio file to the intended recipient with the portion of the information. 7. The communication device of claim 5 , wherein the audio file is delivered to the intended recipient in a .WAV format, an mpx format, a REAL Audio format, or any combination thereof.
| 0.5 |
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