patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
8,788,488 | 1 | 8 | 1. A method, comprising: determining, by at least one processor, an expected popularity of a file based on popularity information; assigning a popularity score to the file based on the expected popularity; adjusting, by the at least one processor, the assigned popularity score based on a time decay component such that greater weight is given to more recent popularity information of the popularity information than to less recent popularity information of the popularity information; and ordering the file relative to a plurality of other files based on the time-decay adjusted assigned popularity-score. | 1. A method, comprising: determining, by at least one processor, an expected popularity of a file based on popularity information; assigning a popularity score to the file based on the expected popularity; adjusting, by the at least one processor, the assigned popularity score based on a time decay component such that greater weight is given to more recent popularity information of the popularity information than to less recent popularity information of the popularity information; and ordering the file relative to a plurality of other files based on the time-decay adjusted assigned popularity-score. 8. The method as recited in claim 1 , further comprising enabling display of an indication of the file as ordered relative to the plurality of other files. | 0.698444 |
7,542,971 | 26 | 31 | 26. The system of claim 21 , wherein the context information is at least one of support information and collaborative user feedback information. | 26. The system of claim 21 , wherein the context information is at least one of support information and collaborative user feedback information. 31. The system of claim 26 , wherein the presentation information source is based on at least one of: audio, visual, tactile information. | 0.709746 |
8,312,042 | 14 | 17 | 14. A computer-implemented method comprising: determining, by one or more servers, whether a textual representation of a first spoken phrase includes one or more keywords that are associated with automatic dialing; in response to determining that the textual representation of the first spoken phrase does not include the one or more keywords, submitting, by the one or more servers, the textual representation of the first spoken phrase to a first search engine; determining, by the one or more servers, whether a textual representation of a second spoken phrase includes the one or more keywords that are associated with automatic dialing; in response to determining that the textual representation of the second spoken phrase includes the one or more keywords, submitting, by the one or more servers, the textual representation of the second spoken phrase to a second search engine, the second search engine being a geographic search engine; receiving, by the one or more servers, one or more responsive search results from the geographic search engine; selecting, by the one or more servers, contact information associated with a particular search result of the one or more responsive search results; and providing, by the one or more servers and for receipt by a mobile device, an instruction to automatically initiate communication using the selected contact information. | 14. A computer-implemented method comprising: determining, by one or more servers, whether a textual representation of a first spoken phrase includes one or more keywords that are associated with automatic dialing; in response to determining that the textual representation of the first spoken phrase does not include the one or more keywords, submitting, by the one or more servers, the textual representation of the first spoken phrase to a first search engine; determining, by the one or more servers, whether a textual representation of a second spoken phrase includes the one or more keywords that are associated with automatic dialing; in response to determining that the textual representation of the second spoken phrase includes the one or more keywords, submitting, by the one or more servers, the textual representation of the second spoken phrase to a second search engine, the second search engine being a geographic search engine; receiving, by the one or more servers, one or more responsive search results from the geographic search engine; selecting, by the one or more servers, contact information associated with a particular search result of the one or more responsive search results; and providing, by the one or more servers and for receipt by a mobile device, an instruction to automatically initiate communication using the selected contact information. 17. The method of claim 14 , wherein the contact information comprises a Uniform Resource Identifier (URI), and the instruction instructs the mobile device to automatically direct a web browser to a web site associated with the URI. | 0.745614 |
9,711,147 | 1 | 11 | 1. A computerized method for analyzing verbal records to improve a textual transcript, the method comprising the steps of: selecting a plurality of verbal records from a database, wherein each verbal record in the plurality of verbal records comprises a combination of: at least one identifier; at least one text feature comprising at least one first feature selected from the group consisting of a word, or word stem, or a combination thereof; and, at least one phonetic feature comprising at least one first feature selected from the group consisting of a number of syllables, a syllable duration pause, duration and pitch value, or a combination thereof; identifying a subset of the plurality of verbal records from the database; extracting the at least one phonetic feature, the at least one text feature, or a combination thereof, from the subset of the plurality of verbal records; analyzing the at least one phonetic feature, the at least one text feature, or a combination thereof, of the subset of the plurality of verbal records; processing the subset of the plurality of records using the analyzed feature according to at least one reasoning approach; further processing the subset of the plurality of records using the at least one phonetic feature, the at least one text feature, or a combination thereof, to determine a position of a punctuation feature in each verbal record in the subset of the plurality of verbal records and introduce the punctuation feature at the position, the punctuation feature being a comma; generating a processed verbal record using the processed subset of the plurality of verbal records; modifying the identified subset of the plurality of verbal records with the system to create a modified verbal record, wherein the system uses the at least one analyzed phonetic feature, the at least one text feature, and the at least one reasoning approach, or a combination thereof, to generate the modified verbal record; and delivering modified verbal record to the recipient. | 1. A computerized method for analyzing verbal records to improve a textual transcript, the method comprising the steps of: selecting a plurality of verbal records from a database, wherein each verbal record in the plurality of verbal records comprises a combination of: at least one identifier; at least one text feature comprising at least one first feature selected from the group consisting of a word, or word stem, or a combination thereof; and, at least one phonetic feature comprising at least one first feature selected from the group consisting of a number of syllables, a syllable duration pause, duration and pitch value, or a combination thereof; identifying a subset of the plurality of verbal records from the database; extracting the at least one phonetic feature, the at least one text feature, or a combination thereof, from the subset of the plurality of verbal records; analyzing the at least one phonetic feature, the at least one text feature, or a combination thereof, of the subset of the plurality of verbal records; processing the subset of the plurality of records using the analyzed feature according to at least one reasoning approach; further processing the subset of the plurality of records using the at least one phonetic feature, the at least one text feature, or a combination thereof, to determine a position of a punctuation feature in each verbal record in the subset of the plurality of verbal records and introduce the punctuation feature at the position, the punctuation feature being a comma; generating a processed verbal record using the processed subset of the plurality of verbal records; modifying the identified subset of the plurality of verbal records with the system to create a modified verbal record, wherein the system uses the at least one analyzed phonetic feature, the at least one text feature, and the at least one reasoning approach, or a combination thereof, to generate the modified verbal record; and delivering modified verbal record to the recipient. 11. The method of claim 1 , further comprising the step of processing the subset of the plurality of records using the at least one first feature to determine a second position of a second punctuation feature in each verbal record in the subset of the plurality of verbal records and introduce the second punctuation feature at the second position, the second punctuation feature being a heading. | 0.584034 |
8,843,427 | 1 | 8 | 1. A computer-implemented method, the method comprising: receiving a training data set that comprises a plurality of examples, wherein each example comprises one or more features and an answer; generating a plurality of modified training data sets, wherein generating each of the modified training data sets comprises applying a respective filter or combination of filters to examples in the training data set to generate the examples of the modified training data set, the filter or combination of filters altering one or more of the examples; training a plurality of predictive models, including training each of one or more predictive models using a different respective modified training data set of the plurality of modified training data sets; determining a respective accuracy for each of the plurality of predictive models; identifying a most accurate predictive model based on the determined respective accuracies; and specifying an association between the training data set and the filter or combination of filters used to generate the modified training data set that was used to train the most accurate predictive model. | 1. A computer-implemented method, the method comprising: receiving a training data set that comprises a plurality of examples, wherein each example comprises one or more features and an answer; generating a plurality of modified training data sets, wherein generating each of the modified training data sets comprises applying a respective filter or combination of filters to examples in the training data set to generate the examples of the modified training data set, the filter or combination of filters altering one or more of the examples; training a plurality of predictive models, including training each of one or more predictive models using a different respective modified training data set of the plurality of modified training data sets; determining a respective accuracy for each of the plurality of predictive models; identifying a most accurate predictive model based on the determined respective accuracies; and specifying an association between the training data set and the filter or combination of filters used to generate the modified training data set that was used to train the most accurate predictive model. 8. The computer-implemented method of claim 1 , wherein: the training data set comprises text-based data; and the filter or combination of filters comprises one or more of an n-gram filter, a stop word filter, a punctuation filter, and a stemming filter. | 0.616314 |
7,945,579 | 13 | 14 | 13. The computer-readable memory device of claim 12 , where the database includes a specialized database of documents selected for classifying the terms identified as the potential stopword. | 13. The computer-readable memory device of claim 12 , where the database includes a specialized database of documents selected for classifying the terms identified as the potential stopword. 14. The computer-readable memory device of claim 13 , where the specialized database of documents includes documents selected as being representative of a concept in which the words in the documents are related to the concept. | 0.5 |
8,458,155 | 1 | 7 | 1. A records management system, comprising: a location designation module configured to designate an electronic storage location for each representation of a page of a document; a data module configured to create an electronic data file that corresponds to the each representation of a page, wherein the electronic data file relates the each representation of the page to the document within a project, and wherein the electronic data file includes the electronic storage location for the each representation of a page; a server configured to receive input of additional data for the electronic data file, the additional data including a category for the each representation of a page and a date for the each representation of a page; a supplementation module configured to supplement the electronic data file with the additional data for the electronic data file; a merging module configured to merge the each representation of a page with a corresponding electronic data file for the each said representation of a page such that the each representation of a page and the corresponding electronic data file are accessible from a single electronic project file; and a summary excerpt of at least one each representation of a page. | 1. A records management system, comprising: a location designation module configured to designate an electronic storage location for each representation of a page of a document; a data module configured to create an electronic data file that corresponds to the each representation of a page, wherein the electronic data file relates the each representation of the page to the document within a project, and wherein the electronic data file includes the electronic storage location for the each representation of a page; a server configured to receive input of additional data for the electronic data file, the additional data including a category for the each representation of a page and a date for the each representation of a page; a supplementation module configured to supplement the electronic data file with the additional data for the electronic data file; a merging module configured to merge the each representation of a page with a corresponding electronic data file for the each said representation of a page such that the each representation of a page and the corresponding electronic data file are accessible from a single electronic project file; and a summary excerpt of at least one each representation of a page. 7. The system of claim 1 , wherein the summary excerpt of at least one each representation of a page includes a page number associated with the at least one each representation of a page. | 0.740997 |
8,166,074 | 1 | 2 | 1. A digital storage medium having an index data structure for one or more data objects encoded thereon, the index data structure comprising: a) a plurality of index keys for uniquely identifying potential context nodes in a data object, each index key being associated with one or more potential context nodes, the index key having a label that provides semantic content to a user; and b) one or more routing tables associated with each index key, the one or more routing tables comprising at least 5 path references selected from a preceding peer-to-peer graph, a following peer-to-peer graph, an ancestor peer-to-peer graph, and descendent peer-to-peer graph. | 1. A digital storage medium having an index data structure for one or more data objects encoded thereon, the index data structure comprising: a) a plurality of index keys for uniquely identifying potential context nodes in a data object, each index key being associated with one or more potential context nodes, the index key having a label that provides semantic content to a user; and b) one or more routing tables associated with each index key, the one or more routing tables comprising at least 5 path references selected from a preceding peer-to-peer graph, a following peer-to-peer graph, an ancestor peer-to-peer graph, and descendent peer-to-peer graph. 2. The digital storage medium of claim 1 wherein the semantic content is a path to the node associated with the index key. | 0.886194 |
7,640,162 | 1 | 9 | 1. A system for synchronizing a natural language input element and a graphical user interface element, the system comprising: the natural language input element, wherein the natural language input element displays, via a display device, an indication of a user natural language input on a user interface, wherein the displayed indication of the user natural language input is a representation of words included within an initial natural language input received from a user, and wherein the displayed indication of the user natural language input is displayed in an editable format that allows the user to modify the representation of words included within the initial natural language input by adding words to or removing words from the representation of words included within the initial natural language input; the graphical user interface element, wherein the graphical user interface element displays, via a display device, on the user interface simultaneously with the display of the indication of the user natural language input, an indication of a user graphical interface input, wherein the displayed indication of the user graphical interface input is an automatically generated control box representation of the initial natural language input received from the user, the displayed indication of the user graphical interface input and the displayed indication of the user natural language input being two different representations of the same initial natural language input received from the user, and wherein the displayed indication of the user graphical interface input is an editable format that allows the user to modify the automatically generated control box representation of words included within the initial natural language input; a synchronization engine that monitors, via a processor, user interactions with the natural language input element and the graphical user interface element and automatically synchronizes the natural language input element and the graphical user interface element responsive to the user interactions, wherein the synchronization engine automatically synchronizes the natural language input element and the graphical user interface element responsive to the user interactions by automatically changing the displayed indication of the user graphical interface input so as to automatically modify the automatically generated control box representation so as to alter the automatically generated control box representation to incorporate revised logic that is consistent with an edit made to the representation of words included within the initial natural language input, the edit being a word added to or removed from the representation of words included within the initial natural language input; and a restatement engine that monitors user interactions with the graphical user interface element and utilizes a computer processor that is a component of a computing device to automatically compose a natural language input representative of a modification to the automatically generated control box representation of the initial natural language input received from the user, wherein the modification alters the logic of the displayed representation, and wherein the synchronization engine updates the natural language element so as to automatically respond to the modification to the automatically generated representation by automatically substituting a display of the automatically composed natural language input for the displayed representation of words included within the initial natural language input received from the user, wherein the automatically composed natural language input is an automatically generated re-statement of the displayed representation of words included within the initial natural language input received from the user with modifications being automatically made to the displayed representation of words based directly on the modification to the displayed representation. | 1. A system for synchronizing a natural language input element and a graphical user interface element, the system comprising: the natural language input element, wherein the natural language input element displays, via a display device, an indication of a user natural language input on a user interface, wherein the displayed indication of the user natural language input is a representation of words included within an initial natural language input received from a user, and wherein the displayed indication of the user natural language input is displayed in an editable format that allows the user to modify the representation of words included within the initial natural language input by adding words to or removing words from the representation of words included within the initial natural language input; the graphical user interface element, wherein the graphical user interface element displays, via a display device, on the user interface simultaneously with the display of the indication of the user natural language input, an indication of a user graphical interface input, wherein the displayed indication of the user graphical interface input is an automatically generated control box representation of the initial natural language input received from the user, the displayed indication of the user graphical interface input and the displayed indication of the user natural language input being two different representations of the same initial natural language input received from the user, and wherein the displayed indication of the user graphical interface input is an editable format that allows the user to modify the automatically generated control box representation of words included within the initial natural language input; a synchronization engine that monitors, via a processor, user interactions with the natural language input element and the graphical user interface element and automatically synchronizes the natural language input element and the graphical user interface element responsive to the user interactions, wherein the synchronization engine automatically synchronizes the natural language input element and the graphical user interface element responsive to the user interactions by automatically changing the displayed indication of the user graphical interface input so as to automatically modify the automatically generated control box representation so as to alter the automatically generated control box representation to incorporate revised logic that is consistent with an edit made to the representation of words included within the initial natural language input, the edit being a word added to or removed from the representation of words included within the initial natural language input; and a restatement engine that monitors user interactions with the graphical user interface element and utilizes a computer processor that is a component of a computing device to automatically compose a natural language input representative of a modification to the automatically generated control box representation of the initial natural language input received from the user, wherein the modification alters the logic of the displayed representation, and wherein the synchronization engine updates the natural language element so as to automatically respond to the modification to the automatically generated representation by automatically substituting a display of the automatically composed natural language input for the displayed representation of words included within the initial natural language input received from the user, wherein the automatically composed natural language input is an automatically generated re-statement of the displayed representation of words included within the initial natural language input received from the user with modifications being automatically made to the displayed representation of words based directly on the modification to the displayed representation. 9. The system of claim 1 , wherein the displayed indication of the user graphical interface input is an automatically generated control box representation that includes a series of text and check boxes that each contain an entry such that, collectively, the text and check boxes represent multiple elements of the initial natural language input received from the user. | 0.632735 |
7,720,599 | 4 | 7 | 4. A tourist information guiding apparatus according to claim 2 , further comprising: a type information storage device for storing type information specifying the types of the tourist spots in correspondence with the image data relating to the tourist spots; a type receiver provided in the apparatus main body for receiving the selection of the type of the tourist spots; and a searcher for searching the image data of the tourist spots corresponding to the tourist spot type selected by the type receiver from contents of storage of the tourist spot information storage device; wherein the display controller causes the monitor to display a list of images relating to the tourist spots searched by the searcher together with the character strings for sightseeing guide written in the language designated by the language receiver. | 4. A tourist information guiding apparatus according to claim 2 , further comprising: a type information storage device for storing type information specifying the types of the tourist spots in correspondence with the image data relating to the tourist spots; a type receiver provided in the apparatus main body for receiving the selection of the type of the tourist spots; and a searcher for searching the image data of the tourist spots corresponding to the tourist spot type selected by the type receiver from contents of storage of the tourist spot information storage device; wherein the display controller causes the monitor to display a list of images relating to the tourist spots searched by the searcher together with the character strings for sightseeing guide written in the language designated by the language receiver. 7. A tourist information guiding apparatus according to claim 4 , wherein the tourist spot information storage device stores a character string data of a message for designating the tourist spot as a destination for each tourist spot, and the print controller causes the character string data of the message to be included in the print data. | 0.614253 |
9,519,463 | 7 | 8 | 7. The method of claim 1 , further comprising storing the parsed data, prior to interpreting the parsed data to enable generation of the flowchart, according to a scheme such that similar keywords, constructs and API usage all flow the same way regardless of the programming language of the test program and/or the test station for which the test program is written. | 7. The method of claim 1 , further comprising storing the parsed data, prior to interpreting the parsed data to enable generation of the flowchart, according to a scheme such that similar keywords, constructs and API usage all flow the same way regardless of the programming language of the test program and/or the test station for which the test program is written. 8. The method of claim 7 , further comprising storing the parsed data in a data structure prior to interpreting the parsed data to enable generation of the flowchart, wherein the data structure in which the parsed data is stored is a memory resident data structure and the scheme in which the parsed data is stored in an XML object or a database object with a predefined structure. | 0.5 |
8,620,659 | 33 | 36 | 33. The method of claim 23 , further comprising: determining a most likely context for the natural language utterances; comparing one or more text combinations against one or more grammar expression entries in a context description grammar to identify one or more contexts that completely or partially match the one or more text combinations; providing a relevance score for each of identified matching contexts; selecting the matching context having a highest score as the most likely context for the natural language utterance, wherein the domain agent is associated with the selected context; communicating the request to the domain agent associated with the selected context; and generating the response to the request using content gathered as a result of the domain agent processing the request, wherein the response arranges the content in an order based on the relevance scores for the identified matching contexts. | 33. The method of claim 23 , further comprising: determining a most likely context for the natural language utterances; comparing one or more text combinations against one or more grammar expression entries in a context description grammar to identify one or more contexts that completely or partially match the one or more text combinations; providing a relevance score for each of identified matching contexts; selecting the matching context having a highest score as the most likely context for the natural language utterance, wherein the domain agent is associated with the selected context; communicating the request to the domain agent associated with the selected context; and generating the response to the request using content gathered as a result of the domain agent processing the request, wherein the response arranges the content in an order based on the relevance scores for the identified matching contexts. 36. The method of claim 33 , further comprising: comparing the text combinations against a context stack that stores one or more expected contexts to identify the one or more contexts. | 0.674912 |
9,058,588 | 11 | 14 | 11. A computer-implemented method for managing a context-sensitive sidebar window, comprising: determining contextual information relevant to an electronic document displayed on an electronic desktop; presenting a portion of the determined contextual information in a sidebar window; and managing a display of the context-sensitive sidebar window within the electronic desktop adjacent to the electronic document, comprising: determining a location of one or more icons on the electronic desktop and assigning a relative importance to each of the one or more icons; assigning an importance value to each pixel of the icons in the electronic desktop; adjusting at least one of a vertical and horizontal positioning of the context-sensitive sidebar within the electronic desktop based on the importance of the icons and the importance of the icon pixels within the electronic desktop such that coverage of the pixels of the icons, associated with a higher importance, by the context-sensitive sidebar is minimized; automatically opening the context-sensitive sidebar window when the electronic document is opened; and automatically closing the context-sensitive sidebar window when the document is closed. | 11. A computer-implemented method for managing a context-sensitive sidebar window, comprising: determining contextual information relevant to an electronic document displayed on an electronic desktop; presenting a portion of the determined contextual information in a sidebar window; and managing a display of the context-sensitive sidebar window within the electronic desktop adjacent to the electronic document, comprising: determining a location of one or more icons on the electronic desktop and assigning a relative importance to each of the one or more icons; assigning an importance value to each pixel of the icons in the electronic desktop; adjusting at least one of a vertical and horizontal positioning of the context-sensitive sidebar within the electronic desktop based on the importance of the icons and the importance of the icon pixels within the electronic desktop such that coverage of the pixels of the icons, associated with a higher importance, by the context-sensitive sidebar is minimized; automatically opening the context-sensitive sidebar window when the electronic document is opened; and automatically closing the context-sensitive sidebar window when the document is closed. 14. A method according to claim 11 , further comprising: presenting the context-sensitive sidebar window as a toolbar. | 0.856796 |
8,504,408 | 4 | 5 | 4. The method of claim 3 , wherein the one or more metrics comprises: recency, frequency and monetary value of transactions made by the customer, value representing one or more campaign management and performance related details, value representing attrition, customer lifetime value, value representing product related details, and value representing service related details offered by the enterprise. | 4. The method of claim 3 , wherein the one or more metrics comprises: recency, frequency and monetary value of transactions made by the customer, value representing one or more campaign management and performance related details, value representing attrition, customer lifetime value, value representing product related details, and value representing service related details offered by the enterprise. 5. The method of claim 4 , wherein the one or more scores comprise recency frequency and monetary score, campaign response score, attrition score, cross-sell products, customer lifetime value, service level agreement score. | 0.5 |
9,165,055 | 17 | 20 | 17. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; linking the content with the at least one term; and wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. | 17. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; linking the content with the at least one term; and wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. 20. The method of claim 17 , wherein the at least one term is visibly enhanced to notify the user of available content. | 0.580986 |
5,455,901 | 19 | 20 | 19. The method of claim 15 wherein said step of generating said translated form of said respective block of said data comprises the step of generating machine readable characters from said strokes. | 19. The method of claim 15 wherein said step of generating said translated form of said respective block of said data comprises the step of generating machine readable characters from said strokes. 20. The method of claim 19 wherein said machine readable characters comprise Unicode characters. | 0.5 |
7,822,626 | 12 | 13 | 12. A computer-implemented method operating on a computer system for automated conversion of a clinical content structure, the computer-implemented method comprising: providing a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; displaying, at the first authoring environment and the second authoring environment, a default clinical content structure receiving, at the server, first modification data from one or more users of the first authoring environment and second modification data from one or more users of the second authoring environment; modifying, at the server, the default clinical content structure based on the first modification data and second modification data to create a modified clinical content structure; storing, at the server, a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; storing, at the server, a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; automatically translating, at the server, the modified clinical content structure into a first standard structure using the first plurality of data translation rules; automatically translating, at the server, the modified clinical content structure into a second standard structure using the second plurality of data translation rules; converting, at the server, the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; converting, at the server, the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and transmitting, from the server, the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers. | 12. A computer-implemented method operating on a computer system for automated conversion of a clinical content structure, the computer-implemented method comprising: providing a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; displaying, at the first authoring environment and the second authoring environment, a default clinical content structure receiving, at the server, first modification data from one or more users of the first authoring environment and second modification data from one or more users of the second authoring environment; modifying, at the server, the default clinical content structure based on the first modification data and second modification data to create a modified clinical content structure; storing, at the server, a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; storing, at the server, a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; automatically translating, at the server, the modified clinical content structure into a first standard structure using the first plurality of data translation rules; automatically translating, at the server, the modified clinical content structure into a second standard structure using the second plurality of data translation rules; converting, at the server, the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; converting, at the server, the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and transmitting, from the server, the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers. 13. The computer-implemented method of claim 12 wherein the computer-implemented method is performed by a web-based system. | 0.5 |
4,028,538 | 13 | 14 | 13. An electronic calculator as in claim 11 wherein: said editing keys include a forward control key and a backward control key for initiating single stepping either forward or backward through a line of one or more alphameric statements entered into said buffer storage means from said keyboard input means or recalled from said memory means; and said processing means is responsive to actuation of either of said forward and backward control keys for enabling said alphameric output display means to visually display part or all of the entered or recalled line of one or more alphameric statements up to and including as the last displayed character the last character to which that line has been single stepped. | 13. An electronic calculator as in claim 11 wherein: said editing keys include a forward control key and a backward control key for initiating single stepping either forward or backward through a line of one or more alphameric statements entered into said buffer storage means from said keyboard input means or recalled from said memory means; and said processing means is responsive to actuation of either of said forward and backward control keys for enabling said alphameric output display means to visually display part or all of the entered or recalled line of one or more alphameric statements up to and including as the last displayed character the last character to which that line has been single stepped. 14. An electronic calculator as in claim 13 wherein said buffer storage means includes a register pointer, said processing means being responsive to actuation of either said forward control key or said backward control key for single stepping said register pointer either forward or backward, respectively, through a line of one or more alphameric statements stored in said buffer storage means and for designating the last character of that line to be displayed by said alphameric output display means. | 0.58838 |
8,359,311 | 1 | 11 | 1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts. | 1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts. 11. The method of claim 1 , further comprising repeating said identifying of the set of resources as the user progresses through the task, wherein, at each part of the task, the method presents the user with a current set of resources associated with current context information, the current set of resources assisting the user in completing a next part of the task. | 0.5 |
9,019,868 | 11 | 16 | 11. A tangible machine readable storage medium comprising instructions that, when executed, cause a machine to perform operations comprising: classifying participants of the conference call in a hierarchy according to respective priority values; detecting an attempt of a first participant and a second participant to speak at substantially a same time; detecting which one of the first and second participants has a lower priority ranking; blocking an audio signal of the one of the first participant and the second participant having the lower priority ranking; placing an identifier associated with the blocked one of the first and second participants in a queue; organizing the queue according to a behavior-based policy, wherein organizing the queue according to the behavior-based policy comprises comparing an utterance of a current speaker to a keyword associated with the conference call to determine a relevancy of the utterance; and increasing a first point total associated with the current speaker in response to determining that the utterance is substantially relevant, and decreasing the first point total associated with the current speaker in response to determining that the utterance is substantially irrelevant. | 11. A tangible machine readable storage medium comprising instructions that, when executed, cause a machine to perform operations comprising: classifying participants of the conference call in a hierarchy according to respective priority values; detecting an attempt of a first participant and a second participant to speak at substantially a same time; detecting which one of the first and second participants has a lower priority ranking; blocking an audio signal of the one of the first participant and the second participant having the lower priority ranking; placing an identifier associated with the blocked one of the first and second participants in a queue; organizing the queue according to a behavior-based policy, wherein organizing the queue according to the behavior-based policy comprises comparing an utterance of a current speaker to a keyword associated with the conference call to determine a relevancy of the utterance; and increasing a first point total associated with the current speaker in response to determining that the utterance is substantially relevant, and decreasing the first point total associated with the current speaker in response to determining that the utterance is substantially irrelevant. 16. A storage medium as defined in claim 11 , wherein organizing the queue according to the behavior-based policy comprises comparing a duration of speaking of the current speaker to a threshold. | 0.706325 |
9,786,281 | 1 | 32 | 1. A device comprising: a profile building component in communication with an electronic data store; a speech recognition component; and a sensor configured to detect movement of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin listening for utterances from the user in response to receiving the indication; detect a first voice signal corresponding to a first utterance of the user; determine an identity of the user using the first voice signal; process the first voice signal to determine acoustic information about the user, wherein the acoustic information comprises at least one of an age, a gender, an accent type, a native language, or a type of speech pattern of the user; perform speech recognition on the first voice signal to obtain a transcript; process the transcript to determine language information relating to the user, wherein the language information comprises at least one of a name, hobbies, habits, or preferences of the user; store, in a user profile associated with the identity of the user, the acoustic information and the language information; determine acoustic model information using at least one of the first voice signal, the acoustic information, or the language information; and determine language model information using at least one of the transcript, the acoustic information, or the language information; and wherein the speech recognition component is configured to: receive a second voice signal corresponding to a second utterance of the user; determine the identity of the user using the second voice signal; perform speech recognition on the second voice signal using at least one of the acoustic model information or the language model information to obtain a word sequence that indicates that a third utterance corresponding to a language characteristic will be uttered by a second user different than the user at a time after a current time; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition at the time after the current time. | 1. A device comprising: a profile building component in communication with an electronic data store; a speech recognition component; and a sensor configured to detect movement of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin listening for utterances from the user in response to receiving the indication; detect a first voice signal corresponding to a first utterance of the user; determine an identity of the user using the first voice signal; process the first voice signal to determine acoustic information about the user, wherein the acoustic information comprises at least one of an age, a gender, an accent type, a native language, or a type of speech pattern of the user; perform speech recognition on the first voice signal to obtain a transcript; process the transcript to determine language information relating to the user, wherein the language information comprises at least one of a name, hobbies, habits, or preferences of the user; store, in a user profile associated with the identity of the user, the acoustic information and the language information; determine acoustic model information using at least one of the first voice signal, the acoustic information, or the language information; and determine language model information using at least one of the transcript, the acoustic information, or the language information; and wherein the speech recognition component is configured to: receive a second voice signal corresponding to a second utterance of the user; determine the identity of the user using the second voice signal; perform speech recognition on the second voice signal using at least one of the acoustic model information or the language model information to obtain a word sequence that indicates that a third utterance corresponding to a language characteristic will be uttered by a second user different than the user at a time after a current time; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition at the time after the current time. 32. The device of claim 1 , wherein the profile building component is further configured to: receive a third voice signal corresponding to a fourth utterance, wherein the fourth utterance is produced by an electronic device; process the third voice signal to determine additional preferences of the user, wherein the additional preferences of the user comprises an identification of a habit of the user, wherein the habit comprises a time that the user routinely watches television; and store, in the user profile associated with the identity of the user, the additional preferences of the user. | 0.5 |
9,691,040 | 11 | 12 | 11. An information processing device comprising: a memory and one or more processors coupled to the memory for executing: a schedule storage unit configured to store schedule information; a keyword storage unit configured to store multiple keywords which are classified into multiple categories; a keyword extraction unit configured to extract keywords from textual information on the basis of the keywords stored in the keyword storage unit, and specify one category corresponding the extracted keyword when extracting a keyword which was classified into a plurality of categories based on position thereof and relationships to other words in the textual information; a schedule information creation unit configured to create new schedule information or revised schedule information which causes schedule information stored in the schedule storage unit to be updated, based on the keywords extracted by the keyword extraction unit and the categories of the extracted keywords; and a schedule updating unit configured to store the new schedule information into the schedule storage unit, and update the schedule information stored in the schedule storage unit with the revised schedule information. | 11. An information processing device comprising: a memory and one or more processors coupled to the memory for executing: a schedule storage unit configured to store schedule information; a keyword storage unit configured to store multiple keywords which are classified into multiple categories; a keyword extraction unit configured to extract keywords from textual information on the basis of the keywords stored in the keyword storage unit, and specify one category corresponding the extracted keyword when extracting a keyword which was classified into a plurality of categories based on position thereof and relationships to other words in the textual information; a schedule information creation unit configured to create new schedule information or revised schedule information which causes schedule information stored in the schedule storage unit to be updated, based on the keywords extracted by the keyword extraction unit and the categories of the extracted keywords; and a schedule updating unit configured to store the new schedule information into the schedule storage unit, and update the schedule information stored in the schedule storage unit with the revised schedule information. 12. The information processing device according to claim 11 , wherein the keyword extraction unit is configured to partition the textual information into sequences of texts with using periods and/or commas, extract keywords from the sequences of the text through comparison with the multiple keywords stored in the keyword storage unit from the head of the each of the sequences of the text, and specify one keyword from context of the sequence of the text when a plurality of keywords are extracted at same position. | 0.666881 |
7,610,193 | 1 | 16 | 1. A machine-readable storage device encoded with a computer program product comprising instructions operable to cause a programmable processor to: search a document for a typesetting placeholder, wherein a typesetting placeholder is a recognized non-alphabetic character that formats the document; determine that the typesetting placeholder is ambiguous, and consequently create a set of candidate solutions from a string of characters including the ambiguous typesetting placeholder, wherein each solution in the set of candidate solutions comprises one or more character sub-strings created by uniquely resolving the ambiguous typesetting placeholder in the string of characters; search a dictionary stored on a computer storage device for the one or more character sub-strings in each solution in the set of candidate solutions; and use the dictionary search result to resolve the ambiguous typesetting placeholder in the string of characters. | 1. A machine-readable storage device encoded with a computer program product comprising instructions operable to cause a programmable processor to: search a document for a typesetting placeholder, wherein a typesetting placeholder is a recognized non-alphabetic character that formats the document; determine that the typesetting placeholder is ambiguous, and consequently create a set of candidate solutions from a string of characters including the ambiguous typesetting placeholder, wherein each solution in the set of candidate solutions comprises one or more character sub-strings created by uniquely resolving the ambiguous typesetting placeholder in the string of characters; search a dictionary stored on a computer storage device for the one or more character sub-strings in each solution in the set of candidate solutions; and use the dictionary search result to resolve the ambiguous typesetting placeholder in the string of characters. 16. The computer program product encoded on the machine-readable storage device of claim 1 , wherein the ambiguous typesetting placeholder comprises a white space between characters resolvable as a blank space or a kerning space. | 0.7331 |
8,825,479 | 3 | 8 | 3. A method for recognizing emotion in a primary audio signal comprising: extracting, using a computer, an MFCC feature from the primary audio signal; dividing, using a computer, the MFCC feature into MFCC subsections; selecting, using a computer, a set of the MFCC subsections; selecting, using a computer, a first set of reference samples from a reference database; computing, using a computer, a comparison of the set of MFCC subsections and the first set of reference samples; and determining, using a computer, a probable emotional state for the primary audio signal from the comparison. | 3. A method for recognizing emotion in a primary audio signal comprising: extracting, using a computer, an MFCC feature from the primary audio signal; dividing, using a computer, the MFCC feature into MFCC subsections; selecting, using a computer, a set of the MFCC subsections; selecting, using a computer, a first set of reference samples from a reference database; computing, using a computer, a comparison of the set of MFCC subsections and the first set of reference samples; and determining, using a computer, a probable emotional state for the primary audio signal from the comparison. 8. The method of claim 3 further comprising filtering the primary audio signal using a dynamic filter. | 0.779221 |
9,223,878 | 5 | 6 | 5. The system of claim 4 , wherein the system further comprises: a content auction system accessed through a public network, wherein the content auction system is configured to retrieve a sponsored content item based upon the search request and the plurality of user characteristics. | 5. The system of claim 4 , wherein the system further comprises: a content auction system accessed through a public network, wherein the content auction system is configured to retrieve a sponsored content item based upon the search request and the plurality of user characteristics. 6. The system of claim 5 , wherein the computer readable medium has stored thereon further instructions which, when executed by a processor of the computer, causes the processor to transmit the sponsored content item to the user, wherein the sponsored content item is presented with the search results to the user on the display of the mobile communication facility. | 0.5 |
8,954,500 | 5 | 7 | 5. The method of claim 1 , further comprising: determining a relevancy measure for each of the contacts which represents a relevance of the relationship between the first user and the contact, the relevancy measure for each contact being determined, at least in part, with reference to one or more of the first data source or the at least one external data source; wherein the relevancy measure is further determined with reference to one or more of a frequency of communication, a recency of communication, a volume of communication, a periodicity of communication, a number of connections, a group membership, a demographic characteristic, a name, a relationship category, or a geographic location. | 5. The method of claim 1 , further comprising: determining a relevancy measure for each of the contacts which represents a relevance of the relationship between the first user and the contact, the relevancy measure for each contact being determined, at least in part, with reference to one or more of the first data source or the at least one external data source; wherein the relevancy measure is further determined with reference to one or more of a frequency of communication, a recency of communication, a volume of communication, a periodicity of communication, a number of connections, a group membership, a demographic characteristic, a name, a relationship category, or a geographic location. 7. The method of claim 5 further comprising grouping the plurality of contacts with reference to the relevancy measures. | 0.786477 |
8,572,682 | 1 | 7 | 1. A computer-implemented method of managing access control policies on a computer system having two high-level programming language environments, comprising: managing, by the computer system, a structured language environment; managing, by the computer system, a dynamic language environment within the structured language environment; receiving a policy, wherein the policy is written in a dynamic language; storing the policy in the dynamic language environment; converting the policy from the dynamic language environment to the structured language environment; and generating a runtime in the structured language environment that includes the policy. | 1. A computer-implemented method of managing access control policies on a computer system having two high-level programming language environments, comprising: managing, by the computer system, a structured language environment; managing, by the computer system, a dynamic language environment within the structured language environment; receiving a policy, wherein the policy is written in a dynamic language; storing the policy in the dynamic language environment; converting the policy from the dynamic language environment to the structured language environment; and generating a runtime in the structured language environment that includes the policy. 7. The computer-implemented method of claim 1 , further comprising: receiving user-role assignment information, wherein the user-role assignment information is written in the dynamic language; converting the user-role assignment information from the dynamic language environment to the structured language environment; and storing the user-role assignment information as a data object in the structured language environment. | 0.576 |
8,688,694 | 1 | 8 | 1. A computer-implemented method, comprising: at a client computer having one or more processors and memory storing programs executed by the one or more processors, receiving user instructions to associate each of a first virtual channel and a second virtual channel with a first content provider, wherein the first virtual channel includes a first set of user-specified search criteria and the second virtual channel includes a second set of user-specified search criteria that is different from the first set of search criteria; continuously performing operations according to a predefined schedule, the operations including: receiving a first set of information items from the first content provider, wherein each information item includes a document title, a document summary, and a document link to a document at a respective remote location; for each of the first set of information items, retrieving the document identified by the corresponding document link from the respective remote location; applying the first set of search criteria to each of the first set of information items and its associated document to generate a first set of search results, wherein the first set of search results includes a first set of chunks within a first document and a third set of chunks within a second document, and each of the first set and the third set of chunks satisfies the first set of search criteria; applying the second set of search criteria to each of the first set of information items and its associated document to generate a second set of search results, wherein the second set of search results includes a second set of chunks within the first document, and each of the second set of chunks satisfies the second set of search criteria, wherein there is at least one difference between the first set of chunks and the second set of chunks; associating the first virtual channel with the first set of search results and the second virtual channel with the second set of search results, wherein there is at least one search result associated with both the first virtual channel and the second virtual channel; displaying the first virtual channel and the second virtual channel on the client computer; in response to a user selection of the first virtual channel, displaying, at least partially, information items associated with the first set of search results and the first set of chunks within the first document and the third set of chunks within the second document to the user; and in response to a user selection of one of the first set of chunks, displaying, at least partially, the first document including the user-selected chunk to the user adjacent to the display of the first set of chunks and the third set of chunks, wherein the user-selected chunk is visually distinguished from the rest of the document. | 1. A computer-implemented method, comprising: at a client computer having one or more processors and memory storing programs executed by the one or more processors, receiving user instructions to associate each of a first virtual channel and a second virtual channel with a first content provider, wherein the first virtual channel includes a first set of user-specified search criteria and the second virtual channel includes a second set of user-specified search criteria that is different from the first set of search criteria; continuously performing operations according to a predefined schedule, the operations including: receiving a first set of information items from the first content provider, wherein each information item includes a document title, a document summary, and a document link to a document at a respective remote location; for each of the first set of information items, retrieving the document identified by the corresponding document link from the respective remote location; applying the first set of search criteria to each of the first set of information items and its associated document to generate a first set of search results, wherein the first set of search results includes a first set of chunks within a first document and a third set of chunks within a second document, and each of the first set and the third set of chunks satisfies the first set of search criteria; applying the second set of search criteria to each of the first set of information items and its associated document to generate a second set of search results, wherein the second set of search results includes a second set of chunks within the first document, and each of the second set of chunks satisfies the second set of search criteria, wherein there is at least one difference between the first set of chunks and the second set of chunks; associating the first virtual channel with the first set of search results and the second virtual channel with the second set of search results, wherein there is at least one search result associated with both the first virtual channel and the second virtual channel; displaying the first virtual channel and the second virtual channel on the client computer; in response to a user selection of the first virtual channel, displaying, at least partially, information items associated with the first set of search results and the first set of chunks within the first document and the third set of chunks within the second document to the user; and in response to a user selection of one of the first set of chunks, displaying, at least partially, the first document including the user-selected chunk to the user adjacent to the display of the first set of chunks and the third set of chunks, wherein the user-selected chunk is visually distinguished from the rest of the document. 8. The method of claim 1 , wherein the first set of information items is an XML-based document. | 0.913636 |
7,827,125 | 1 | 11 | 1. A method for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the method comprising: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, by determining an implicit feedback value, an explicit feedback value, and a negative feedback value for the search results for which feedback is received, wherein, for concepts associated with search criteria applied to retrieve the search results, feedback is received to create a source concept that is compared against a reference concept to form a set of source concept values and a set of reference concept values, and wherein the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values by: applying the implicit feedback value to the values in the set of source concept values but not in the set of reference concept values; applying the explicit feedback value to the values in both the set of source concept values and the set of reference concept values; and applying the negative feedback value to the values in the set of reference concept values but not in the set of source concept values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. | 1. A method for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the method comprising: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, by determining an implicit feedback value, an explicit feedback value, and a negative feedback value for the search results for which feedback is received, wherein, for concepts associated with search criteria applied to retrieve the search results, feedback is received to create a source concept that is compared against a reference concept to form a set of source concept values and a set of reference concept values, and wherein the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values by: applying the implicit feedback value to the values in the set of source concept values but not in the set of reference concept values; applying the explicit feedback value to the values in both the set of source concept values and the set of reference concept values; and applying the negative feedback value to the values in the set of reference concept values but not in the set of source concept values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. 11. The method of claim 1 , wherein constructing the one or more profiles further comprises determining a feedback value tuple for each search result, the feedback value tuple including the implicit feedback value, the explicit feedback value, and the negative feedback value determined, each having a value between −1.0 and 1.0. | 0.718803 |
9,251,144 | 1 | 8 | 1. A method comprising: displaying, on a display device, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the display device; receiving, by an input device, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image to a server; receiving, from the server, one or more translated words in a second language corresponding to a translation of the at least one word of the one or more words in the first language; and displaying, on the display device, the one or more translated words. | 1. A method comprising: displaying, on a display device, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the display device; receiving, by an input device, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image to a server; receiving, from the server, one or more translated words in a second language corresponding to a translation of the at least one word of the one or more words in the first language; and displaying, on the display device, the one or more translated words. 8. The method of claim 1 , wherein the one or more translated words in the second language comprise a word-for-word translation corresponding to the at least one word of the one or more words in the first language. | 0.536797 |
7,543,055 | 1 | 2 | 1. A method for identifying a network threat, comprising: assembling a set of names of files responsible for proliferating a network threat and a set of names of files previously identified as not responsible for proliferating a network threat; inserting a network traffic monitor within a network service provider's infrastructure, the network traffic monitor configured to identify a first domain responsible for presently communicating at least one file from the set of names of files responsible for proliferating a network threat; searching the first domain for files not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; analyzing the content of the files not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; and adding a file name to one of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat responsive to the step of analyzing. | 1. A method for identifying a network threat, comprising: assembling a set of names of files responsible for proliferating a network threat and a set of names of files previously identified as not responsible for proliferating a network threat; inserting a network traffic monitor within a network service provider's infrastructure, the network traffic monitor configured to identify a first domain responsible for presently communicating at least one file from the set of names of files responsible for proliferating a network threat; searching the first domain for files not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; analyzing the content of the files not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; and adding a file name to one of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat responsive to the step of analyzing. 2. The method of claim 1 , further comprising: searching the first domain for links to a second domain other than the first domain; searching the second domain for files not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; analyzing the content of the files from the second domain not associated with either of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat; adding a file name to one of the set of names of files responsible for proliferating a network threat and the set of names of files previously identified as not responsible for proliferating a network threat responsive to the step of analyzing the content of files from the second domain; and updating a set of domain names that contain at least one file from the set of names of files responsible for proliferating a network threat. | 0.5 |
9,158,773 | 1 | 6 | 1. A method to reduce an amount of processing required to generate a response to a first case by a question answering system, the method comprising: determining that a similarity score, of the first case relative to a second case, exceeds a similarity threshold; identifying, by operation of one or more computer processors, a first feature of the second case having a first relevance score exceeding a relevance threshold, wherein the relevance score indicates that the first feature is relevant in generating a correct response to the second case; determining, based on the similarity score and the first relevance score, that the first feature is relevant in generating a correct response to the first case; identifying a first candidate answer for the first case that does not have the first feature; and refraining from analyzing the first candidate answer in generating the response to the first case, thereby reducing the amount of processing of the question answering system. | 1. A method to reduce an amount of processing required to generate a response to a first case by a question answering system, the method comprising: determining that a similarity score, of the first case relative to a second case, exceeds a similarity threshold; identifying, by operation of one or more computer processors, a first feature of the second case having a first relevance score exceeding a relevance threshold, wherein the relevance score indicates that the first feature is relevant in generating a correct response to the second case; determining, based on the similarity score and the first relevance score, that the first feature is relevant in generating a correct response to the first case; identifying a first candidate answer for the first case that does not have the first feature; and refraining from analyzing the first candidate answer in generating the response to the first case, thereby reducing the amount of processing of the question answering system. 6. The method of claim 1 , wherein identifying the first feature of the second case as having the first relevance score exceeding the relevance threshold is based on a stored dependency of the second case to the first feature. | 0.801056 |
7,941,418 | 1 | 7 | 1. A computer-implemented method of generating a dynamic corpus, the method comprising: (a) generating a plurality (n) of web threads, based upon a corresponding plurality of sets of words dequeued from a word queue of size m words, to obtain web thread resulting URLs, the web thread resulting URLs being returned by search engines in response to receiving the plurality of sets of words as search requests, the web thread resulting URLs corresponding to websites having text that includes the plurality of sets of words; (b) enqueueing the web thread resulting URLs in a URL queue of size o words; (c) generating a plurality (p) of text extraction threads, based upon documents downloaded using URLs dequeued from the URL queue, to obtain text files, the text files providing the dynamic corpus; (d) randomly obtaining new words from the text files; (e) enqueueing the randomly obtained words in the word queue; (f) iteratively repeating the steps (a), (b), (c), (d) and (e) to obtain the dynamic corpus having a predefined size of x first text files, wherein repeating the step (a) includes utilizing the randomly obtained words as additional search requests and receiving additional thread resulting URLs from the search engines in response to the additional search requests, the additional thread resulting URLs corresponding to websites having text that includes the randomly obtained words; (g) adjusting variables n, m, o, p based on a time required to obtain the dynamic corpus with x first text files and based on a predefined refresh rate that specifies an amount of time within which a user desires the dynamic corpus to obtain x new text files so the x first text files are replaced within the dynamic corpus with the x new text files within the amount of time specified by the refresh rate; and iteratively repeating steps (a), (b), (c), (d), (e), (f) and (g). | 1. A computer-implemented method of generating a dynamic corpus, the method comprising: (a) generating a plurality (n) of web threads, based upon a corresponding plurality of sets of words dequeued from a word queue of size m words, to obtain web thread resulting URLs, the web thread resulting URLs being returned by search engines in response to receiving the plurality of sets of words as search requests, the web thread resulting URLs corresponding to websites having text that includes the plurality of sets of words; (b) enqueueing the web thread resulting URLs in a URL queue of size o words; (c) generating a plurality (p) of text extraction threads, based upon documents downloaded using URLs dequeued from the URL queue, to obtain text files, the text files providing the dynamic corpus; (d) randomly obtaining new words from the text files; (e) enqueueing the randomly obtained words in the word queue; (f) iteratively repeating the steps (a), (b), (c), (d) and (e) to obtain the dynamic corpus having a predefined size of x first text files, wherein repeating the step (a) includes utilizing the randomly obtained words as additional search requests and receiving additional thread resulting URLs from the search engines in response to the additional search requests, the additional thread resulting URLs corresponding to websites having text that includes the randomly obtained words; (g) adjusting variables n, m, o, p based on a time required to obtain the dynamic corpus with x first text files and based on a predefined refresh rate that specifies an amount of time within which a user desires the dynamic corpus to obtain x new text files so the x first text files are replaced within the dynamic corpus with the x new text files within the amount of time specified by the refresh rate; and iteratively repeating steps (a), (b), (c), (d), (e), (f) and (g). 7. The method of claim 1 , and further comprising increasing or decreasing at least one of a number of words in the word queue, a number of web threads in the plurality of web threads, a number of URLs in the URL queue, and a number of text extraction threads in the plurality of text extraction threads in order to optimize the generation of the dynamic corpus. | 0.5 |
8,429,206 | 7 | 11 | 7. The method of claim 1 where the step of comparing the at least one sub-expression of the input expression to the at least one element of the at least one set of input sub-expressions comprises the steps of: performing at least one traversal of both the at least one sub-expression of the input expression and at least one element of the at least one set of input sub-expressions, the traversal involving the visitation of at least one node; forming at least one representation of the at least one node visited on the at least one traversal; and comparing the at least one representation of the at least one sub-expression of the input expression to at least one representation of the at least one element of the set of input sub-expressions. | 7. The method of claim 1 where the step of comparing the at least one sub-expression of the input expression to the at least one element of the at least one set of input sub-expressions comprises the steps of: performing at least one traversal of both the at least one sub-expression of the input expression and at least one element of the at least one set of input sub-expressions, the traversal involving the visitation of at least one node; forming at least one representation of the at least one node visited on the at least one traversal; and comparing the at least one representation of the at least one sub-expression of the input expression to at least one representation of the at least one element of the set of input sub-expressions. 11. The method of claim 7 wherein the at least one traversal is at least one in-order traversal. | 0.510204 |
7,676,739 | 7 | 8 | 7. The method of claim 1 , further comprising the step of maintaining a history buffer of matches. | 7. The method of claim 1 , further comprising the step of maintaining a history buffer of matches. 8. The method of claim 7 , wherein the history buffer is used to update a set of allowed annotations. | 0.5 |
8,332,383 | 2 | 5 | 2. The system of claim 1 , wherein each of the search definitions is formulated to include a constraint set that is unique, and wherein the constraints of the constraint set are selected from a group including a keyword constraint, a category constraint, a search parameter constraint, and an attribute constraint. | 2. The system of claim 1 , wherein each of the search definitions is formulated to include a constraint set that is unique, and wherein the constraints of the constraint set are selected from a group including a keyword constraint, a category constraint, a search parameter constraint, and an attribute constraint. 5. The system of claim 2 , wherein each constraint set is selectable by the user to display associated data items. | 0.847185 |
8,180,785 | 12 | 14 | 12. A system for searching numerical terms, comprising: a computer-based stemming module for processing a numerical term to a stem, the stem being in the form of a number, and a distance measurement of the numerical term to the stem, wherein a numerical term is a string of characters including identified as a number by a numeric parser; an indexer for indexing the numerical term in a search index by the stem for search retrieval; a user interface for setting a modulus for sensitivity of the stemming; wherein the stemming module and the indexer are executed in any of a) computer hardware having a processor coupled to a memory, wherein said processor is configured to execute said processing and indexing steps and store information related to said processing and indexing steps in said memory, and b) computer software embodied in a non-transitory, computer-readable medium. | 12. A system for searching numerical terms, comprising: a computer-based stemming module for processing a numerical term to a stem, the stem being in the form of a number, and a distance measurement of the numerical term to the stem, wherein a numerical term is a string of characters including identified as a number by a numeric parser; an indexer for indexing the numerical term in a search index by the stem for search retrieval; a user interface for setting a modulus for sensitivity of the stemming; wherein the stemming module and the indexer are executed in any of a) computer hardware having a processor coupled to a memory, wherein said processor is configured to execute said processing and indexing steps and store information related to said processing and indexing steps in said memory, and b) computer software embodied in a non-transitory, computer-readable medium. 14. The system as claimed in claim 12 , wherein the tokenizer determines textual terms and numerical terms in a document, and wherein textual terms are processed by a textual stemming module. | 0.794181 |
9,779,140 | 4 | 5 | 4. The method according to claim 3 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. | 4. The method according to claim 3 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. 5. The method according to claim 4 , wherein the at least one popularity metric comprises at least one of query-to-click ratio information or click-through ratio (CTR) information for the at least one web page search result. | 0.575758 |
7,856,472 | 156 | 160 | 156. The computer program product of claim 70 , wherein the computer program product is operable such that first preloaded information derived from the first message is preloaded and initially hidden, and later displayed in response to a first user interaction. | 156. The computer program product of claim 70 , wherein the computer program product is operable such that first preloaded information derived from the first message is preloaded and initially hidden, and later displayed in response to a first user interaction. 160. The computer program product of claim 156 , wherein the computer program product is operable such that the first preloaded information includes a date and time. | 0.664634 |
9,904,584 | 10 | 11 | 10. The system of claim 6 , wherein the computer-executable instructions further cause the processing device to: determine anomaly scores for the identified anomalous latencies; and generate a ranked list of the predicates using the anomaly scores. | 10. The system of claim 6 , wherein the computer-executable instructions further cause the processing device to: determine anomaly scores for the identified anomalous latencies; and generate a ranked list of the predicates using the anomaly scores. 11. The system of claim 10 , wherein an individual anomaly score indicates a respective magnitude of an individual identified anomalous latency. | 0.5 |
9,666,064 | 1 | 12 | 1. An information processing system comprising circuitry configured to: extract environment expressions from incident information, which describes an incident in which what abnormal action was performed in what environment, and which includes the environment expressions expressing the environments to be monitored and action expressions expressing actions performed in the environments; extract the action expressions from the incident information; generate information in which the extracted action expressions are associated with the environment expressions expressing the environments when the actions expressed by the action expressions have been performed among the extracted environment expressions, conducts a search with respect to the generated information, with the action expressions as a key, and calculates, on the basis of the search, frequency at which the environment expressions have been extracted; store the action expressions and the associated environment; refer to the stored expressions, and, when the frequency at which the environment expressions associated with a specific action expression among the stored action expressions have been extracted is higher than a predetermined threshold value, associates the specific action expression with the environment expressions having high frequency of extraction and outputs the associated expressions; and generate a monitoring rule for monitoring occurrence of an abnormal circumstance, on the basis of the outputted environment expressions and action expression, the monitoring rule having a conditional clause in which the environments expressed by the environment expressions are satisfied and the action expressed by the action expression is detected. | 1. An information processing system comprising circuitry configured to: extract environment expressions from incident information, which describes an incident in which what abnormal action was performed in what environment, and which includes the environment expressions expressing the environments to be monitored and action expressions expressing actions performed in the environments; extract the action expressions from the incident information; generate information in which the extracted action expressions are associated with the environment expressions expressing the environments when the actions expressed by the action expressions have been performed among the extracted environment expressions, conducts a search with respect to the generated information, with the action expressions as a key, and calculates, on the basis of the search, frequency at which the environment expressions have been extracted; store the action expressions and the associated environment; refer to the stored expressions, and, when the frequency at which the environment expressions associated with a specific action expression among the stored action expressions have been extracted is higher than a predetermined threshold value, associates the specific action expression with the environment expressions having high frequency of extraction and outputs the associated expressions; and generate a monitoring rule for monitoring occurrence of an abnormal circumstance, on the basis of the outputted environment expressions and action expression, the monitoring rule having a conditional clause in which the environments expressed by the environment expressions are satisfied and the action expressed by the action expression is detected. 12. The information processing system according to claim 1 , the circuitry further configured to associate a plurality of expressions expressing the same or similar actions or environments with a typical expression which is a typical expression of the plurality of expressions, and stores the associated expressions; and refer to the stored typical expression, on the basis of the environment expressions or the action expressions, to replace the environment expressions or the action expressions with the typical expression. | 0.5 |
8,392,440 | 1 | 15 | 1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting one or more of the one or more splits according to the overall score for each split; and augmenting the query with the subterms of each selected split. | 1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting one or more of the one or more splits according to the overall score for each split; and augmenting the query with the subterms of each selected split. 15. The system of claim 1 , wherein the operations further comprise maintaining a list of subterms that should not be used in splits. | 0.844262 |
8,326,604 | 9 | 13 | 9. A method for compressing textual data using a dictionary comprising: receiving the dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; matching words and phrases within the textual data with the keys of the dictionary; replacing the words and phrases within the textual data that match the keys of the dictionary with the identifiers of the keys; and, storing the textual data within which the words and phrases that match the keys have been replaced with the identifiers of the keys. | 9. A method for compressing textual data using a dictionary comprising: receiving the dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; matching words and phrases within the textual data with the keys of the dictionary; replacing the words and phrases within the textual data that match the keys of the dictionary with the identifiers of the keys; and, storing the textual data within which the words and phrases that match the keys have been replaced with the identifiers of the keys. 13. The method of claim 9 , further comprising constructing the dictionary based on the textual data that is to be compressed using the dictionary. | 0.765924 |
5,566,330 | 13 | 14 | 13. The stored program computer of claim 12 wherein: the editing styles tailorable by said applications programmer further comprise extended column definitions of display characteristics for data of corresponding columns of said database table beyond those characteristics inherent in a data dictionary of said database table. | 13. The stored program computer of claim 12 wherein: the editing styles tailorable by said applications programmer further comprise extended column definitions of display characteristics for data of corresponding columns of said database table beyond those characteristics inherent in a data dictionary of said database table. 14. The stored program computer of claim 13 wherein: said extended column definitions comprise a label for labelling the display of data of a column of said database table, said label being different than the column name maintained by said database manager program. | 0.584639 |
8,466,896 | 1 | 4 | 1. An apparatus for selectable input, comprising: a touch screen having a plurality of selectable regions therein; and at least one processor programmed for tracking motion that corresponds to interaction of a user in relation to the touch screen, wherein the tracked motion defines a path comprising path data, wherein the path data comprises sequential positions and corresponding times; for each sequential position, comparing the current position and corresponding time to the path data; detecting if the current position meets a threshold of a selectable position along the defined path, wherein the defined path comprises at least two selectable positions, wherein the threshold of a selectable position in relation to the touch screen comprises any of starting the defined path, looping the defined path, changing direction of the defined path, changing velocity of the defined path, pausing motion in the defined path, and ending the defined path, and wherein the threshold of changing direction comprises any of a curve having an estimated radius that is less than a threshold geometry, a comparison of the defined path direction before and after a curve, a sharp cusp edge in the defined path, or a comparison of path direction before and after a cusp; determining which of the detected selectable positions along the defined path correspond to one of the selectable regions; and adding a selection that corresponds to the determined selectable region to a sequence of selections that corresponds to the defined path. | 1. An apparatus for selectable input, comprising: a touch screen having a plurality of selectable regions therein; and at least one processor programmed for tracking motion that corresponds to interaction of a user in relation to the touch screen, wherein the tracked motion defines a path comprising path data, wherein the path data comprises sequential positions and corresponding times; for each sequential position, comparing the current position and corresponding time to the path data; detecting if the current position meets a threshold of a selectable position along the defined path, wherein the defined path comprises at least two selectable positions, wherein the threshold of a selectable position in relation to the touch screen comprises any of starting the defined path, looping the defined path, changing direction of the defined path, changing velocity of the defined path, pausing motion in the defined path, and ending the defined path, and wherein the threshold of changing direction comprises any of a curve having an estimated radius that is less than a threshold geometry, a comparison of the defined path direction before and after a curve, a sharp cusp edge in the defined path, or a comparison of path direction before and after a cusp; determining which of the detected selectable positions along the defined path correspond to one of the selectable regions; and adding a selection that corresponds to the determined selectable region to a sequence of selections that corresponds to the defined path. 4. The apparatus of claim 1 , wherein the selectable regions are associated with any of characters, numbers, tasks, actions, functions, decisions, priorities, outcomes, or points. | 0.605727 |
9,424,247 | 4 | 7 | 4. The method of claim 3 , wherein one or more task terms are assigned to the given information field. | 4. The method of claim 3 , wherein one or more task terms are assigned to the given information field. 7. The method of claim 4 , further comprising: prompting the user to replace the task terms with the n-gram. | 0.717277 |
8,150,862 | 2 | 9 | 2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. | 2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. 9. The method of claim 2 , wherein the event parsing logic specified by a respective XML document includes conditional logic for conditionally supplementing the information extracted from the second event with information extracted from the first event in accordance with when a condition specified in the XML document is satisfied. | 0.63913 |
8,626,743 | 8 | 9 | 8. The apparatus of claim 6 , wherein the computer-readable code is further configured to: store the user query. | 8. The apparatus of claim 6 , wherein the computer-readable code is further configured to: store the user query. 9. The apparatus of claim 8 , wherein storing the user query further comprises storing a plurality of user queries. | 0.5 |
8,731,819 | 1 | 3 | 1. A method of identifying and associating individuals comprising: providing a first set of records associated with one or more individuals at a defined geographic location and a defined period of time; providing a second set of records associated with one or more individuals across multiple geographic locations and defined time periods; a user selecting both a desired demarcated area of the Earth and a desired date range on a computing device; on the computing device, identifying a set of individuals corresponding to the selected demarcated area of the Earth and the desired date range, and associating relationships among the set of identified individuals who previously had no identified relationships in the first and second sets of records corresponding to the demarcated area of the Earth and the desired date range; and outputting to the user by displaying on a monitor of the computing device results of the associated relationships among the set of identified individuals to provide the user with results of known and probable relationships in the defined geographic location over the defined period of time. | 1. A method of identifying and associating individuals comprising: providing a first set of records associated with one or more individuals at a defined geographic location and a defined period of time; providing a second set of records associated with one or more individuals across multiple geographic locations and defined time periods; a user selecting both a desired demarcated area of the Earth and a desired date range on a computing device; on the computing device, identifying a set of individuals corresponding to the selected demarcated area of the Earth and the desired date range, and associating relationships among the set of identified individuals who previously had no identified relationships in the first and second sets of records corresponding to the demarcated area of the Earth and the desired date range; and outputting to the user by displaying on a monitor of the computing device results of the associated relationships among the set of identified individuals to provide the user with results of known and probable relationships in the defined geographic location over the defined period of time. 3. The method of claim 1 wherein the relationships are selected from the group consisting of pedigree relationships, non-pedigree group or affiliation relationships. | 0.952063 |
10,133,781 | 10 | 16 | 10. A method of generating a query in a user interface, the method comprising: displaying, in a visio-spatial user interface generated by a processor based device, a user interface (UI) element representation of a first query item, the first query item being a data structure belonging to a data set and having at least one attribute; displaying, in the visio-spatial user interface, a UI element representation of a second query item, the second query item being an anchor query item type of data structure defined as relating to at least one particular attribute of another query item; receiving an indication of a user selectively positioning one of the UI element representation of one of the first query item and the UI element representation of the second query item in proximate location to the UI element representation of the other of the first query item and the second query item in the visio-spatial user interface, the visio-spatial user interface including a display of both the UI element representation of the first query item and the UI element representation of the second query item; associating, by a processor, the second query item with the first query item in response to the user selectively manipulating at least one of the UI element representation of the first query item and the UI element representation of the second query item within the visio-spatial user interface to indicate a relationship between the first query item and the second query item; automatically retrieving, in response to the second query item being associated with the first query item, a value for the at least one particular attribute of the second query item defined as relating to another query item from the first query item; generating, by the processor, query search terms including a combination of the retrieved value and the second query item; and saving a record of the query search terms. | 10. A method of generating a query in a user interface, the method comprising: displaying, in a visio-spatial user interface generated by a processor based device, a user interface (UI) element representation of a first query item, the first query item being a data structure belonging to a data set and having at least one attribute; displaying, in the visio-spatial user interface, a UI element representation of a second query item, the second query item being an anchor query item type of data structure defined as relating to at least one particular attribute of another query item; receiving an indication of a user selectively positioning one of the UI element representation of one of the first query item and the UI element representation of the second query item in proximate location to the UI element representation of the other of the first query item and the second query item in the visio-spatial user interface, the visio-spatial user interface including a display of both the UI element representation of the first query item and the UI element representation of the second query item; associating, by a processor, the second query item with the first query item in response to the user selectively manipulating at least one of the UI element representation of the first query item and the UI element representation of the second query item within the visio-spatial user interface to indicate a relationship between the first query item and the second query item; automatically retrieving, in response to the second query item being associated with the first query item, a value for the at least one particular attribute of the second query item defined as relating to another query item from the first query item; generating, by the processor, query search terms including a combination of the retrieved value and the second query item; and saving a record of the query search terms. 16. The method of claim 10 , further comprising determining whether the at least one attribute of the first query item is compatible with the at least one particular attribute defined for the second query item. | 0.794118 |
9,230,061 | 1 | 10 | 1. A contextual analysis system comprising: memory; circuitry comprising at least one data processor that is configured to: extract data elements from an unstructured text input, the data elements being words or phrases; identify whether the extracted data elements are relevant to a predetermined context, the predetermined context being a predetermined list of keywords or phrases; determine, in response to determining that the extracted words or phrases are relevant to the predetermined list of keywords or phrases, whether the extracted words or phrases match an item included in a predetermined list of truth cases, and tagging matched words or phrases as a concept; tag each concept that is included in a predetermined keyword list as a trigger; generate a triggered block that includes a sequence of concepts that includes the trigger; generate a key-word value pair in response to determining that the triggered block matches at least one of the predetermined list of truth cases; generate a new concept, for inclusion in the triggered block, based on an evaluation of the generated keyword-value pair against an algorithm stored in a context algorithm repository, and based on the information contained in previously generated keyword-value pairs and structured data elements extracted from the same source as the unstructured data elements; determine whether the new triggered block complies with the predetermined list of truth cases, the predetermined list of truth cases being at least one medical guideline, wherein the at least one medical guideline includes information indicating a periodicity requirement for performing a task in the predetermined context; determine, based on the relevant data elements, whether the periodicity requirement is violated; generate a recommendation based on the determination as to whether the information contained in the new triggered block complies with the medical guideline; and output the recommendation to a display interface. | 1. A contextual analysis system comprising: memory; circuitry comprising at least one data processor that is configured to: extract data elements from an unstructured text input, the data elements being words or phrases; identify whether the extracted data elements are relevant to a predetermined context, the predetermined context being a predetermined list of keywords or phrases; determine, in response to determining that the extracted words or phrases are relevant to the predetermined list of keywords or phrases, whether the extracted words or phrases match an item included in a predetermined list of truth cases, and tagging matched words or phrases as a concept; tag each concept that is included in a predetermined keyword list as a trigger; generate a triggered block that includes a sequence of concepts that includes the trigger; generate a key-word value pair in response to determining that the triggered block matches at least one of the predetermined list of truth cases; generate a new concept, for inclusion in the triggered block, based on an evaluation of the generated keyword-value pair against an algorithm stored in a context algorithm repository, and based on the information contained in previously generated keyword-value pairs and structured data elements extracted from the same source as the unstructured data elements; determine whether the new triggered block complies with the predetermined list of truth cases, the predetermined list of truth cases being at least one medical guideline, wherein the at least one medical guideline includes information indicating a periodicity requirement for performing a task in the predetermined context; determine, based on the relevant data elements, whether the periodicity requirement is violated; generate a recommendation based on the determination as to whether the information contained in the new triggered block complies with the medical guideline; and output the recommendation to a display interface. 10. The contextual analysis system according to claim 1 , wherein: the circuitry is configured to generate a new keyword-value pair based on the generated keyword-value pair; and the new keyword-value pair is generated, by the circuitry, based on an evaluation of the generated keyword-value pair against an algorithm stored in a context algorithm repository, and based on the information contained in the previously generated keyword-value pairs and structured data elements extracted from a same source as the unstructured data elements. | 0.5 |
9,586,315 | 1 | 5 | 1. A computer-implemented method for enabling generalizable user-robot collaboration, comprising: providing a composition of a robot capability and one or more user interaction capabilities, wherein the robot capability models at least one functionality of a robot for performing a type of task action; specializing the robot capability with an information kernel to provide a specialized robot capability, wherein the information kernel encapsulates a set of task-related parameters associated with the type of task action; providing an instance of the specialized robot capability as a robot capability element that controls the at least one functionality of the robot based on the set of task-related parameters; providing one or more instances of the one or more user interaction capabilities as one or more interaction capability elements; executing the robot capability element to receive user input via the one or more user interaction capability elements; and controlling, based on the user input and the set of task-related parameters, the at least one functionality of the robot to perform at least one task action of the type of task action in collaboration with the user input. | 1. A computer-implemented method for enabling generalizable user-robot collaboration, comprising: providing a composition of a robot capability and one or more user interaction capabilities, wherein the robot capability models at least one functionality of a robot for performing a type of task action; specializing the robot capability with an information kernel to provide a specialized robot capability, wherein the information kernel encapsulates a set of task-related parameters associated with the type of task action; providing an instance of the specialized robot capability as a robot capability element that controls the at least one functionality of the robot based on the set of task-related parameters; providing one or more instances of the one or more user interaction capabilities as one or more interaction capability elements; executing the robot capability element to receive user input via the one or more user interaction capability elements; and controlling, based on the user input and the set of task-related parameters, the at least one functionality of the robot to perform at least one task action of the type of task action in collaboration with the user input. 5. The method of claim 1 , wherein the type of task action includes motion constraint and the set of task-related parameters in the information kernel includes a set of tool parameters associated with a type of tool, and wherein executing the robot capability element further comprises: detecting that a tool of the type of tool is attached to the robot; and constraining, based on the set of tool parameters associated with the type of tool, one or more motions of the robot in performing the at least one task action responsive to the user input, thereby enforcing the motion constraint. | 0.5 |
8,990,225 | 4 | 7 | 4. A computer-executed method for filtering outbound content via inference detection, the method comprising: receiving a first piece of outbound content associated with a destination identifier; extracting keywords from the first piece of outbound content; issuing a set of web queries that each includes one or more of the extracted keywords to obtain a set of search results; extracting a set of candidate keywords from the search results returned by a search engine in response to the queries; performing inference detection using the set of search results for the extracted keywords; determining, from the set of candidate keywords, a set of expected-content keywords which are determined to be representative of the previously sent content based on the inference detection; ranking the set of candidate keywords extracted from the search results based on a confidence value generated using web-based inference detection, wherein the confidence value evaluates the candidate keyword's sensitivity to expected content; selecting one or more top ranked keywords to represent the first piece of outbound content; responsive to receiving a second piece of outbound content, determining whether the second piece of outbound content is proper, which involves performing one of: determining that the second piece of outbound content is associated with the first destination identifier, and the number of expected-content keywords present in the second piece of outbound content is below a first predetermined threshold; and determining that the second piece of outbound content is not associated with the first destination identifier, and the number of expected-content keywords present in the second piece of outbound content is above a second predetermined threshold; and responsive to the second piece of outbound content being improper, displaying the destination identifier for the second piece of outbound content, the selected one or more top ranked keywords to represent the first piece of outbound content, and at least one expected-content keyword selected to represent the second piece of outbound content, thereby allowing a user to determine whether the second piece of outbound content has the proper content and destination identifier. | 4. A computer-executed method for filtering outbound content via inference detection, the method comprising: receiving a first piece of outbound content associated with a destination identifier; extracting keywords from the first piece of outbound content; issuing a set of web queries that each includes one or more of the extracted keywords to obtain a set of search results; extracting a set of candidate keywords from the search results returned by a search engine in response to the queries; performing inference detection using the set of search results for the extracted keywords; determining, from the set of candidate keywords, a set of expected-content keywords which are determined to be representative of the previously sent content based on the inference detection; ranking the set of candidate keywords extracted from the search results based on a confidence value generated using web-based inference detection, wherein the confidence value evaluates the candidate keyword's sensitivity to expected content; selecting one or more top ranked keywords to represent the first piece of outbound content; responsive to receiving a second piece of outbound content, determining whether the second piece of outbound content is proper, which involves performing one of: determining that the second piece of outbound content is associated with the first destination identifier, and the number of expected-content keywords present in the second piece of outbound content is below a first predetermined threshold; and determining that the second piece of outbound content is not associated with the first destination identifier, and the number of expected-content keywords present in the second piece of outbound content is above a second predetermined threshold; and responsive to the second piece of outbound content being improper, displaying the destination identifier for the second piece of outbound content, the selected one or more top ranked keywords to represent the first piece of outbound content, and at least one expected-content keyword selected to represent the second piece of outbound content, thereby allowing a user to determine whether the second piece of outbound content has the proper content and destination identifier. 7. The method of claim 4 , wherein ranking the keywords extracted from the search results comprises determining the number of documents which contain a respective keyword. | 0.602326 |
9,396,167 | 3 | 4 | 3. The method of claim 1 , wherein each of the plurality of content items have an asset type selected from a group consisting of text and image. | 3. The method of claim 1 , wherein each of the plurality of content items have an asset type selected from a group consisting of text and image. 4. The method of claim 3 , wherein the difference between sizes of each slot in a candidate template and size constraints of one or more of the plurality of content items is based on an aspect ratio of each slot in the candidate template and a minimum or a maximum aspect ratio of content items with an asset image type. | 0.5 |
9,405,186 | 10 | 14 | 10. A program product stored on a non-transitory computer readable storage medium, the program product operative to automatically create a target sample plan for optical proximity correction (OPC) calibration with a minimal number of clips when executed, the non-transitory computer readable storage medium comprising program code for: defining a sample plan including a plurality of clips, each of the plurality of clips representing portions of an integrated circuit (IC) layout; calculating a total relevancy score of a projected sample plan for the IC layout, wherein the projected sample plan includes a candidate clip representing an additional portion of the IC layout, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight for the at least one relevancy criterion, the at least one relevancy criterion being one of a topology type of a clip, a printing difficulty of a clip, and a dimensional ratio between clips in the projected sample plan; calculating a relevancy score difference between the total relevancy score of the projected sample plan and a total relevancy score of the sample plan without the candidate clip; adding the candidate clip to the sample plan for the IC layout and removing the candidate clip from the plurality of clips in response to the relevancy score difference substantially fitting a non-linear relevancy score function removing the candidate clip from the plurality of clips without adding the clip to the sample plan for the IC layout in response to the relevancy score difference substantially fitting a linear relevancy score function, wherein the candidate clip not being added to the sample plan indicates that the sample plan includes the minimal number of clips; and generating an OPC model using the sample plan with the minimal number of clips, wherein the sample plan with the minimal number of clips represents the target sample plan, and wherein the OPC model is used to manufacture at least one IC. | 10. A program product stored on a non-transitory computer readable storage medium, the program product operative to automatically create a target sample plan for optical proximity correction (OPC) calibration with a minimal number of clips when executed, the non-transitory computer readable storage medium comprising program code for: defining a sample plan including a plurality of clips, each of the plurality of clips representing portions of an integrated circuit (IC) layout; calculating a total relevancy score of a projected sample plan for the IC layout, wherein the projected sample plan includes a candidate clip representing an additional portion of the IC layout, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight for the at least one relevancy criterion, the at least one relevancy criterion being one of a topology type of a clip, a printing difficulty of a clip, and a dimensional ratio between clips in the projected sample plan; calculating a relevancy score difference between the total relevancy score of the projected sample plan and a total relevancy score of the sample plan without the candidate clip; adding the candidate clip to the sample plan for the IC layout and removing the candidate clip from the plurality of clips in response to the relevancy score difference substantially fitting a non-linear relevancy score function removing the candidate clip from the plurality of clips without adding the clip to the sample plan for the IC layout in response to the relevancy score difference substantially fitting a linear relevancy score function, wherein the candidate clip not being added to the sample plan indicates that the sample plan includes the minimal number of clips; and generating an OPC model using the sample plan with the minimal number of clips, wherein the sample plan with the minimal number of clips represents the target sample plan, and wherein the OPC model is used to manufacture at least one IC. 14. The program product of claim 10 , wherein in the case that the at least one relevancy criterion includes the printing difficulty, the plurality of clips includes a highest printing difficulty clip and a lowest printing difficulty clip, and the printing difficulty is calculated based on a critical dimension or a layout lithography difficulty estimator (LDE) of the clip. | 0.633072 |
8,365,090 | 21 | 25 | 21. A non-transitory computer readable storage medium having stored therein instructions, which when executed by a device with a touch screen display, cause the device to: display an electronic document at a first magnification on the touch screen display; detect a gesture on the touch screen display corresponding to a command to zoom out by a user-specified amount; display the electronic document at a magnification less than the first magnification on the touch screen display, in response to detecting the gesture; display the electronic document at a magnification wherein areas beyond opposite edges of the electronic document are displayed on the touch screen display, if a document length or a document width is entirely displayed while the gesture is still detected on the touch screen display; and in response to detecting termination of the gesture, display the electronic document at a magnification wherein the areas beyond opposite edges of the electronic document are no longer displayed on the touch screen display. | 21. A non-transitory computer readable storage medium having stored therein instructions, which when executed by a device with a touch screen display, cause the device to: display an electronic document at a first magnification on the touch screen display; detect a gesture on the touch screen display corresponding to a command to zoom out by a user-specified amount; display the electronic document at a magnification less than the first magnification on the touch screen display, in response to detecting the gesture; display the electronic document at a magnification wherein areas beyond opposite edges of the electronic document are displayed on the touch screen display, if a document length or a document width is entirely displayed while the gesture is still detected on the touch screen display; and in response to detecting termination of the gesture, display the electronic document at a magnification wherein the areas beyond opposite edges of the electronic document are no longer displayed on the touch screen display. 25. The computer readable storage medium of claim 21 , wherein the areas beyond opposite edges of the electronic document include an area beyond a right edge of the document and an area beyond a left edge of the document. | 0.644695 |
9,432,495 | 1 | 6 | 1. A method, comprising: receiving, at a processor operating in a vehicle, an audio signal generated from speech spoken by a user; recognizing, by the processor, a portion of the audio signal that corresponds to a command prefix, the command prefix representing a spoken word that indicates a next spoken word is a voice command; identifying, by the processor, another portion of the audio signal corresponding to the next spoken word after the command prefix; recognizing, by the processor, the next spoken word based on the another portion of the audio signal; comparing, by the processor, the next spoken word to electronic associations between commands and words including the next spoken word; recognizing, by the processor, the voice command of the commands that is electronically associated with the next spoken word; and executing, by the processor, the command in response to the speech spoken by the user. | 1. A method, comprising: receiving, at a processor operating in a vehicle, an audio signal generated from speech spoken by a user; recognizing, by the processor, a portion of the audio signal that corresponds to a command prefix, the command prefix representing a spoken word that indicates a next spoken word is a voice command; identifying, by the processor, another portion of the audio signal corresponding to the next spoken word after the command prefix; recognizing, by the processor, the next spoken word based on the another portion of the audio signal; comparing, by the processor, the next spoken word to electronic associations between commands and words including the next spoken word; recognizing, by the processor, the voice command of the commands that is electronically associated with the next spoken word; and executing, by the processor, the command in response to the speech spoken by the user. 6. The method of claim 1 , further comprising initiating a call in response to the speech spoken by the user. | 0.570866 |
8,577,682 | 13 | 15 | 13. The at least one non-transitory computer-readable medium of claim 12 , wherein the method further comprises: determining whether the computer has an already-installed text-to-speech engine that is compatible with the computer instructions; and if the computer does not have an already-installed text-to-speech engine that is compatible with the computer instructions, installing on the computer a newly-installed compatible text-to-speech engine that is compatible with the computer instructions. | 13. The at least one non-transitory computer-readable medium of claim 12 , wherein the method further comprises: determining whether the computer has an already-installed text-to-speech engine that is compatible with the computer instructions; and if the computer does not have an already-installed text-to-speech engine that is compatible with the computer instructions, installing on the computer a newly-installed compatible text-to-speech engine that is compatible with the computer instructions. 15. The at least one non-transitory computer-readable medium of claim 13 , wherein: if the computer does not have the already-installed text-to-speech engine, removing the newly-installed compatible text-to-speech engine from the computer following the installation of the application program. | 0.745217 |
8,539,510 | 1 | 12 | 1. A method comprising: capturing a stream of operational events; and materializing, by an activity monitoring computer system, a resulting view, wherein the resulting view comprises a dynamically defined view of the stream of operational events, wherein the materializing of the resulting view comprises: forming a row for at least one event in the stream of operational events; capturing a context that comprises data relevant to the at least one event; and joining the context with the row to form a compound row within the resulting view; and when a business rule applied to the resulting view holds true, outputting a reportlet corresponding to an alert that is based at least in part on the business rule. | 1. A method comprising: capturing a stream of operational events; and materializing, by an activity monitoring computer system, a resulting view, wherein the resulting view comprises a dynamically defined view of the stream of operational events, wherein the materializing of the resulting view comprises: forming a row for at least one event in the stream of operational events; capturing a context that comprises data relevant to the at least one event; and joining the context with the row to form a compound row within the resulting view; and when a business rule applied to the resulting view holds true, outputting a reportlet corresponding to an alert that is based at least in part on the business rule. 12. The method as recited in claim 1 , further comprising outputting a reportlet to a rule engine, wherein the reportlet comprises information relevant to an event comprising the stream of operational events and additional context. | 0.547059 |
8,671,069 | 51 | 52 | 51. The computer readable medium of claim 50 containing digital information which when executed further causes the processor or processors to: store a multimedia affinity graph in one or more memories, wherein said affinity graph represents multimedia data samples as nodes and comprises edges measuring relatedness among data samples; and calculate a classification function based on at least the selected multimedia label data, wherein calculating said classification function comprises iteratively performing at least updating selected multimedia label data relating to selected multimedia data or predicting new multimedia label data for stored multimedia data. | 51. The computer readable medium of claim 50 containing digital information which when executed further causes the processor or processors to: store a multimedia affinity graph in one or more memories, wherein said affinity graph represents multimedia data samples as nodes and comprises edges measuring relatedness among data samples; and calculate a classification function based on at least the selected multimedia label data, wherein calculating said classification function comprises iteratively performing at least updating selected multimedia label data relating to selected multimedia data or predicting new multimedia label data for stored multimedia data. 52. The computer readable medium of claim 51 , wherein at least one multimedia label data sample is further normalized based on a regularization matrix calculated using members of a corresponding class and connectivity degrees of the corresponding nodes in the graph. | 0.514545 |
8,918,322 | 1 | 8 | 1. A method comprising: receiving, from a sender, a textual message generated by a spoken dialog system, the textual message having a fixed text portion and a variable text portion; selecting, based on voice characteristics of the sender and the sender speaking a particular set of lines, a speech template from a plurality of speech templates, the speech template comprising information representing characteristics of an individual's voice, wherein each speech template in the plurality of speech templates is personalized to the individual and in a distinct language from other speech templates in the plurality of speech templates; accessing pre-recorded speech from storage, the pre-recorded speech corresponding to the fixed text portion of the textual message; generating variable speech corresponding to the variable text portion of the textual message; and merging the pre-recorded speech and the variable speech in an order defined by the speech template. | 1. A method comprising: receiving, from a sender, a textual message generated by a spoken dialog system, the textual message having a fixed text portion and a variable text portion; selecting, based on voice characteristics of the sender and the sender speaking a particular set of lines, a speech template from a plurality of speech templates, the speech template comprising information representing characteristics of an individual's voice, wherein each speech template in the plurality of speech templates is personalized to the individual and in a distinct language from other speech templates in the plurality of speech templates; accessing pre-recorded speech from storage, the pre-recorded speech corresponding to the fixed text portion of the textual message; generating variable speech corresponding to the variable text portion of the textual message; and merging the pre-recorded speech and the variable speech in an order defined by the speech template. 8. The method according to claim 1 , wherein the textual message comprises one of an e-mail message and a manuscript text. | 0.75502 |
8,204,950 | 23 | 25 | 23. The machine-readable media of claim 19 , wherein the element of the webpage comprises a search box. | 23. The machine-readable media of claim 19 , wherein the element of the webpage comprises a search box. 25. The machine-readable media of claim 23 , wherein the search box includes one or more elements for controlling the search. | 0.594156 |
8,161,049 | 7 | 9 | 7. The method as described in claim 5 , further comprising visualizing the quality of the patent document, comprising: (d) assigning a color to each of said sub-spaces within said hyperspace such that at least one said sub-space has a color, which is different from colors of other said sub-spaces; and (e) assigning a color to the quality of the patent document, which is the same as the color of the sub-space to which said patent indices characterizing the patent document belong. | 7. The method as described in claim 5 , further comprising visualizing the quality of the patent document, comprising: (d) assigning a color to each of said sub-spaces within said hyperspace such that at least one said sub-space has a color, which is different from colors of other said sub-spaces; and (e) assigning a color to the quality of the patent document, which is the same as the color of the sub-space to which said patent indices characterizing the patent document belong. 9. The method as described in claim 7 , wherein: the step (a) comprises introducing two or three patent indices; and the step (d) comprises: (i) selecting one of said sub-spaces; (ii) selecting a patent document whose patent indices belong to the selected sub-space; (iii) assigning a color to the selected sub-space according to a color model, having respectively two or three input components whose mixture produces said color, wherein values of the components of the color model are equal to the respective values of patent indices. | 0.5 |
9,966,063 | 8 | 11 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: selecting, based on a microphone type and a current location of a speaker, a user profile from a plurality of user profiles, wherein the user profile is associated with the speaker; and performing, via a processor, speech recognition on speech received from the speaker using the user profile. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: selecting, based on a microphone type and a current location of a speaker, a user profile from a plurality of user profiles, wherein the user profile is associated with the speaker; and performing, via a processor, speech recognition on speech received from the speaker using the user profile. 11. The system of claim 8 , wherein the selecting of the user profile is further based on a recipient profile associated with a recipient of the speech. | 0.76324 |
8,346,724 | 1 | 2 | 1. A method, comprising: employing a processor to carry out the following acts: receiving an attribute value, the attribute value being measured via a sensor or derived from one or more values received from one or more sensors; processing the received attribute value; identifying attribute value requests related to the received attribute value that meet predetermined criteria which cause the received attribute value to be pushed to one or more clients; when one or more requests are identified and multiple instances of the attribute value are available, mediating the available multiple instances of the attribute value to produce a mediated attribute value and additional information associated therewith; pushing one of the received attribute value or a mediated value; and processing the additional information, the additional information including at least one of uncertainty or accuracy information, a timestamp of when the value was created or supplied or was most accurate, an indication that the value is a constant, indications of restrictions on whether the availability of the attribute instance or of the particular value is available to a specific client, data type, units, a format version, a name, or generic attribute property supplied by a client, history information, an indication of the supplier of the attribute, an indication of equivalent attributes, indications of clients that have registered for the attribute or consumed values for the attribute, descriptions of clients in order to track statistics, information to be used to evaluate characterization module efficiency or to facilitate process optimization, an indication of a verification of accuracy, a consumer rating or reputation based on input from a set of clients, a cost to use the value, future availability of the attribute value, or a version of the attribute, said processing the additional information comprises: when a time stamp is received, associating a time stamp to the attribute value; when accuracy information is received, associating the accuracy information to the attribute value; when accuracy decay information is received, associated the accuracy decay information to the attribute value; when a constant attribute value is received, conveying that the received attribute value is a constant; and when information associated with clients that are to have access to the received attribute value, associating the information with the received attribute value to restrict access thereof to the intended clients. | 1. A method, comprising: employing a processor to carry out the following acts: receiving an attribute value, the attribute value being measured via a sensor or derived from one or more values received from one or more sensors; processing the received attribute value; identifying attribute value requests related to the received attribute value that meet predetermined criteria which cause the received attribute value to be pushed to one or more clients; when one or more requests are identified and multiple instances of the attribute value are available, mediating the available multiple instances of the attribute value to produce a mediated attribute value and additional information associated therewith; pushing one of the received attribute value or a mediated value; and processing the additional information, the additional information including at least one of uncertainty or accuracy information, a timestamp of when the value was created or supplied or was most accurate, an indication that the value is a constant, indications of restrictions on whether the availability of the attribute instance or of the particular value is available to a specific client, data type, units, a format version, a name, or generic attribute property supplied by a client, history information, an indication of the supplier of the attribute, an indication of equivalent attributes, indications of clients that have registered for the attribute or consumed values for the attribute, descriptions of clients in order to track statistics, information to be used to evaluate characterization module efficiency or to facilitate process optimization, an indication of a verification of accuracy, a consumer rating or reputation based on input from a set of clients, a cost to use the value, future availability of the attribute value, or a version of the attribute, said processing the additional information comprises: when a time stamp is received, associating a time stamp to the attribute value; when accuracy information is received, associating the accuracy information to the attribute value; when accuracy decay information is received, associated the accuracy decay information to the attribute value; when a constant attribute value is received, conveying that the received attribute value is a constant; and when information associated with clients that are to have access to the received attribute value, associating the information with the received attribute value to restrict access thereof to the intended clients. 2. The method of claim 1 , further comprising: receiving an attribute value request, wherein the request specifies one or more criteria for the value; identifying one or more attribute instances that match the one or more criteria; pulling current values for the identified one or more attribute instances from a source of attribute values; determining if an attribute value is received, and processing the attribute value when received; and determining whether multiple attribute values are available for the attribute instances that match the one or more criteria, and mediating the multiple values when available. | 0.5 |
10,061,849 | 4 | 5 | 4. The method of claim 3 , further comprising: associating the re-arranged arrangement with a particular user; and associating the particular user with other arrangements associated with other users based on similar attributes in the one or more media object identifiers of the particular user and other media object identifiers associated with the other users. | 4. The method of claim 3 , further comprising: associating the re-arranged arrangement with a particular user; and associating the particular user with other arrangements associated with other users based on similar attributes in the one or more media object identifiers of the particular user and other media object identifiers associated with the other users. 5. The method of claim 4 , further comprising: enabling the particular user to view the other arrangements associated with the other users. | 0.5 |
8,805,684 | 7 | 8 | 7. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a user device, cause the user device to perform operations comprising: performing automatic speech recognition (ASR) on received utterances, wherein performing the ASR includes: generating feature vectors based on the utterances, updating the feature vectors based on feature-space speaker adaptation parameters, transcribing the utterances to text strings, wherein the transcriptions are based at least in part on an acoustic model and the updated feature vectors, and updating the feature-space speaker adaptation parameters based on the feature vectors; transmitting a representation of at least some of the utterances to a computing device for development of an updated acoustic model; after transmitting the representation, receiving the updated acoustic model from the computing device, wherein the updated acoustic model is based on the representation; and replacing, by the user device, the acoustic model with the updated acoustic model, wherein the feature-space speaker adaptation parameters are updated more frequently than the acoustic model is updated, and wherein the acoustic model is updated when the computing device has received a threshold extent of the representations from the user device. | 7. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a user device, cause the user device to perform operations comprising: performing automatic speech recognition (ASR) on received utterances, wherein performing the ASR includes: generating feature vectors based on the utterances, updating the feature vectors based on feature-space speaker adaptation parameters, transcribing the utterances to text strings, wherein the transcriptions are based at least in part on an acoustic model and the updated feature vectors, and updating the feature-space speaker adaptation parameters based on the feature vectors; transmitting a representation of at least some of the utterances to a computing device for development of an updated acoustic model; after transmitting the representation, receiving the updated acoustic model from the computing device, wherein the updated acoustic model is based on the representation; and replacing, by the user device, the acoustic model with the updated acoustic model, wherein the feature-space speaker adaptation parameters are updated more frequently than the acoustic model is updated, and wherein the acoustic model is updated when the computing device has received a threshold extent of the representations from the user device. 8. The article of manufacture of claim 7 , wherein the operations further comprise: receiving new feature-space speaker adaptation parameters; and replacing the updated feature-space speaker adaptation parameters with the new feature-space speaker adaptation parameters. | 0.5 |
8,359,292 | 1 | 5 | 1. A process of organizing program performance data in semantic groups, the performance data including multiple samples, each of the multiple samples having at least one name and at least one associated cost, the process comprising the steps of: submitting a grouping expression to a performance analysis tool, the grouping expression specifying, in a transformation syntax language which supports pattern-matching, a pattern and a replacement for grouping multiple performance data samples, each of the performance data samples having a stack of names which represent nodes located in a directed acyclic graph (DAG) in a computer-readable memory, each of the nodes having an associated cost; and getting from the performance analysis tool a cost accounting created by execution of instructions by a processor in response to the submitting step, the cost accounting showing names of the performance data samples and associated attributed costs, all of the names being consistent with the grouping expression. | 1. A process of organizing program performance data in semantic groups, the performance data including multiple samples, each of the multiple samples having at least one name and at least one associated cost, the process comprising the steps of: submitting a grouping expression to a performance analysis tool, the grouping expression specifying, in a transformation syntax language which supports pattern-matching, a pattern and a replacement for grouping multiple performance data samples, each of the performance data samples having a stack of names which represent nodes located in a directed acyclic graph (DAG) in a computer-readable memory, each of the nodes having an associated cost; and getting from the performance analysis tool a cost accounting created by execution of instructions by a processor in response to the submitting step, the cost accounting showing names of the performance data samples and associated attributed costs, all of the names being consistent with the grouping expression. 5. The process of claim 1 , further comprising drilling down into a group shown in the cost accounting and then obtaining a cost accounting result specific to samples chosen by said drilling down. | 0.589958 |
9,031,897 | 5 | 6 | 5. The method of claim 4 , wherein a first class of the plurality of classes is an accept class, and wherein the desired performance characteristics comprise a desired rate for falsely classifying inputs as belonging to the accept class by the classification model. | 5. The method of claim 4 , wherein a first class of the plurality of classes is an accept class, and wherein the desired performance characteristics comprise a desired rate for falsely classifying inputs as belonging to the accept class by the classification model. 6. The method of claim 5 , wherein a second class of the plurality of classes is a reject class, and wherein the desired performance characteristics further comprise a desired rate for falsely classifying inputs as belonging to the reject class by the classification model. | 0.5 |
8,335,679 | 1 | 4 | 1. A method for local computer-aided translation using remotely-generated translation predictions, the method comprising the steps of: (a) receiving, by a remote translation server, a request for a translation of a document; (b) translating, by the remote translation server, a first portion of the document; (c) receiving, by a first one of a plurality of local machines, the translation of the first portion of the document; (d) receiving, by the first one local machine, a modification to the translated first portion of the document, and storing the modification to the translated first portion of the document in a local cache; (e) transmitting, by the first one local machine, the modification to the translated first portion of the document; (f) identifying, by the remote translation server, the modification to the translated first portion of the document as useful in translating a second portion of the document, prior to receiving the request to translate a second portion of the document; (g) generating, by the remote translation server, a translation of the second portion of the document using the modification to the translated first portion of the document, responsive to the identification of the utility of the modification to the first portion of the document in the translation of the second portion of the document; and (h) transmitting, by the remote translation server to the first one local machine, the translation of the second portion of the document. | 1. A method for local computer-aided translation using remotely-generated translation predictions, the method comprising the steps of: (a) receiving, by a remote translation server, a request for a translation of a document; (b) translating, by the remote translation server, a first portion of the document; (c) receiving, by a first one of a plurality of local machines, the translation of the first portion of the document; (d) receiving, by the first one local machine, a modification to the translated first portion of the document, and storing the modification to the translated first portion of the document in a local cache; (e) transmitting, by the first one local machine, the modification to the translated first portion of the document; (f) identifying, by the remote translation server, the modification to the translated first portion of the document as useful in translating a second portion of the document, prior to receiving the request to translate a second portion of the document; (g) generating, by the remote translation server, a translation of the second portion of the document using the modification to the translated first portion of the document, responsive to the identification of the utility of the modification to the first portion of the document in the translation of the second portion of the document; and (h) transmitting, by the remote translation server to the first one local machine, the translation of the second portion of the document. 4. The method of claim 1 , wherein step (c) further comprises determining whether an updated version of the translation makes the received translation obsolete. | 0.5 |
7,644,360 | 1 | 7 | 1. A system for displaying patent claims, the system comprising: at least one input device in communication with a computer and at least one output device, wherein at least one user is capable of inputting information via the at least one input device to the at least one computer and viewing information on the at least one output device, and wherein the at least one computer is capable of storing, modifying, outputting, and retrieving information in communication with the at least one input device and at least one output device; and software installed and capable of running on the at least one computer for automatically importing patent claims based upon the user inputted information, parsing the patent claims hierarchically, generating a hierarchical claims diagram comprising graphical claim structure and textual claim content associated with each patent claim, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim, and outputting a viewable diagram of the parsed claims wherein, for each patent claim, the graphical claim structure fully includes the textual claim content; wherein the claims diagram shows at least part of a patent claims series in an interactive format that is operable to dynamically expand and compress the at least part of a patent claims series, including both the graphical claim structure and the fully included textual claim content, according to the hierarchy of the at least part of a patent claims series; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according to the hierarchy of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. | 1. A system for displaying patent claims, the system comprising: at least one input device in communication with a computer and at least one output device, wherein at least one user is capable of inputting information via the at least one input device to the at least one computer and viewing information on the at least one output device, and wherein the at least one computer is capable of storing, modifying, outputting, and retrieving information in communication with the at least one input device and at least one output device; and software installed and capable of running on the at least one computer for automatically importing patent claims based upon the user inputted information, parsing the patent claims hierarchically, generating a hierarchical claims diagram comprising graphical claim structure and textual claim content associated with each patent claim, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim, and outputting a viewable diagram of the parsed claims wherein, for each patent claim, the graphical claim structure fully includes the textual claim content; wherein the claims diagram shows at least part of a patent claims series in an interactive format that is operable to dynamically expand and compress the at least part of a patent claims series, including both the graphical claim structure and the fully included textual claim content, according to the hierarchy of the at least part of a patent claims series; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim, and at least one line directly connecting the outlines to each other according to the hierarchy of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. 7. The system of claim 1 , wherein the imported claims are an entire patent's claims. | 0.673077 |
8,356,087 | 13 | 21 | 13. A method, comprising the steps of: requesting, through a service call, creation of a virtual private network (VPN) through a VPN client gateway and a VPN server gateway; receiving, in response to the service call, a generic gateway configuration document applicable to the VPN client gateway; and translating the generic gateway configuration document to a device-specific gateway configuration document. | 13. A method, comprising the steps of: requesting, through a service call, creation of a virtual private network (VPN) through a VPN client gateway and a VPN server gateway; receiving, in response to the service call, a generic gateway configuration document applicable to the VPN client gateway; and translating the generic gateway configuration document to a device-specific gateway configuration document. 21. The method of claim 13 , wherein the translating applies a device-specific translation table to the generic gateway configuration document to produce the device-specific gateway configuration document. | 0.5 |
10,091,330 | 10 | 11 | 10. A computer-implemented method for facilitating scheduling of interests in a content centric network, the method comprising: determining, by a scheduler component, network properties associated with name prefixes of interests transmitted by a plurality of local applications, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, and wherein a name prefix includes one or more contiguous name components; generating a first interest which indicates a command to set a window size for a transport stack associated with a respective local application based on the network properties; allocating a predetermined number of tokens to the transport stack based on a name prefix and a priority or a weight assigned to the transport stack; and transmitting the first interest to a component associated with the transport stack, which causes the component to set the window size for the transport stack, thereby facilitating scheduling of interests based on the network properties. | 10. A computer-implemented method for facilitating scheduling of interests in a content centric network, the method comprising: determining, by a scheduler component, network properties associated with name prefixes of interests transmitted by a plurality of local applications, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, and wherein a name prefix includes one or more contiguous name components; generating a first interest which indicates a command to set a window size for a transport stack associated with a respective local application based on the network properties; allocating a predetermined number of tokens to the transport stack based on a name prefix and a priority or a weight assigned to the transport stack; and transmitting the first interest to a component associated with the transport stack, which causes the component to set the window size for the transport stack, thereby facilitating scheduling of interests based on the network properties. 11. The method of claim 10 , wherein the network properties are further associated with content objects received by the local applications in response to the transmitted interests, and wherein the network properties are one or more of: a round trip time that begins when an interest is transmitted and ends when a corresponding content object is received; an estimate of the round trip time based on round trip times for transmitted interests and corresponding received content objects based on a predetermined amount of lime; a total number of the transmitted interests; a number of the transmitted interests based on the predetermined amount of time; a changing rate of the transmitted interests and the corresponding received content objects based on the predetermined amount of time; a total number of interest return messages received, wherein an interest return message is received in response to an interest and is identified based on a code indicated in the message; a number of the interest return messages received based on the predetermined amount of time; a number of the transmitted interests for which a corresponding content object is not received based on the predetermined amount of time; a number of the transmitted interests that time out based on the predetermined amount of time; a number of the transmitted interests which are retransmitted based on the predetermined amount of time; and a number of retransmitted interests that time out based on the predetermined amount of time. | 0.5 |
8,610,723 | 11 | 13 | 11. A processor-implemented method for modeling a pose of a hand of a user, comprising: obtaining depth pixels of the hand in one or more frames; processing the depth pixels of the one or more frames to identify articulated portions of the hand; accessing a model of the articulated portions of the hand, the articulated portions of the hand of the model comprising a palm and fingers, including finger segments; matching the articulated portions of the hand of the model to the identified articulated portions of the hand of the depth pixels of the one or more frames, to provide an initial match; evaluating an extent to which distance constraints are violated in the initial match by at least one of the fingers, the distance constraints comprise constraints on distances between finger segments of the at least one of the fingers; rasterizing the model to provide depth pixels of the model; comparing the depth pixels of the at least one of the fingers to the depth pixels of the one or more frames to identify, from among the depth pixels of the one or more frames, non-overlapping depth pixels of the one or more frames which are not overlapping in at least one comparison plane with the depth pixels of the at least one of the fingers of the model; and adjusting the model: (a) in an attempt to satisfy the distance constraints, including adjusting a length of at least one finger segments of at least one of the fingers of the model based on the extent to which the distance constraints are violated by the at least one of the fingers, and (b) based on the comparing, to cause the model to more closely match the non-overlapping depth pixels of the one or more frames, by increasing a width of the at least one of the finger segments of the at least one of the fingers of the model. | 11. A processor-implemented method for modeling a pose of a hand of a user, comprising: obtaining depth pixels of the hand in one or more frames; processing the depth pixels of the one or more frames to identify articulated portions of the hand; accessing a model of the articulated portions of the hand, the articulated portions of the hand of the model comprising a palm and fingers, including finger segments; matching the articulated portions of the hand of the model to the identified articulated portions of the hand of the depth pixels of the one or more frames, to provide an initial match; evaluating an extent to which distance constraints are violated in the initial match by at least one of the fingers, the distance constraints comprise constraints on distances between finger segments of the at least one of the fingers; rasterizing the model to provide depth pixels of the model; comparing the depth pixels of the at least one of the fingers to the depth pixels of the one or more frames to identify, from among the depth pixels of the one or more frames, non-overlapping depth pixels of the one or more frames which are not overlapping in at least one comparison plane with the depth pixels of the at least one of the fingers of the model; and adjusting the model: (a) in an attempt to satisfy the distance constraints, including adjusting a length of at least one finger segments of at least one of the fingers of the model based on the extent to which the distance constraints are violated by the at least one of the fingers, and (b) based on the comparing, to cause the model to more closely match the non-overlapping depth pixels of the one or more frames, by increasing a width of the at least one of the finger segments of the at least one of the fingers of the model. 13. The processor-implemented method of claim 11 , further comprising: comparing the depth pixels of at least one of the articulated portions of the hand, other than the at least one of the fingers, to the depth pixels of the one or more frames to identify, from among the depth pixels of the one or more frames, non-overlapping depth pixels of the at least one of the articulated portions of the hand of the model which are not overlapping in the at least one comparison plane with the depth pixels of the one or more frames; and adjusting the model based on the comparing of the depth pixels of the at least one of the articulated portions of the hand, other than the at least one of the fingers, to the depth pixels of the one or more frames, to cause the model to more closely match the depth pixels of the one or more frames, by decreasing a width of the at least one of the articulated portions of the hand of the model. | 0.5 |
7,831,635 | 9 | 10 | 9. A non-transitory computer-readable storage medium including computer readable instructions stored thereon which are executed by a processor to cause a device to perform a method to: receive an XML file, including a vendor instruction, created at a support engineer site to collect particular information at a customer site without involvement of a customer associated with the customer site; and permit a computer system, associated with the customer site, to collect information based on the vendor instruction in XML file wherein: the XML file and the instruction are created in a computer system at a support engineer first site; the XML file is posted to a client software in a computer system at a customer site via a network protocol; and the client software, having the XML file as input, automatically invokes a collection software to execute the vendor instruction in the computer system at the customer site when the XML file is posted to the client software so that the collection software collects the particular information at the customer site; wherein the collection software collects the particular information identified by the vendor instruction in the XML file; and the client software transmits the particular information, prior to analysis of the particular information, from the customer site to the support engineer site for analysis. | 9. A non-transitory computer-readable storage medium including computer readable instructions stored thereon which are executed by a processor to cause a device to perform a method to: receive an XML file, including a vendor instruction, created at a support engineer site to collect particular information at a customer site without involvement of a customer associated with the customer site; and permit a computer system, associated with the customer site, to collect information based on the vendor instruction in XML file wherein: the XML file and the instruction are created in a computer system at a support engineer first site; the XML file is posted to a client software in a computer system at a customer site via a network protocol; and the client software, having the XML file as input, automatically invokes a collection software to execute the vendor instruction in the computer system at the customer site when the XML file is posted to the client software so that the collection software collects the particular information at the customer site; wherein the collection software collects the particular information identified by the vendor instruction in the XML file; and the client software transmits the particular information, prior to analysis of the particular information, from the customer site to the support engineer site for analysis. 10. The medium of claim 9 wherein the network protocol is an HTTP, a Java RMI, a CORBA, a DCOM, a DCE. | 0.58871 |
10,069,857 | 1 | 19 | 1. A method, comprising: extracting a set of accessed domain names from a set of events stored in a field-searchable data store; identifying a respective registration time for each accessed domain name in the set of accessed domain names, wherein the respective registration time is indicative of when the accessed domain name was registered with a registrar; identifying a subset of accessed domain names in the set of accessed domain names that have a respective registration time that meets a first criterion; determining, for each accessed domain name in the subset of accessed domain names, an associated access count corresponding to how many times the set of events indicates that the accessed domain name was accessed; performing an action for each accessed domain name in the subset of accessed domain names that has an associated access count that meets a second criterion according to one or more rules associated with the accessed domain name, wherein the one or more rules include causing an alert to be generated and transmitted that identifies the accessed domain name and that the accessed domain name was accessed; wherein the method is performed by one or more computing devices. | 1. A method, comprising: extracting a set of accessed domain names from a set of events stored in a field-searchable data store; identifying a respective registration time for each accessed domain name in the set of accessed domain names, wherein the respective registration time is indicative of when the accessed domain name was registered with a registrar; identifying a subset of accessed domain names in the set of accessed domain names that have a respective registration time that meets a first criterion; determining, for each accessed domain name in the subset of accessed domain names, an associated access count corresponding to how many times the set of events indicates that the accessed domain name was accessed; performing an action for each accessed domain name in the subset of accessed domain names that has an associated access count that meets a second criterion according to one or more rules associated with the accessed domain name, wherein the one or more rules include causing an alert to be generated and transmitted that identifies the accessed domain name and that the accessed domain name was accessed; wherein the method is performed by one or more computing devices. 19. The method of claim 1 , wherein the one or more rules include blocking access to a webpage. | 0.824074 |
9,405,773 | 1 | 14 | 1. A computer implemented method comprising: receiving a query comprising a query image that is sent via a user interface at a client machine operating over a wireless communication channel; responsive to receiving the query image, searching a database and obtaining from the database a set of images that are similar to the query image, the searching a database and obtaining a set of images that are similar to the query image comprising a two-pass search, a first pass resulting in a plurality of images that are similar to the query image and ranking the plurality of images that are similar to the query image to form a similarity score, and a second pass comprising ranking fewer than all of the resulting plurality of images from the first pass against pre-computed digests of image-based listings comprising textual information, wherein the ranking of fewer than all of the resulting plurality of images is performed using a best match procedure that comprises weighting the resulting plurality of images by color similarity, by edge similarity, and by the similarity score; providing, over the wireless communication channel for display at the user interface at the client machine, results of the searching, the results comprising image members of the obtained set of images that are similar to the query image; detecting a request, sent via the user interface at the client machine, for a similarity search for more images similar to one of the image members of the set of images displayed at the user interface at the client machine; responsive to detecting the request sent via the user interface at the client machine for the similarity search, searching for more images similar to one of the image members of the set of images displayed at the user interface at the client machine, searching the database and obtaining from the database the more images similar to the one of the image members of the set of images; and responsive to the searching the database and the obtaining from the database more images similar to the one of the image members of the set of images, providing, over the wireless communication channel for display at the user interface at the client machine, at least some of the obtained more images similar to the one of the image members of the set of images. | 1. A computer implemented method comprising: receiving a query comprising a query image that is sent via a user interface at a client machine operating over a wireless communication channel; responsive to receiving the query image, searching a database and obtaining from the database a set of images that are similar to the query image, the searching a database and obtaining a set of images that are similar to the query image comprising a two-pass search, a first pass resulting in a plurality of images that are similar to the query image and ranking the plurality of images that are similar to the query image to form a similarity score, and a second pass comprising ranking fewer than all of the resulting plurality of images from the first pass against pre-computed digests of image-based listings comprising textual information, wherein the ranking of fewer than all of the resulting plurality of images is performed using a best match procedure that comprises weighting the resulting plurality of images by color similarity, by edge similarity, and by the similarity score; providing, over the wireless communication channel for display at the user interface at the client machine, results of the searching, the results comprising image members of the obtained set of images that are similar to the query image; detecting a request, sent via the user interface at the client machine, for a similarity search for more images similar to one of the image members of the set of images displayed at the user interface at the client machine; responsive to detecting the request sent via the user interface at the client machine for the similarity search, searching for more images similar to one of the image members of the set of images displayed at the user interface at the client machine, searching the database and obtaining from the database the more images similar to the one of the image members of the set of images; and responsive to the searching the database and the obtaining from the database more images similar to the one of the image members of the set of images, providing, over the wireless communication channel for display at the user interface at the client machine, at least some of the obtained more images similar to the one of the image members of the set of images. 14. The method of claim 1 wherein the displayed results comprising image members of the obtained set of images similar to the query image comprise selectable icons that, when selected, comprise the request by the user at the client machine for a similarity search for more images similar to one of the image members of the set of images. | 0.548257 |
7,672,951 | 1 | 5 | 1. A method for classifying content, comprising: providing a taxonomy containing facets; associating different intra-document classifiers with the facets in the taxonomy, the different intra-document classifiers defining different separate sections or sub-sections of content within each document that are each separately classified; receiving, at a computer server, a query; retrieving, by the computer server, documents responsive to the query; selecting, by the computer server, different ones of the facets for classifying the retrieved documents; identifying, by the computer server, the intra-document classifiers associated with the selected facets; identifying, by the computer server, different individual sections or subsections within the individual retrieved documents corresponding with the identified intra-document classifiers associated with the selected facets; identifying, by the computer server, any of the identified individual sections or subsections within the individual retrieved documents corresponding with the identified intra-document classifiers that contain similar text or concepts as text or concepts associated with the query and that also have similar text or concepts as text or concepts associated with the selected facets; providing, by the computer server, any of the individual retrieved documents containing the identified individual sections or subsections as answers to the query; and wherein a first portion less than all of a particular one of the individual retrieved documents is identified as being one of the identified individual sections or subsections that contains similar text or concepts as text or concepts associated with the query, wherein a second portion less than all of the particular document is not identified being one of the identified individual sections or subsections that contains similar text or concepts as text or concepts associated with the query, and wherein the particular document is provided as at least a part of the answers. | 1. A method for classifying content, comprising: providing a taxonomy containing facets; associating different intra-document classifiers with the facets in the taxonomy, the different intra-document classifiers defining different separate sections or sub-sections of content within each document that are each separately classified; receiving, at a computer server, a query; retrieving, by the computer server, documents responsive to the query; selecting, by the computer server, different ones of the facets for classifying the retrieved documents; identifying, by the computer server, the intra-document classifiers associated with the selected facets; identifying, by the computer server, different individual sections or subsections within the individual retrieved documents corresponding with the identified intra-document classifiers associated with the selected facets; identifying, by the computer server, any of the identified individual sections or subsections within the individual retrieved documents corresponding with the identified intra-document classifiers that contain similar text or concepts as text or concepts associated with the query and that also have similar text or concepts as text or concepts associated with the selected facets; providing, by the computer server, any of the individual retrieved documents containing the identified individual sections or subsections as answers to the query; and wherein a first portion less than all of a particular one of the individual retrieved documents is identified as being one of the identified individual sections or subsections that contains similar text or concepts as text or concepts associated with the query, wherein a second portion less than all of the particular document is not identified being one of the identified individual sections or subsections that contains similar text or concepts as text or concepts associated with the query, and wherein the particular document is provided as at least a part of the answers. 5. The method according to claim 1 including using a matching language in the intra-document classifiers to identify the text or concepts associated with the selected facets. | 0.894032 |
8,416,454 | 10 | 12 | 10. A method of producing documents comprising: storing personalized digital alphanumeric characters in a digital memory accessible by a computer, wherein each of the personalized digital alphanumeric characters is represented using spline fitting functions; opening a preformatted document stored on the computer; entering text in the preformatted document; transcribing the text entered in the preformatted document into the personalized digital characters to generate a personalized document; and printing the personalized document. | 10. A method of producing documents comprising: storing personalized digital alphanumeric characters in a digital memory accessible by a computer, wherein each of the personalized digital alphanumeric characters is represented using spline fitting functions; opening a preformatted document stored on the computer; entering text in the preformatted document; transcribing the text entered in the preformatted document into the personalized digital characters to generate a personalized document; and printing the personalized document. 12. The method of claim 10 wherein the step of printing comprises printing the transcribed personalized digital characters on a first side of the personalized document and printing a stored digital image on a second side of the personalized document. | 0.616564 |
9,367,540 | 9 | 12 | 9. A machine-readable, non-transitory and tangible medium having data recorded thereon for providing translated web content, the medium, when read by the machine, causes the machine to perform the following: receiving a request, via a public network connection, from an online user for content in a second language translated from content in a first language; obtaining in response to the request, via a public network connection, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining, with respect to each of the plurality of translatable components, whether there is a corresponding translated component previously stored; generating, if a number of translatable components that have corresponding translated components exceeds a threshold, the content in the second language by replacing each of the number of translatable components with a corresponding translated component; automatically placing a representation of the content in the first language onto a translation queue, if the number of translatable components that have corresponding translated components does not exceed the threshold, for human translation of the content in the first language represented by the representation into the second language; and sending the content in the second language generated in the generating step to the online user as a response to the request. | 9. A machine-readable, non-transitory and tangible medium having data recorded thereon for providing translated web content, the medium, when read by the machine, causes the machine to perform the following: receiving a request, via a public network connection, from an online user for content in a second language translated from content in a first language; obtaining in response to the request, via a public network connection, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining, with respect to each of the plurality of translatable components, whether there is a corresponding translated component previously stored; generating, if a number of translatable components that have corresponding translated components exceeds a threshold, the content in the second language by replacing each of the number of translatable components with a corresponding translated component; automatically placing a representation of the content in the first language onto a translation queue, if the number of translatable components that have corresponding translated components does not exceed the threshold, for human translation of the content in the first language represented by the representation into the second language; and sending the content in the second language generated in the generating step to the online user as a response to the request. 12. The medium of claim 9 , wherein the representation of the content in the first language includes a Universal Resource Locator (URL). | 0.752727 |
7,577,718 | 9 | 15 | 9. A computer-readable medium containing computer-executable instructions that when executed by a processor of a computer system cause the computer system to perform a method for adaptively disseminating contextually relevant information based on user interests of a user, the method comprising: identifying user interests from clusters of terms extracted from one or more user emails, each cluster of terms corresponding to a set of similar terms; identifying a user event; identifying topics based on the user event; for each topic, identifying clusters of terms for the topic; for each of the identified clusters of terms, identifying key terms in the cluster by, selecting a term in the cluster, calculating a type weight for the selected term, calculating a relevance weight for the selected term, calculating an overall weight for the selected term based at least in part on the calculated type and relevance weights, and if the overall weight exceeds a predetermined threshold, identifying the selected term as a key term; and generating a query based on the key terms; obtaining search results by executing the queries associated with each topic against information sources; ranking the search results; and rendering the ranked search results to the user. | 9. A computer-readable medium containing computer-executable instructions that when executed by a processor of a computer system cause the computer system to perform a method for adaptively disseminating contextually relevant information based on user interests of a user, the method comprising: identifying user interests from clusters of terms extracted from one or more user emails, each cluster of terms corresponding to a set of similar terms; identifying a user event; identifying topics based on the user event; for each topic, identifying clusters of terms for the topic; for each of the identified clusters of terms, identifying key terms in the cluster by, selecting a term in the cluster, calculating a type weight for the selected term, calculating a relevance weight for the selected term, calculating an overall weight for the selected term based at least in part on the calculated type and relevance weights, and if the overall weight exceeds a predetermined threshold, identifying the selected term as a key term; and generating a query based on the key terms; obtaining search results by executing the queries associated with each topic against information sources; ranking the search results; and rendering the ranked search results to the user. 15. The computer-readable medium of claim 9 , wherein the search results are ranked based in part on static weights corresponding to the search results. | 0.831858 |
9,363,634 | 21 | 29 | 21. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a user context of a user, wherein the user context specifies a location of a user device being used by the user; obtaining user activity data organized into sessions, each session being data representing a plurality of user activities performed by a distinct user during a respective time period, the sessions including sessions for multiple users; obtaining matching sessions for the received user context, each matching session being a distinct session that includes data representing activities performed by respective users having a user context matching the received user context during a time period represented by the matching session; obtaining general sessions, each general session including data representing activities performed by respective users during a time period represented by the general session; determining, from the obtained matching sessions and the obtained general sessions, one or more context-relevant activities that occur in the matching sessions more frequently than the one or more context-relevant activities occur in the general sessions, the one or more context-relevant activities being activities performed by users matching the received user context more frequently than by users in general; and providing information related to the one or more context-relevant activities in response to receiving the user context. | 21. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a user context of a user, wherein the user context specifies a location of a user device being used by the user; obtaining user activity data organized into sessions, each session being data representing a plurality of user activities performed by a distinct user during a respective time period, the sessions including sessions for multiple users; obtaining matching sessions for the received user context, each matching session being a distinct session that includes data representing activities performed by respective users having a user context matching the received user context during a time period represented by the matching session; obtaining general sessions, each general session including data representing activities performed by respective users during a time period represented by the general session; determining, from the obtained matching sessions and the obtained general sessions, one or more context-relevant activities that occur in the matching sessions more frequently than the one or more context-relevant activities occur in the general sessions, the one or more context-relevant activities being activities performed by users matching the received user context more frequently than by users in general; and providing information related to the one or more context-relevant activities in response to receiving the user context. 29. The computer program product of claim 21 , wherein the user context includes a home geographic location associated with the user. | 0.862603 |
8,140,549 | 9 | 11 | 9. The computer program product of claim 8 , wherein: the computer product further comprises program instructions to create an array object based upon a set of dimension objects; and the program instructions to create the filter object comprise program instructions to reference one or more elements of the array object by the filter object, wherein: the one or more elements of the filter object refer to one or more elements of the set of dimension objects; and a specification of the one or more elements of the set of dimension objects comprise a reference to the one or more elements of the array object. | 9. The computer program product of claim 8 , wherein: the computer product further comprises program instructions to create an array object based upon a set of dimension objects; and the program instructions to create the filter object comprise program instructions to reference one or more elements of the array object by the filter object, wherein: the one or more elements of the filter object refer to one or more elements of the set of dimension objects; and a specification of the one or more elements of the set of dimension objects comprise a reference to the one or more elements of the array object. 11. The computer program product of claim 9 , wherein the program instructions to create the filter object comprise program instructions to create a filter object containing one element from each dimension of the set of dimensions of the array. | 0.5 |
10,089,292 | 1 | 4 | 1. In a computing environment, a method for facilitating adding content to forms by providing field content suggestions using context determined based on form features, the method comprising: defining a plurality of form contexts, wherein the form contexts comprise a unique purpose, a circumstance, or a perspective of a representative form, and wherein each of the form contexts is defined by assigning to it a plurality of representative form features and by assigning a weighting to each of the representative form features, wherein the representative form features comprise non-text field characteristics, field labels, and other field-specific text characteristics; providing a user interface for display, the user interface displaying a form and providing editing features usable to add content to fillable fields of the form, each of the fillable fields identified by a field label; determining, by a processor, which of the plurality of form contexts to assign to a portion of the form by identifying form features found in the portion of the form, correlating the identified form features to the representative form features of each of the form contexts, and assigning to the portion of the form the form context having a highest degree of correlation, wherein the portion of the form comprises a plurality of the fillable fields of the form; identifying, by the processor and from the form context of the portion of the form, a field content suggestion for a fillable field within the portion of the form, the field content suggestion indicating content items selectable by a user to complete the fillable field; and providing, by the processor, the field content suggestion for the fillable field for display in the user interface. | 1. In a computing environment, a method for facilitating adding content to forms by providing field content suggestions using context determined based on form features, the method comprising: defining a plurality of form contexts, wherein the form contexts comprise a unique purpose, a circumstance, or a perspective of a representative form, and wherein each of the form contexts is defined by assigning to it a plurality of representative form features and by assigning a weighting to each of the representative form features, wherein the representative form features comprise non-text field characteristics, field labels, and other field-specific text characteristics; providing a user interface for display, the user interface displaying a form and providing editing features usable to add content to fillable fields of the form, each of the fillable fields identified by a field label; determining, by a processor, which of the plurality of form contexts to assign to a portion of the form by identifying form features found in the portion of the form, correlating the identified form features to the representative form features of each of the form contexts, and assigning to the portion of the form the form context having a highest degree of correlation, wherein the portion of the form comprises a plurality of the fillable fields of the form; identifying, by the processor and from the form context of the portion of the form, a field content suggestion for a fillable field within the portion of the form, the field content suggestion indicating content items selectable by a user to complete the fillable field; and providing, by the processor, the field content suggestion for the fillable field for display in the user interface. 4. The method of claim 1 , further comprising: creating a machine learning model for categorizing forms into the plurality of form contexts, the machine learning model trained using a collection of uncategorized forms; and wherein determining which of the plurality of form contexts to assign to the portion of the form is performed by applying the machine learning model to the portion of the form. | 0.620722 |
9,779,291 | 1 | 9 | 1. A computerized method for classifying images, comprising: receiving an image hierarchy; receiving a first image of interest wherein the image includes at least one feature; classifying the at least one feature of the image according to the image hierarchy; generating a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimizing the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generating at least one optimized classification of the at least one feature of the image for the first image of interest. | 1. A computerized method for classifying images, comprising: receiving an image hierarchy; receiving a first image of interest wherein the image includes at least one feature; classifying the at least one feature of the image according to the image hierarchy; generating a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimizing the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generating at least one optimized classification of the at least one feature of the image for the first image of interest. 9. The computerized method of claim 1 , wherein the Lagrange function can be evaluated using the following expression:
L ( f ,λ)= R ( f )+λ(Φ( f )−1−∈) where L(f,λ) is the Lagrange function, f is the classifier, λ is the dual variable, R(f) is the information gain, Φ(f) is the accuracy, and ∈ is an arbitrary accuracy value. | 0.524709 |
9,437,195 | 1 | 6 | 1. A system comprising: a user speech profile stored on a computer readable storage device, the speech profile containing a plurality of phonemes with user identifying characteristics for the phonemes, wherein the identifying characteristic comprise a representation of the amount of pronunciation difference for each of the plurality of phonemes from an average user; and a speech processor coupled to access the speech profile and generate a phrase containing user distinguishing phonemes based on the pronunciation difference between the user identifying characteristics for such phonemes and average user identifying characteristics, such that the phrase has discriminability from other users wherein the speech processor generates the phrase by searching for a phrase in a library that contains user distinguishing phonemes, wherein a user distinguishing phoneme is based on pronunciation of a phoneme by a user differing from the way most other users pronounce the phoneme and wherein such distinguishing phonemes have an associated score indicative of a magnitude by which such pronunciation differs and wherein the associated score is adjusted based on a difference of the pronunciation from ambient noise, resulting in a different generated phrase in the presence of the ambient noise. | 1. A system comprising: a user speech profile stored on a computer readable storage device, the speech profile containing a plurality of phonemes with user identifying characteristics for the phonemes, wherein the identifying characteristic comprise a representation of the amount of pronunciation difference for each of the plurality of phonemes from an average user; and a speech processor coupled to access the speech profile and generate a phrase containing user distinguishing phonemes based on the pronunciation difference between the user identifying characteristics for such phonemes and average user identifying characteristics, such that the phrase has discriminability from other users wherein the speech processor generates the phrase by searching for a phrase in a library that contains user distinguishing phonemes, wherein a user distinguishing phoneme is based on pronunciation of a phoneme by a user differing from the way most other users pronounce the phoneme and wherein such distinguishing phonemes have an associated score indicative of a magnitude by which such pronunciation differs and wherein the associated score is adjusted based on a difference of the pronunciation from ambient noise, resulting in a different generated phrase in the presence of the ambient noise. 6. The system of claim 1 wherein the generated phrase contains at least two instances of a user distinguishing phoneme, and wherein the associated score is an average of scores related to ambient noise and user differences in pronunciation. | 0.525692 |
8,166,054 | 1 | 2 | 1. A system for adaptively locating dynamic web page elements, said system comprising: a computer processor; an Extensible Markup Language Path Language (XPath) refiner for refining by the computer processor an XPath path expression of the web page element based on a Hypertext Markup Language (HTML) knowledge database describing an HTML tag relationship and an attribute importance; and an enhanced XPath resolving engine for searching by the computer processor an HTML Document Object Model (DOM) tree of a target web page for the web page element through the refined XPath path expression; wherein the HTML knowledge database further comprises an HTML tag relationship table and an HTML attribute importance table, wherein the HTML tag relationship table is configured for representing said relationships between HTML tags, and wherein the HTML attribute importance table is configured for representing said importance of HTML attributes relative to HTML tags; wherein the relationships between HTML tags and the importance of HTML attributes relative to HTML tags are represented by weight values; wherein the enhanced XPath resolving engine is configured to output a result set when elements are found in the HTML DOM tree according to the XPath path expression; and when no element is found, to notify the XPath refiner to further refine the XPath path expression; wherein the XPath refiner is further configured to remove tags whose relationships do not achieve a threshold based on the HTML knowledge database from the XPath path expression; wherein the XPath refiner is further configured to adjust the threshold when no element is found by the enhanced XPath resolving engine. | 1. A system for adaptively locating dynamic web page elements, said system comprising: a computer processor; an Extensible Markup Language Path Language (XPath) refiner for refining by the computer processor an XPath path expression of the web page element based on a Hypertext Markup Language (HTML) knowledge database describing an HTML tag relationship and an attribute importance; and an enhanced XPath resolving engine for searching by the computer processor an HTML Document Object Model (DOM) tree of a target web page for the web page element through the refined XPath path expression; wherein the HTML knowledge database further comprises an HTML tag relationship table and an HTML attribute importance table, wherein the HTML tag relationship table is configured for representing said relationships between HTML tags, and wherein the HTML attribute importance table is configured for representing said importance of HTML attributes relative to HTML tags; wherein the relationships between HTML tags and the importance of HTML attributes relative to HTML tags are represented by weight values; wherein the enhanced XPath resolving engine is configured to output a result set when elements are found in the HTML DOM tree according to the XPath path expression; and when no element is found, to notify the XPath refiner to further refine the XPath path expression; wherein the XPath refiner is further configured to remove tags whose relationships do not achieve a threshold based on the HTML knowledge database from the XPath path expression; wherein the XPath refiner is further configured to adjust the threshold when no element is found by the enhanced XPath resolving engine. 2. The system according to claim 1 , wherein the XPath refiner is further configured to remove attributes that do not achieve a threshold importance based on the HTML knowledge database from the XPath path expression. | 0.589015 |
9,990,359 | 1 | 9 | 1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment. | 1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment. 9. The processor-implemented method of claim 1 , further comprising creating a hierarchical relational map corresponding to at least a portion of the online discussion including the first concept, the second concept and the first relation. | 0.736784 |
9,747,276 | 9 | 13 | 9. A computer system for determining a crowd behavior, the system comprising: a memory having computer readable instructions; and a processor configured to execute the computer readable instructions, the instructions comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold. | 9. A computer system for determining a crowd behavior, the system comprising: a memory having computer readable instructions; and a processor configured to execute the computer readable instructions, the instructions comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold. 13. The computer system of claim 9 , wherein the recording points comprise a screening checkpoint, wherein the method further comprises: determining a behavior of an individual or a behavior a group of individuals of the crowd by performing the graphical text analysis on the graph; and outputting the determined individual or group behavior to trigger a security measure. | 0.5 |
9,495,559 | 8 | 9 | 8. The non-transitory computer-readable storage medium of claim 7 , wherein inserting the first user's notes into the second user's existing notes comprises inserting a reference or a pointer, within the document, to the first user's notes in the second user's existing notes. | 8. The non-transitory computer-readable storage medium of claim 7 , wherein inserting the first user's notes into the second user's existing notes comprises inserting a reference or a pointer, within the document, to the first user's notes in the second user's existing notes. 9. The non-transitory computer-readable storage medium of claim 8 , wherein notifying the second user of the availability of the shared notes comprises sending a notification message to the second user. | 0.5 |
8,078,963 | 34 | 36 | 34. A non-transitory computer readable medium storing a computer program which when executed by at least one processor places content in a document created based on a template, said computer program comprising sets of instructions for: receiving a selection of a template page comprising (i) a body layer for holding in-line content and (ii) a floating layer for holding floating content that is moveable to a location of the in-line content so that the in-line content at the location re-arranges around the floating content; adding the template page to the document, wherein the added template page comprises placeholder content in at least one of the body layer and the floating layer; displaying the template page with the placeholder content; in response to movement of a cursor over the placeholder content, displaying a message indicating to a user that the content is placeholder content that is part of the added template page and not content generated by the user. | 34. A non-transitory computer readable medium storing a computer program which when executed by at least one processor places content in a document created based on a template, said computer program comprising sets of instructions for: receiving a selection of a template page comprising (i) a body layer for holding in-line content and (ii) a floating layer for holding floating content that is moveable to a location of the in-line content so that the in-line content at the location re-arranges around the floating content; adding the template page to the document, wherein the added template page comprises placeholder content in at least one of the body layer and the floating layer; displaying the template page with the placeholder content; in response to movement of a cursor over the placeholder content, displaying a message indicating to a user that the content is placeholder content that is part of the added template page and not content generated by the user. 36. The non-transitory computer readable medium of claim 34 , wherein the placeholder content is in the body layer of the template page. | 0.514286 |
8,086,441 | 11 | 12 | 11. A non-transitory machine-accessible medium that provides instructions that, if executed by a processor, will cause the processor to perform operations comprising: receiving a string of bytes representing non-segmented text written in a non-delimited language, wherein the non-segmented text has been classified into a predetermined category; simultaneously searching for a plurality of N-grams in a single pass through the string of bytes; collecting statistical information on occurrences of the plurality of N-grams in the string of bytes; generating a model based on the statistical information, the model usable by a content filter to classify contents, defining a plurality of states based on the plurality of N-grams; constructing a finite state machine having the plurality of states, wherein the plurality of states are coupled to each other via one or more paths; and mapping each of the plurality of states to a set of zero or more of the plurality of N-grams in an output table. | 11. A non-transitory machine-accessible medium that provides instructions that, if executed by a processor, will cause the processor to perform operations comprising: receiving a string of bytes representing non-segmented text written in a non-delimited language, wherein the non-segmented text has been classified into a predetermined category; simultaneously searching for a plurality of N-grams in a single pass through the string of bytes; collecting statistical information on occurrences of the plurality of N-grams in the string of bytes; generating a model based on the statistical information, the model usable by a content filter to classify contents, defining a plurality of states based on the plurality of N-grams; constructing a finite state machine having the plurality of states, wherein the plurality of states are coupled to each other via one or more paths; and mapping each of the plurality of states to a set of zero or more of the plurality of N-grams in an output table. 12. The non-transitory machine-accessible medium of claim 11 , wherein collecting the statistical information comprises: counting a number of occurrences of each of the plurality of N-grams in the string of bytes. | 0.649671 |
10,002,189 | 7 | 10 | 7. The method of claim 1 , wherein the ontology further comprises: a plurality of links connecting nodes of the ontology with one another, each of the plurality of links representing a relation between nodes linked thereby. | 7. The method of claim 1 , wherein the ontology further comprises: a plurality of links connecting nodes of the ontology with one another, each of the plurality of links representing a relation between nodes linked thereby. 10. The method of claim 7 , wherein at least one relation among nodes comprises an indication that one of the nodes represents at least one additional search criterion associated with a concept represented by another of the nodes. | 0.5 |
8,290,822 | 1 | 10 | 1. A computer-implemented system for providing selectable attribute values for one or more products, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of a product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: create one or more attribute binary decision diagram (BDD) structures representative of the product attributes, the BDD structures including offering attribute nodes representative of product attribute values selectable by the user based on the product configuration rules, and non-offering attribute nodes representative of product attribute values not selectable by the user based on the product configuration rules; and evaluate the BDD structures and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values corresponding to the offering attribute nodes. | 1. A computer-implemented system for providing selectable attribute values for one or more products, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of a product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: create one or more attribute binary decision diagram (BDD) structures representative of the product attributes, the BDD structures including offering attribute nodes representative of product attribute values selectable by the user based on the product configuration rules, and non-offering attribute nodes representative of product attribute values not selectable by the user based on the product configuration rules; and evaluate the BDD structures and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values corresponding to the offering attribute nodes. 10. The computer-implemented system of claim 1 , wherein at least one product configuration rule of the product configuration rules has a rule type selected from a group of rule types comprising: a non-conditional rule type, wherein the non-conditional rule type comprises an action statement that is not dependent upon a conditional statement; a product conditional rule type, wherein the product conditional rule type comprises an action statement dependent upon a conditional statement comprising a product attribute value; and, a customer conditional rule type, wherein the customer conditional rule type comprises an action statement dependent upon a conditional statement comprising a customer attribute value. | 0.707038 |
8,538,960 | 1 | 2 | 1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. | 1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. 2. The one or more computer-readable storage memories of claim 1 , said aspect of relevance being based on a comparison of words in said query with attributes of people in said social graph. | 0.808468 |
8,560,317 | 7 | 8 | 7. The voice recognition apparatus according to claim 5 , further comprising a vocabulary group use frequency managing unit for dividing the plurality of words stored in the vocabulary dictionary storing unit into a plurality of vocabulary groups and calculating a use frequency of each of the vocabulary groups based on the use frequency of each of the plurality of words belonging to the vocabulary group stored in the vocabulary dictionary storing unit, a vocabulary group use frequency storing unit for storing, as vocabulary group use frequency data, the use frequency of the vocabulary group calculated by the vocabulary group use frequency managing unit so as to correspond to each of the vocabulary groups, and a threshold storing unit for storing a threshold indicating a criterion of the vocabulary group use frequency data at the time of extracting the recognition target words, wherein the vocabulary dictionary managing unit selectively performs one of operations (3) and (4) below referring to the threshold stored in the threshold storing unit and the vocabulary group use frequency data stored in the vocabulary group use frequency storing unit according to the extraction criterion information stored in the extraction criterion information storing unit: (3) for the vocabulary group whose vocabulary group use frequency data are equal to or larger than the threshold, the vocabulary dictionary managing unit extracts all the words belonging to this vocabulary group as the recognition target words regardless of the scale information, (4) for the vocabulary group whose vocabulary group use frequency data are smaller than the threshold, the vocabulary dictionary managing unit extracts the recognition target words from the words belonging to this vocabulary group based on the scale information. | 7. The voice recognition apparatus according to claim 5 , further comprising a vocabulary group use frequency managing unit for dividing the plurality of words stored in the vocabulary dictionary storing unit into a plurality of vocabulary groups and calculating a use frequency of each of the vocabulary groups based on the use frequency of each of the plurality of words belonging to the vocabulary group stored in the vocabulary dictionary storing unit, a vocabulary group use frequency storing unit for storing, as vocabulary group use frequency data, the use frequency of the vocabulary group calculated by the vocabulary group use frequency managing unit so as to correspond to each of the vocabulary groups, and a threshold storing unit for storing a threshold indicating a criterion of the vocabulary group use frequency data at the time of extracting the recognition target words, wherein the vocabulary dictionary managing unit selectively performs one of operations (3) and (4) below referring to the threshold stored in the threshold storing unit and the vocabulary group use frequency data stored in the vocabulary group use frequency storing unit according to the extraction criterion information stored in the extraction criterion information storing unit: (3) for the vocabulary group whose vocabulary group use frequency data are equal to or larger than the threshold, the vocabulary dictionary managing unit extracts all the words belonging to this vocabulary group as the recognition target words regardless of the scale information, (4) for the vocabulary group whose vocabulary group use frequency data are smaller than the threshold, the vocabulary dictionary managing unit extracts the recognition target words from the words belonging to this vocabulary group based on the scale information. 8. The voice recognition apparatus according to claim 7 , wherein the monitor control unit monitors at least one monitor target from a processing state of an operation accepted from a user, a processing state of the voice accepted from the user and a predetermined time passed from a measurement unit for measuring a time, the voice recognition apparatus further comprises a threshold managing unit for updating the threshold stored in the threshold storing unit according to the result of the monitoring by the monitor control unit, and the vocabulary dictionary managing unit selectively performs one of the operations (3) and (4) above according to the updated threshold. | 0.5 |
8,180,721 | 11 | 19 | 11. A system to validate a plurality of electronic data interchange (EDI) documents, where each EDI document is associated with at least one of a plurality of entities, comprising: a computer system having a processor, a memory, a storage device, a network interface and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: implement creation of an inventory of all rules, the inventory including a common set of rules for the plurality of entities; facilitate dynamic adjustment of the inventory of all rules based upon entity specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; facilitate determination of a profile for each of the plurality of entities where each profile indicates that entity's companion guide rules and provides pointers to select rules in the inventory of all rules that are associated with the current rule set of that entity, wherein each is stored by the storage device; check received EDI documents for validation, each checked EDI document associated with a corresponding entity, comprising: implement a runtime checker to check the storage device for a current rule set based upon the profile for the corresponding entity, where the current rule set comprises rules from the inventory of rules required by the companion guide associated with the corresponding entity; compare the received EDI document with the associated current rule set retrieved from storage; forward the received EDI document to an associated destination entity if the received EDI document matches the associated current rule set, wherein the received EDI document is validated; and return the received EDI document to the sender if the received EDI document does not match the associated current rule set, wherein the received EDI document is invalidated; and receive documents, each document associated with one of the plurality of entities, wherein the computer usable program code configured to check received EDI documents is utilized for validation of each received document. | 11. A system to validate a plurality of electronic data interchange (EDI) documents, where each EDI document is associated with at least one of a plurality of entities, comprising: a computer system having a processor, a memory, a storage device, a network interface and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: implement creation of an inventory of all rules, the inventory including a common set of rules for the plurality of entities; facilitate dynamic adjustment of the inventory of all rules based upon entity specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; facilitate determination of a profile for each of the plurality of entities where each profile indicates that entity's companion guide rules and provides pointers to select rules in the inventory of all rules that are associated with the current rule set of that entity, wherein each is stored by the storage device; check received EDI documents for validation, each checked EDI document associated with a corresponding entity, comprising: implement a runtime checker to check the storage device for a current rule set based upon the profile for the corresponding entity, where the current rule set comprises rules from the inventory of rules required by the companion guide associated with the corresponding entity; compare the received EDI document with the associated current rule set retrieved from storage; forward the received EDI document to an associated destination entity if the received EDI document matches the associated current rule set, wherein the received EDI document is validated; and return the received EDI document to the sender if the received EDI document does not match the associated current rule set, wherein the received EDI document is invalidated; and receive documents, each document associated with one of the plurality of entities, wherein the computer usable program code configured to check received EDI documents is utilized for validation of each received document. 19. The system of claim 11 , wherein the memory further stores computer usable program code executed by the processor to: create the current rule set for each of the plurality of entities the first time a corresponding companion guide profile is accessed during validating the EDI document associated with that entity, wherein the current rule set is used subsequently each additional time that the corresponding companion guide profile is accessed. | 0.638486 |
9,558,182 | 1 | 2 | 1. A computer implemented method for developing linguistic markers computed for a given plurality of matches associated with respective reference dictionaries and respective final dictionaries, the method comprising: generating an Original Term Index (OTI) by a smart term assessment subsystem (STA-SS) using a plurality of best matches across a plurality of source and target language segments and the respective reference dictionaries; generating a Best Term Index (BTI) by a smart term linguistic analytical subsystem (STLA-SS) using the plurality of best matches across the plurality of source and target language segments and the respective final dictionaries; generating a Perfect Term Index (PTI) by the STLA-SS using a plurality of final translations across the plurality of source and target language segments and the respective final dictionaries; generating a Final Term Index (FTI) by the STLA-SS using the plurality of final translations across the plurality of source and target language segments and using the respective reference dictionaries; generating a Match Term Index (MTI) by the STLA-SS using the plurality of best matches across the plurality of source and target language segments and using respective match dictionaries; and generating a Final Match Term Index (FMTI) by the STLA-SS using the plurality of final translations across the plurality of source and target language segments and using the respective match dictionaries. | 1. A computer implemented method for developing linguistic markers computed for a given plurality of matches associated with respective reference dictionaries and respective final dictionaries, the method comprising: generating an Original Term Index (OTI) by a smart term assessment subsystem (STA-SS) using a plurality of best matches across a plurality of source and target language segments and the respective reference dictionaries; generating a Best Term Index (BTI) by a smart term linguistic analytical subsystem (STLA-SS) using the plurality of best matches across the plurality of source and target language segments and the respective final dictionaries; generating a Perfect Term Index (PTI) by the STLA-SS using a plurality of final translations across the plurality of source and target language segments and the respective final dictionaries; generating a Final Term Index (FTI) by the STLA-SS using the plurality of final translations across the plurality of source and target language segments and using the respective reference dictionaries; generating a Match Term Index (MTI) by the STLA-SS using the plurality of best matches across the plurality of source and target language segments and using respective match dictionaries; and generating a Final Match Term Index (FMTI) by the STLA-SS using the plurality of final translations across the plurality of source and target language segments and using the respective match dictionaries. 2. The method set forth in claim 1 , wherein the match dictionaries is a plurality of unique words found in the plurality of matches, and the final dictionary is a plurality of unique words found in the plurality of final translations. | 0.5 |
9,195,769 | 15 | 18 | 15. The server computer of claim 14 , the method further comprising: obtaining, at the server computer, personal data from the one or more of data sources, wherein the personal data is associated with the target user in the plurality of users; storing the personal data at the server computer, wherein personal data associated with the plurality of users is stored in a user database; merging, by the server computer, the personal data from the plurality of data sources; mapping, by the server computer, the personal data from the plurality of data sources to the target user; updating the user database with the personal data and stored data associated with the target user; wherein the order of relevance of the set of entity evaluations to request is based at least in part on the personal data from the target user. | 15. The server computer of claim 14 , the method further comprising: obtaining, at the server computer, personal data from the one or more of data sources, wherein the personal data is associated with the target user in the plurality of users; storing the personal data at the server computer, wherein personal data associated with the plurality of users is stored in a user database; merging, by the server computer, the personal data from the plurality of data sources; mapping, by the server computer, the personal data from the plurality of data sources to the target user; updating the user database with the personal data and stored data associated with the target user; wherein the order of relevance of the set of entity evaluations to request is based at least in part on the personal data from the target user. 18. The server computer of claim 15 , wherein the communicating further comprises: determining a set of media objects associated with the set of entity evaluations to request; and displaying the set of media objects with the set of entity evaluations to request. | 0.5 |
8,249,351 | 14 | 16 | 14. The logical structure model creation assistance device according to claim 10 , wherein, the character string associated with each of the logical elements in the logical structure model includes a designation of the logical element and an actual expression of the logical element, and a limit condition for an attribute of the character string is established to the actual expression. | 14. The logical structure model creation assistance device according to claim 10 , wherein, the character string associated with each of the logical elements in the logical structure model includes a designation of the logical element and an actual expression of the logical element, and a limit condition for an attribute of the character string is established to the actual expression. 16. The logical structure model creation assistance device according to claim 14 , wherein, the logical structure similarity estimation unit determines, for the several selected logical elements, according to the priority, the degree of similarity between the designation of the logical element and/or the actual expression of the logical element associated with a logical element at an upper level, a logical element at a lower level or a logical element at the same level in the hierarchical structure of the reference logical element and the extracted character strings in the input image, and estimates, based on the result of the determination, the degree of similarity between the logical structure stored in the logical structure model, and the logical structure among the extracted character strings in the input image. | 0.5 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.