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5,473,741 | 1 | 6 | 1. A method for determining an estimated amount of time required to complete raster image processing of an actual page description language file having a predetermined size, without performing actual raster image processing of the actual page description language file, comprising the steps of: (a) providing a test data file that includes a first non-rotated, non-scaled image file, a rotated, non-scaled image file, a non-rotated, scaled image file, each of these files having substantially the same file size, and a second non-rotated, non-scaled image file of a different file size; (b) performing raster image processing on each of said above files, performing raster image processing on each of two graduated fills of two different areas, performing raster image processing on each of two patterned fills of two different areas, performing raster image processing on each of two radial fills of two different areas, and performing raster image processing on each of two page description language files of two different file sizes, thereby creating a timing data profile that includes performance information in units of processing time per file size for each type of said above files, including image files and page description language files, and in units of processing time per unit area for each of said above types of fills, including a graduated fill, a patterned fill, and a radial fill; (c) examining said actual page description language file by determining, for each image of said actual page description language file, its size, whether it is scaled or non-scaled, and whether it is rotated or non-rotated, and determining the area for each computer generated graduated fill, patterned fill, and radial fill; (d) determining the total combined size of all image files of the actual page description language file and multiplying said total combined size by said performance information of the timing data profile in processing time per file size, and determining the total combined area of all computer generated fills by respective type and multiplying said total combined area by said performance information of the timing data profile in processing time per unit area by respective type, thereby creating an estimated first time period; (e) measuring the size of said actual page description language file and multiplying said actual page description language file size by said performance information the timing data profile in said page description language file processing time per file size, thereby creating an estimated second time period; and (f) combining said first time period and said second time period to create an estimate of the total time required to complete raster image processing. | 1. A method for determining an estimated amount of time required to complete raster image processing of an actual page description language file having a predetermined size, without performing actual raster image processing of the actual page description language file, comprising the steps of: (a) providing a test data file that includes a first non-rotated, non-scaled image file, a rotated, non-scaled image file, a non-rotated, scaled image file, each of these files having substantially the same file size, and a second non-rotated, non-scaled image file of a different file size; (b) performing raster image processing on each of said above files, performing raster image processing on each of two graduated fills of two different areas, performing raster image processing on each of two patterned fills of two different areas, performing raster image processing on each of two radial fills of two different areas, and performing raster image processing on each of two page description language files of two different file sizes, thereby creating a timing data profile that includes performance information in units of processing time per file size for each type of said above files, including image files and page description language files, and in units of processing time per unit area for each of said above types of fills, including a graduated fill, a patterned fill, and a radial fill; (c) examining said actual page description language file by determining, for each image of said actual page description language file, its size, whether it is scaled or non-scaled, and whether it is rotated or non-rotated, and determining the area for each computer generated graduated fill, patterned fill, and radial fill; (d) determining the total combined size of all image files of the actual page description language file and multiplying said total combined size by said performance information of the timing data profile in processing time per file size, and determining the total combined area of all computer generated fills by respective type and multiplying said total combined area by said performance information of the timing data profile in processing time per unit area by respective type, thereby creating an estimated first time period; (e) measuring the size of said actual page description language file and multiplying said actual page description language file size by said performance information the timing data profile in said page description language file processing time per file size, thereby creating an estimated second time period; and (f) combining said first time period and said second time period to create an estimate of the total time required to complete raster image processing. 6. The method as recited in claim 1, wherein the steps of providing a test data file, performing raster image processing and creating a timing data profile comprise: (a) performing raster image processing on a first non-rotated, non-scaled image file having a first file size, thereby creating a first time interval; (b) performing raster image processing on a second non-rotated, non-scaled image file having a second file size, said second file size being larger than said first file size, thereby creating a second time interval; (c) determining, from the values of said first and second time intervals and first and second file sizes, a value of raster image processing time per megabyte image file size; (d) performing raster image processing on a third rotated, non-scaled image file having said first file size, thereby creating a third time interval; (e) determining, from the values of said first and third time intervals, a first factor; (f) performing raster image processing on a fourth non-rotated, scaled image file having said first file size, thereby creating a fourth time interval; (g) determining, from the values of said first and fourth time intervals, a second factor; (h) performing raster image processing on a first graduated fill having a first area, thereby creating a fifth time interval; (i) performing raster image processing on a second graduated fill having a second area, said second area being larger than said first area, thereby creating a sixth time interval; (j) determining, from the values of said fifth and sixth time intervals and first and second areas, a value of raster image processing time per unit graduated fill area; (k) performing raster image processing on a first patterned fill having a third area, thereby creating a seventh time interval; (l) performing raster image processing on a second patterned fill having a fourth area, said second area being larger than said first area, thereby creating a eighth time interval; (m) determining, from the values of said seventh and eighth time intervals and third and fourth areas, a value of raster image processing time per unit patterned fill area; (n) performing raster image processing on a first radial fill having a fifth area, thereby creating a ninth time interval; (o) performing raster image processing on a second radial fill having a sixth area, said second area being larger than said first area, thereby creating a tenth time interval; (p) determining, from the values of said ninth and tenth time intervals and fifth and sixth areas, a value of raster image processing time per unit radial fill area; (q) performing raster image processing on a first page description language file having a third file size, thereby creating an eleventh time interval; (r) performing raster image processing on a second page description language file having a fourth file size, said fourth file size being larger than said third file size, thereby creating a twelfth time interval; and (s) determining, from the values of said eleventh and twelfth time intervals and third and fourth file sizes, a value of raster image processing time per megabyte page description language file size. | 0.500157 |
8,190,195 | 22 | 26 | 22. A mobile terminal, having: a pick-up device having an image acquisition element and a data record generator for generating at least one object data record from at least one acquired first image, which represents a physical object, and an identification label, and at least one information data record from at least one acquired second image which represents coded information related to the physical object, and the identification label; a transmitting/pick-up device for transmitting at least the object data record and the information data record to a correlation device spatially separate from the mobile terminal and connected thereto by means of at least one network, for the extraction of the coded information from the information data record, for the semantic interpretation analysis of the extracted information in order to establish which parts of the extracted information have which semantic meaning, and for the generation of at least one combination data record from the results of the semantic analysis, the extracted information and the at least one object data record with the same identification label as the extracted information data record; and for receiving the at least one combination data record from the correlation device; and a user device for the storage and further use of the combination data record. | 22. A mobile terminal, having: a pick-up device having an image acquisition element and a data record generator for generating at least one object data record from at least one acquired first image, which represents a physical object, and an identification label, and at least one information data record from at least one acquired second image which represents coded information related to the physical object, and the identification label; a transmitting/pick-up device for transmitting at least the object data record and the information data record to a correlation device spatially separate from the mobile terminal and connected thereto by means of at least one network, for the extraction of the coded information from the information data record, for the semantic interpretation analysis of the extracted information in order to establish which parts of the extracted information have which semantic meaning, and for the generation of at least one combination data record from the results of the semantic analysis, the extracted information and the at least one object data record with the same identification label as the extracted information data record; and for receiving the at least one combination data record from the correlation device; and a user device for the storage and further use of the combination data record. 26. The mobile terminal according to claim 22 , wherein the at least one combination data record has further data from the Internet which relate semantically to the extracted information, to the results of the semantic analysis, and/or to the object data. | 0.774336 |
8,019,710 | 29 | 39 | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. 39. The system of claim 29 further comprising instructions for at least one view that comprises at least one of a view of at least one question related to knowledge and at least one conclusion, a view of at least one set of questions or topics, a view of at least one question or topic related to knowledge, a view of knowledge related to at least one conclusion or meaning statement, a view of at least one meaning statement related to at least one conclusion, a view of at least one meaning statement or conclusion related to at least one answer or summary or both, a view of multiple alternative answers or summary viewpoints, a view of at least one question or topic related to at least one conclusion or meaning statement, a view of at least one question related to at least one answer, or a view of analysis related to data and related to at least one conclusion or meaning statement or answer or summary, or a combination thereof. | 0.500533 |
8,578,334 | 3 | 7 | 3. A method for providing dynamic code completion suggestions comprising the steps of: providing a browser-based integrated development environment that is implemented at least in part using a dynamic language; receiving input from a user in a form of at least a portion of a code command, the code command implemented at least in part using a dynamic language; using introspection of the browser-based integrated development environment that is implemented at least in part using a dynamic language to dynamically generate a list of one or more possible code command completion suggestions that are suitable completions for the input received from the user, wherein at least a portion of the code command completion suggestions are generated from searching a plurality of available commands for one or more suitable completions to the code command input by the user, wherein using introspection is performed against one or more available classes and global variables implemented using the dynamic language in the integrated development environment; and displaying at least a portion of the list of possible code command completion suggestions. | 3. A method for providing dynamic code completion suggestions comprising the steps of: providing a browser-based integrated development environment that is implemented at least in part using a dynamic language; receiving input from a user in a form of at least a portion of a code command, the code command implemented at least in part using a dynamic language; using introspection of the browser-based integrated development environment that is implemented at least in part using a dynamic language to dynamically generate a list of one or more possible code command completion suggestions that are suitable completions for the input received from the user, wherein at least a portion of the code command completion suggestions are generated from searching a plurality of available commands for one or more suitable completions to the code command input by the user, wherein using introspection is performed against one or more available classes and global variables implemented using the dynamic language in the integrated development environment; and displaying at least a portion of the list of possible code command completion suggestions. 7. A computer-readable storage memory having computer-executable instructions for causing a computer to perform the steps recited in claim 3 . | 0.653659 |
7,805,430 | 29 | 30 | 29. A computer readable storage medium according to claim 27 , wherein the second values are names. | 29. A computer readable storage medium according to claim 27 , wherein the second values are names. 30. A computer readable storage medium according to claim 29 , wherein the second values are information corresponding to the names. | 0.972385 |
7,552,398 | 27 | 29 | 27. The system of claim 16 , in which the processor stores the combination of the selected different length representations in a storage structure comprising records, wherein each record is associated with a level and differs from prior records and subsequent records by the associated levels. | 27. The system of claim 16 , in which the processor stores the combination of the selected different length representations in a storage structure comprising records, wherein each record is associated with a level and differs from prior records and subsequent records by the associated levels. 29. The system of claim 27 , in which the records are stored in a monotonically decreasing order based on the associated levels. | 0.951442 |
10,084,606 | 8 | 13 | 8. A computer program product for facilitating the generating of digital identity documents, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a selection and initialization of properties to be used in a digital identity document, wherein said properties comprise identity attributes, document types and a service uniform resource locator; building a template using said selected properties, wherein said template is to be used to construct a particular digital identity document; presenting a list of built templates to a user or a verifier to select; receiving a notification of a template selected by said user or said verifier from said list of templates to be used in generating a corresponding digital identity document; providing an acquisition uniform resource locator associated with said selected template to said user or said verifier to be used by said user or said verifier to request said digital identity document from an issuer, wherein said issuer constructs said digital identity document using said template selected by said user or said verifier, wherein said issuer is a government agency; receiving said digital identity document from said issuer; and delivering said received digital identity document to said user or said verifier. | 8. A computer program product for facilitating the generating of digital identity documents, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for: receiving a selection and initialization of properties to be used in a digital identity document, wherein said properties comprise identity attributes, document types and a service uniform resource locator; building a template using said selected properties, wherein said template is to be used to construct a particular digital identity document; presenting a list of built templates to a user or a verifier to select; receiving a notification of a template selected by said user or said verifier from said list of templates to be used in generating a corresponding digital identity document; providing an acquisition uniform resource locator associated with said selected template to said user or said verifier to be used by said user or said verifier to request said digital identity document from an issuer, wherein said issuer constructs said digital identity document using said template selected by said user or said verifier, wherein said issuer is a government agency; receiving said digital identity document from said issuer; and delivering said received digital identity document to said user or said verifier. 13. The computer program product as recited in claim 8 , wherein said user selects which attribute values in said digital identity document delivered to said user are to be revealed to said verifier in response to a challenge from said verifier. | 0.62766 |
9,449,598 | 6 | 11 | 6. A computer-implemented method comprising: as executed by a spoken language processing system comprising one or more computing devices configured to execute specific instructions, obtaining audio data corresponding to an utterance; initiating speech recognition on the audio data using a grammar, wherein speech recognition using the grammar proceeds to at least a first state of the grammar, wherein the first state of the grammar is linked to a second state of the grammar and a first state of a statistical language model, and wherein individual links between the grammar and the statistical language model are configured to bias speech recognition to use the grammar over the statistical language model; determining a first score using (1) acoustic information regarding the utterance and (2) a first weight associated with a link from the first state of the grammar to the second state of the grammar; determining a second score using (1) acoustic information regarding the utterance and (2) a second weight associated with a link from the first state of the grammar to the first state of the statistical language model; if the first score is greater than the second score, continuing speech recognition on the audio data using the second state of the grammar; and if the second score is greater than the first score, continuing speech recognition on the audio data using the first state of the statistical language model. | 6. A computer-implemented method comprising: as executed by a spoken language processing system comprising one or more computing devices configured to execute specific instructions, obtaining audio data corresponding to an utterance; initiating speech recognition on the audio data using a grammar, wherein speech recognition using the grammar proceeds to at least a first state of the grammar, wherein the first state of the grammar is linked to a second state of the grammar and a first state of a statistical language model, and wherein individual links between the grammar and the statistical language model are configured to bias speech recognition to use the grammar over the statistical language model; determining a first score using (1) acoustic information regarding the utterance and (2) a first weight associated with a link from the first state of the grammar to the second state of the grammar; determining a second score using (1) acoustic information regarding the utterance and (2) a second weight associated with a link from the first state of the grammar to the first state of the statistical language model; if the first score is greater than the second score, continuing speech recognition on the audio data using the second state of the grammar; and if the second score is greater than the first score, continuing speech recognition on the audio data using the first state of the statistical language model. 11. The computer-implemented method of claim 6 , wherein states of the grammar are linked to states of the statistical language model in an n-to-1 relationship, wherein n may be any positive integer. | 0.918107 |
9,690,861 | 1 | 7 | 1. A method comprising: receiving a query for information from an electronic medical record (EMR) comprising structured data and unstructured data; annotating contents of said unstructured data and said structured data to produce annotations; using said annotations to create concept unique identifiers (CUIs); identifying clinically relevant semantic relationships between said structured data and unstructured data in said EMR based on statistical associations between said CUIs; producing a score for relevant information from said EMR that is semantically related to said query based on strength of said clinically relevant semantic relationships between said structured data and unstructured data; and prioritizing a display of said relevant information based on said score; and providing, in response to said query, said relevant information, said relevant information comprising at least one of clinical notes, medications, test results, treatments, and contraindications. | 1. A method comprising: receiving a query for information from an electronic medical record (EMR) comprising structured data and unstructured data; annotating contents of said unstructured data and said structured data to produce annotations; using said annotations to create concept unique identifiers (CUIs); identifying clinically relevant semantic relationships between said structured data and unstructured data in said EMR based on statistical associations between said CUIs; producing a score for relevant information from said EMR that is semantically related to said query based on strength of said clinically relevant semantic relationships between said structured data and unstructured data; and prioritizing a display of said relevant information based on said score; and providing, in response to said query, said relevant information, said relevant information comprising at least one of clinical notes, medications, test results, treatments, and contraindications. 7. The method according to claim 1 , said CUIs comprise standardized identifiers relating to medical disorders related to said information in said unstructured data and said structured data. | 0.874835 |
9,471,692 | 3 | 4 | 3. The method of claim 2 , wherein the structured query comprises references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges. | 3. The method of claim 2 , wherein the structured query comprises references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges. 4. The method of claim 3 , wherein: the inner query constraint is for one or more nodes of the plurality of nodes connected to a first of the selected nodes by a first of the selected edges; and the outer query constraint is for one or more nodes of the plurality of nodes connected to a second of the selected nodes by a second of the selected edges. | 0.823263 |
9,183,194 | 9 | 10 | 9. The method of claim 1 , further comprising: identifying a document type of the document structure instance, the document type including structure categories; and where the glossary includes permissible terms for a selected structure category from the structure categories of the document type. | 9. The method of claim 1 , further comprising: identifying a document type of the document structure instance, the document type including structure categories; and where the glossary includes permissible terms for a selected structure category from the structure categories of the document type. 10. The method of claim 9 , where the relationship map visualizes at least part of the selected structure category. | 0.927582 |
9,760,561 | 1 | 8 | 1. A method programmed in a non-transitory memory of a device comprising: a. acquiring target information; b. processing the target information, including parsing the target information into parsed information; c. fact checking, with the device, the target information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; d. generating a modified target information by deleting the parsed information indicated as factually inaccurate; e. summarizing the modified target information to generate a summary of the target information utilizing lexical chaining and the fact checking results generated by fact checking the target information, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in a lexical chain when the word is found, further wherein summarizing the modified target information includes determining total strengths of sentences within the target information, wherein a total strength of a sentence is based on a lexical chain strength and a factual accuracy of the sentence, further wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the target information includes the fact checking results; and f. providing the summary of the target information in real-time. | 1. A method programmed in a non-transitory memory of a device comprising: a. acquiring target information; b. processing the target information, including parsing the target information into parsed information; c. fact checking, with the device, the target information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; d. generating a modified target information by deleting the parsed information indicated as factually inaccurate; e. summarizing the modified target information to generate a summary of the target information utilizing lexical chaining and the fact checking results generated by fact checking the target information, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in a lexical chain when the word is found, further wherein summarizing the modified target information includes determining total strengths of sentences within the target information, wherein a total strength of a sentence is based on a lexical chain strength and a factual accuracy of the sentence, further wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the target information includes the fact checking results; and f. providing the summary of the target information in real-time. 8. The method of claim 1 wherein summarizing the modified target information utilizes two different summarizing implementations to generate two different summaries, and comparing the two different summaries. | 0.882386 |
8,174,409 | 4 | 5 | 4. A lineographic data input system according to claim 1 , wherein said plurality of cells are configured in four rows and three columns. | 4. A lineographic data input system according to claim 1 , wherein said plurality of cells are configured in four rows and three columns. 5. A lineographic data input system according to claim 4 , further including a high relief line separating the first three rows from the fourth row. | 0.949001 |
7,936,861 | 1 | 8 | 1. A system comprising: a call reception module configured to receive a call from a caller; a factor engine configured to identify a set of menu options based on a plurality of factors, wherein the factor engine is further configured to order the set of menu options based on weightings associated with each factor of the plurality of factors, wherein the weightings are not defined by the caller, and wherein at least one of the plurality of factors includes a geographic region of the caller, each of the weightings is applied to each of the plurality of factors to produce each weighted factor; an audio clip sequencing engine responsive to the factor engine and configured to generate an ordered sequence of audio clips based on the ordered set of menu options, wherein one or more audio clips of the ordered sequence of audio clips are associated with one or more products or services that are available to the caller based on the geographic region of the caller; an announcement engine responsive to the audio clip sequencing engine and configured to play the ordered sequence of audio clips in connection with the call; and a response system configured to receive a caller selection of a menu option of the set of menu options; wherein the announcement engine configured to play a pre-emptive clip before playing the ordered sequence of audio clips when an exception condition exists. | 1. A system comprising: a call reception module configured to receive a call from a caller; a factor engine configured to identify a set of menu options based on a plurality of factors, wherein the factor engine is further configured to order the set of menu options based on weightings associated with each factor of the plurality of factors, wherein the weightings are not defined by the caller, and wherein at least one of the plurality of factors includes a geographic region of the caller, each of the weightings is applied to each of the plurality of factors to produce each weighted factor; an audio clip sequencing engine responsive to the factor engine and configured to generate an ordered sequence of audio clips based on the ordered set of menu options, wherein one or more audio clips of the ordered sequence of audio clips are associated with one or more products or services that are available to the caller based on the geographic region of the caller; an announcement engine responsive to the audio clip sequencing engine and configured to play the ordered sequence of audio clips in connection with the call; and a response system configured to receive a caller selection of a menu option of the set of menu options; wherein the announcement engine configured to play a pre-emptive clip before playing the ordered sequence of audio clips when an exception condition exists. 8. The system of claim 1 , wherein the factor engine identifies a first menu option based on a first factor and determines a first score associated with the first menu option based on a first weighting associated with the first factor, wherein the factor engine identifies a second menu option based on a second factor and determines a second score associated with the second menu option based on a second weighting associated with the second factor, and wherein the first menu option precedes the second menu option in the ordered set of menu options when the first score exceeds the second score. | 0.641487 |
8,695,037 | 12 | 15 | 12. A method of enabling a user to select an individual content item associated with a displayed channel, in a system that includes a single graphical user interface window, wherein the single graphical user interface window does not involve overlaying, including a representation of a set of channels and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data, the method comprising: displaying the representation of a plurality of the channels; enabling the user to navigate interactively in the individual content items; enabling the user to navigate among the individual content items from the graphical user interface window, wherein if the user navigates to the interactive data, then the representation of the plurality of channels and the interactive data are both displayed within the single graphical user interface window; enabling the user to select a desired channel; displaying the representation of the individual content items associated with a selected channel, wherein displaying the individual content is performed upon the selection of the desired channel; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. | 12. A method of enabling a user to select an individual content item associated with a displayed channel, in a system that includes a single graphical user interface window, wherein the single graphical user interface window does not involve overlaying, including a representation of a set of channels and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data, the method comprising: displaying the representation of a plurality of the channels; enabling the user to navigate interactively in the individual content items; enabling the user to navigate among the individual content items from the graphical user interface window, wherein if the user navigates to the interactive data, then the representation of the plurality of channels and the interactive data are both displayed within the single graphical user interface window; enabling the user to select a desired channel; displaying the representation of the individual content items associated with a selected channel, wherein displaying the individual content is performed upon the selection of the desired channel; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. 15. The method of claim 12 , wherein the individual content items include information that includes links to other information associated with the selected channel, the method further comprising: displaying the information that includes the links; enabling the user to activate a link to the other information; and displaying the linked information. | 0.642418 |
9,350,636 | 7 | 12 | 7. Logic encoded in one or more non-transitory tangible media that includes code for execution and when executed by a processor is operable to perform operations comprising: processing a first text created by a user using an online service into a first bag of words, the first bag of words comprising a list of words that appear in the text, each of the words having associated therewith a number representing a number of times the associated word appears in the text; computing a similarity between the first bag of words and at least one second bag of words, wherein the computing comprises, for each word in the first bag of words, determining a compare count comprising a minimum number of times the word appears in each of the first bag of words and the second bag of words and adding the compare count to a sum of counts, wherein the computed similarity comprises two times the sum of counts divided by the total number of words in the first bag of words and the second bag of words; comparing the computed similarity with a threshold; and determining that the user is a spammer and preventing the user from using the online service to create additional texts if the computed similarity is greater than the threshold, wherein the first text comprises a user profile of the user in connection with the online service. | 7. Logic encoded in one or more non-transitory tangible media that includes code for execution and when executed by a processor is operable to perform operations comprising: processing a first text created by a user using an online service into a first bag of words, the first bag of words comprising a list of words that appear in the text, each of the words having associated therewith a number representing a number of times the associated word appears in the text; computing a similarity between the first bag of words and at least one second bag of words, wherein the computing comprises, for each word in the first bag of words, determining a compare count comprising a minimum number of times the word appears in each of the first bag of words and the second bag of words and adding the compare count to a sum of counts, wherein the computed similarity comprises two times the sum of counts divided by the total number of words in the first bag of words and the second bag of words; comparing the computed similarity with a threshold; and determining that the user is a spammer and preventing the user from using the online service to create additional texts if the computed similarity is greater than the threshold, wherein the first text comprises a user profile of the user in connection with the online service. 12. The logic of claim 7 , wherein the second bag of words is associated with a spam text. | 0.892344 |
9,658,988 | 12 | 14 | 12. An apparatus for segmenting text for layout on a web browser, the apparatus comprising: a client computer configured to: receive a block of text; define a plurality of regular expressions, wherein a first regular expression in the plurality of regular expressions is used to search for a word or a word boundary; segment the block of text into a plurality of text segments, wherein the segmenting comprises: searching the block of text starting at a defined location for a first text segment that matches any of the plurality of regular expressions; searching the first text segment for a change in text style; segmenting the first text segment into two sub-segments at the location of the change in text style to create a modified first segment and a second segment; adding the modified first text segment to the plurality of text segments; and updating the defined location to be located at the end of the modified first text segment within the block of text; and construct a layout of the block of text using the plurality of text segments, wherein constructing the layout comprises automatically inserting a line break before the modified first segment. | 12. An apparatus for segmenting text for layout on a web browser, the apparatus comprising: a client computer configured to: receive a block of text; define a plurality of regular expressions, wherein a first regular expression in the plurality of regular expressions is used to search for a word or a word boundary; segment the block of text into a plurality of text segments, wherein the segmenting comprises: searching the block of text starting at a defined location for a first text segment that matches any of the plurality of regular expressions; searching the first text segment for a change in text style; segmenting the first text segment into two sub-segments at the location of the change in text style to create a modified first segment and a second segment; adding the modified first text segment to the plurality of text segments; and updating the defined location to be located at the end of the modified first text segment within the block of text; and construct a layout of the block of text using the plurality of text segments, wherein constructing the layout comprises automatically inserting a line break before the modified first segment. 14. The apparatus of claim 12 , wherein the client computer is further configured to: search the first text segment for a change in text direction; and segment the first text segment into two sub-segments at the location of the change in text direction. | 0.633333 |
9,875,309 | 1 | 3 | 1. A method comprising: identifying a set of topics appearing in text strings included in a plurality of data sources; associating each topic with a context vector, each context vector representing a frequency of a given topic co-occurring in one or more text strings with a plurality of topics from the set of topics and comprising: a plurality of context confidence values, each context confidence value representing a relationship between a given identified topic and an additional identified topic that co-occurs within a text string from the plurality of data sources with the given identified topic; and where each context confidence value of the plurality of context confidence values is based upon a combination of a topic confidence value of the given identified topic and a topic confidence value of the additional identified topic that co-occurs within the text string from the plurality of data sources with the given identified topic; receiving a search query comprising a keyword; identifying one or more topics associated with the keyword included in the search query; identifying one or more text strings from the plurality of data sources that include one or more of the topics associated with the keyword included in the search query; and generating a search result for the search query that includes the identified text strings. | 1. A method comprising: identifying a set of topics appearing in text strings included in a plurality of data sources; associating each topic with a context vector, each context vector representing a frequency of a given topic co-occurring in one or more text strings with a plurality of topics from the set of topics and comprising: a plurality of context confidence values, each context confidence value representing a relationship between a given identified topic and an additional identified topic that co-occurs within a text string from the plurality of data sources with the given identified topic; and where each context confidence value of the plurality of context confidence values is based upon a combination of a topic confidence value of the given identified topic and a topic confidence value of the additional identified topic that co-occurs within the text string from the plurality of data sources with the given identified topic; receiving a search query comprising a keyword; identifying one or more topics associated with the keyword included in the search query; identifying one or more text strings from the plurality of data sources that include one or more of the topics associated with the keyword included in the search query; and generating a search result for the search query that includes the identified text strings. 3. The method of claim 1 wherein the search result comprises a plurality of topic categories, each category associated with an identified topic associated with the keyword. | 0.834933 |
9,361,586 | 1 | 7 | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. 7. The method of claim 1 wherein the input vectors comprise images. | 0.856838 |
7,627,571 | 16 | 18 | 16. The method of claim 12 wherein the extracting of text identifies a dominant reference node for each reference explanatory text node. | 16. The method of claim 12 wherein the extracting of text identifies a dominant reference node for each reference explanatory text node. 18. The method of claim 16 wherein the extracting of text extracts explanatory text associated with a reference in a dominant reference node. | 0.964195 |
8,630,920 | 1 | 2 | 1. A computer-implemented method comprising: processing a search query by selecting a plurality of item listings that are determined to satisfy the search query; determining an initial ranking score for each item listing in the plurality of item listings; determining, using a computer processor, that a conditional statement of a business rule is satisfied for a first item listing, wherein the conditional statement provides that the conditional statement is satisfied if a shipping fee specified by the first item listing is less than or equal to a median or a mode of shipping fees for a set of item listings offering items determined to be similar to a first item being offered by the first item listing, wherein determining that the conditional statement of the business rule is satisfied includes calculating the mode or the median of the shipping fees; responsive to determining that the conditional statement of the business rule is satisfied for the first item listing, adjusting an initial ranking score for the first item listing with an adjustment factor included in the business rule to generate an adjusted ranking score for the first item listing; presenting a set of the plurality of item listings in a search results page with the first item listing positioned relative to other item listings in the set based, at least in part, on the adjusted ranking score for the first item listing and an initial ranking score or an adjusted ranking score for each of the other item listings. | 1. A computer-implemented method comprising: processing a search query by selecting a plurality of item listings that are determined to satisfy the search query; determining an initial ranking score for each item listing in the plurality of item listings; determining, using a computer processor, that a conditional statement of a business rule is satisfied for a first item listing, wherein the conditional statement provides that the conditional statement is satisfied if a shipping fee specified by the first item listing is less than or equal to a median or a mode of shipping fees for a set of item listings offering items determined to be similar to a first item being offered by the first item listing, wherein determining that the conditional statement of the business rule is satisfied includes calculating the mode or the median of the shipping fees; responsive to determining that the conditional statement of the business rule is satisfied for the first item listing, adjusting an initial ranking score for the first item listing with an adjustment factor included in the business rule to generate an adjusted ranking score for the first item listing; presenting a set of the plurality of item listings in a search results page with the first item listing positioned relative to other item listings in the set based, at least in part, on the adjusted ranking score for the first item listing and an initial ranking score or an adjusted ranking score for each of the other item listings. 2. The computer-implemented method of claim 1 , wherein the initial ranking score associated with an item listing is to be adjusted when the item listing specifies that an item will ship to a buyer with no shipping fee. | 0.844017 |
8,374,791 | 17 | 19 | 17. A computer implemented method of operating a navigation system to provide a guidance message, the method comprising: obtaining, by a processor, data from a geographic database associated with the navigation system to identify a preferred name of a visible feature, wherein the preferred name is in a first language; identifying, by the processor, parts-of-speech components of the preferred name; and translating, by the processor, the parts-of-speech components of the preferred name into a target language and arranging the translated components into a target language text to provide the preferred name of the visible feature in the target language, wherein the target language is different from the first language. | 17. A computer implemented method of operating a navigation system to provide a guidance message, the method comprising: obtaining, by a processor, data from a geographic database associated with the navigation system to identify a preferred name of a visible feature, wherein the preferred name is in a first language; identifying, by the processor, parts-of-speech components of the preferred name; and translating, by the processor, the parts-of-speech components of the preferred name into a target language and arranging the translated components into a target language text to provide the preferred name of the visible feature in the target language, wherein the target language is different from the first language. 19. The method of claim 17 wherein the wherein the parts-of-speech components of the preferred name are indicated by data from the geographic database. | 0.856464 |
7,725,452 | 13 | 17 | 13. A computer-readable storage medium having stored thereon instructions which, when executed by a processor, cause the processor to perform the operations of: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; for each retrieved document identifier, determining a query-independent score indicative of a page rank of the corresponding document relative to other documents in a set of documents; determining a content change frequency of the corresponding document identifier by comparing information stored for successive downloads of the corresponding document, determining an age of the corresponding document, wherein the age is associated with the time of the last download of the corresponding document, and determining a first score for the document identifier that is a function of the query-independent score and the determined content change frequency and the determined age of the corresponding document; comparing the first score against a threshold value; and conditionally scheduling the document for indexing based on the result of the comparison. | 13. A computer-readable storage medium having stored thereon instructions which, when executed by a processor, cause the processor to perform the operations of: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; for each retrieved document identifier, determining a query-independent score indicative of a page rank of the corresponding document relative to other documents in a set of documents; determining a content change frequency of the corresponding document identifier by comparing information stored for successive downloads of the corresponding document, determining an age of the corresponding document, wherein the age is associated with the time of the last download of the corresponding document, and determining a first score for the document identifier that is a function of the query-independent score and the determined content change frequency and the determined age of the corresponding document; comparing the first score against a threshold value; and conditionally scheduling the document for indexing based on the result of the comparison. 17. A computer-readable storage medium of claim 13 , wherein the threshold value is determined using a score computed for each document identifier in a sample set of document identifiers. | 0.815945 |
8,756,184 | 13 | 19 | 13. An apparatus for utilizing a user's predicted attributes in a computer system comprising: (a) a computer having a memory; (b) an application executing on the computer, wherein the application is configured to: collect a plurality of sample user behaviors and a plurality of sample user attributes from a service that offers videos for viewing, wherein a sample user behavior is based on a sample user using the service and a sample user attribute is received from the sample user; train a model to be able to produce the plurality of sample user attributes from the plurality of sample user behaviors; after training, input the plurality of sample user behaviors into the trained model to produce predicted sample user attributes; compare the plurality of sample user attributes and the plurality of sample user behaviors to the predicted sample user attributes to determine associated probabilities for the predicted sample user attributes; determine a real user behavior for a second user based on the second user using the service; predict, using the model, that the second user has a predicted user attribute of an associated probability based on the user having the real user behavior, wherein the predicted user attribute of the associated probability is not known for the second user; and utilize that the second user has the predicted user attribute of the associated probability to improve the second user's experience using the service. | 13. An apparatus for utilizing a user's predicted attributes in a computer system comprising: (a) a computer having a memory; (b) an application executing on the computer, wherein the application is configured to: collect a plurality of sample user behaviors and a plurality of sample user attributes from a service that offers videos for viewing, wherein a sample user behavior is based on a sample user using the service and a sample user attribute is received from the sample user; train a model to be able to produce the plurality of sample user attributes from the plurality of sample user behaviors; after training, input the plurality of sample user behaviors into the trained model to produce predicted sample user attributes; compare the plurality of sample user attributes and the plurality of sample user behaviors to the predicted sample user attributes to determine associated probabilities for the predicted sample user attributes; determine a real user behavior for a second user based on the second user using the service; predict, using the model, that the second user has a predicted user attribute of an associated probability based on the user having the real user behavior, wherein the predicted user attribute of the associated probability is not known for the second user; and utilize that the second user has the predicted user attribute of the associated probability to improve the second user's experience using the service. 19. The apparatus of claim 13 , wherein the application is configured to predict by: processing the real user behavior in the model to produce the predicted user attribute and a cumulative probability as the associated probability for the predicted user attribute. | 0.844156 |
7,908,329 | 8 | 11 | 8. A method for improving security of electronic mail messages comprising the steps of: receiving, at an electronic mail application on a computing device, an electronic mail message in its original format as sent to a user by an un-trusted source, the electronic mail message comprising at least one hyperlink in a body of the electronic mail message, wherein when the electronic mail message is displayed in its original format, text of a uniform resource locator associated with the at least one hyperlink is hidden from view of the user; determining that the electronic mail message is a junk message; identifying the electronic mail message as a spam message or a phishing message; placing the electronic mail message in a junk folder of the user within electronic mail storage of the electronic mail application, the junk folder being used to store junk messages that have been sent to the user from un-trusted sources and that have been identified by the electronic mail application spam messages or phishing messages, the electronic mail message being stored in the junk folder in its original format as sent by the un-trusted source and as received by the electronic mail application; providing, in the electronic mail storage of the electronic mail application, an inbox folder of the user to store the electronic mail message in its original format upon being moved by the user from the junk folder to the inbox folder; in response to receiving a request from the user to view the electronic mail message when in the junk folder: reformatting the electronic mail message from its original format to a modified format, the modified format comprising a plain text format for reformatting the body of the electronic mail message with the at least one hyperlink disabled, and displaying the electronic mail message in the modified format with the at least one hyperlink disabled and the text of the uniform resource locator associated with the at least one hyperlink visible to the user as plain text in the body of the electronic mail message; and in response receiving a request from the user to view the electronic mail message when in the inbox folder after being moved by the user from the junk folder to the inbox folder: displaying the electronic mail message in its original format with the at least one hyperlink enabled if the electronic mail message has been identified as a spam message, and displaying the electronic mail message in its original format with the at least one hyperlink disabled if the electronic mail message has been identified as a phishing message. | 8. A method for improving security of electronic mail messages comprising the steps of: receiving, at an electronic mail application on a computing device, an electronic mail message in its original format as sent to a user by an un-trusted source, the electronic mail message comprising at least one hyperlink in a body of the electronic mail message, wherein when the electronic mail message is displayed in its original format, text of a uniform resource locator associated with the at least one hyperlink is hidden from view of the user; determining that the electronic mail message is a junk message; identifying the electronic mail message as a spam message or a phishing message; placing the electronic mail message in a junk folder of the user within electronic mail storage of the electronic mail application, the junk folder being used to store junk messages that have been sent to the user from un-trusted sources and that have been identified by the electronic mail application spam messages or phishing messages, the electronic mail message being stored in the junk folder in its original format as sent by the un-trusted source and as received by the electronic mail application; providing, in the electronic mail storage of the electronic mail application, an inbox folder of the user to store the electronic mail message in its original format upon being moved by the user from the junk folder to the inbox folder; in response to receiving a request from the user to view the electronic mail message when in the junk folder: reformatting the electronic mail message from its original format to a modified format, the modified format comprising a plain text format for reformatting the body of the electronic mail message with the at least one hyperlink disabled, and displaying the electronic mail message in the modified format with the at least one hyperlink disabled and the text of the uniform resource locator associated with the at least one hyperlink visible to the user as plain text in the body of the electronic mail message; and in response receiving a request from the user to view the electronic mail message when in the inbox folder after being moved by the user from the junk folder to the inbox folder: displaying the electronic mail message in its original format with the at least one hyperlink enabled if the electronic mail message has been identified as a spam message, and displaying the electronic mail message in its original format with the at least one hyperlink disabled if the electronic mail message has been identified as a phishing message. 11. The method of claim 8 , wherein the electronic mail message includes HTML and at least one image in its original format. | 0.850242 |
9,218,589 | 15 | 18 | 15. The system of claim 3 , the endorsement management module further comprising a central authority database for rules and protocol associated with valid endorsement registrations. | 15. The system of claim 3 , the endorsement management module further comprising a central authority database for rules and protocol associated with valid endorsement registrations. 18. The system of claim 15 , the endorsement management module further configured to push specified management endorsement rules to the endorsement issuance module as specified endorsement issuance rules. | 0.949254 |
8,151,358 | 1 | 12 | 1. A method, performed at least in part by a computer, for sharing digital items with communication identities, the method comprising: receiving, from a user interface of a first communication identity, a selection of a first group of multiple communication identities, wherein the first group of multiple communication identities comprises a subset of a group of linked communication identities, wherein the first communication identity is able to send instant messages to and receive instant messages from each of the linked communication identities; receiving, from the user interface of the first communication identity, instructions to grant each of the multiple communication identities in the first group access to a digital item via the Internet; enabling the multiple communication identities in the first group to access the digital item via the Internet based on inclusion of the multiple communication identities in the first group within the instructions to grant access to the digital item via the Internet; enabling one or more of the multiple communication identities in the first group to annotate the digital item via the Internet; in response to receiving an indication that the first communication identity has selected the digital item from a list of digital items displayed in a first window in a graphical user interface, displaying the group of linked communication identities in a second window in the graphical user interface; in response to receiving an indication that the first communication identity has selected a communication identity from the second window, displaying a list of permissions associated with the selected communication identity in a third window in the graphical user interface, wherein the third window provides functionality for allowing the first communication identity to specify permissions governing the selected communication identity's access to the selected digital item, wherein the selected communication identity is one of the multiple communication identities, and wherein the list of permissions includes an option to deny the selected communication identity access to view annotations associated with the digital item; and in response to receiving instructions to deny access to view annotations associated with the digital item, denying the selected communication identity access to view annotations associated with the digital item, while still enabling the selected communication identity to access the digital item. | 1. A method, performed at least in part by a computer, for sharing digital items with communication identities, the method comprising: receiving, from a user interface of a first communication identity, a selection of a first group of multiple communication identities, wherein the first group of multiple communication identities comprises a subset of a group of linked communication identities, wherein the first communication identity is able to send instant messages to and receive instant messages from each of the linked communication identities; receiving, from the user interface of the first communication identity, instructions to grant each of the multiple communication identities in the first group access to a digital item via the Internet; enabling the multiple communication identities in the first group to access the digital item via the Internet based on inclusion of the multiple communication identities in the first group within the instructions to grant access to the digital item via the Internet; enabling one or more of the multiple communication identities in the first group to annotate the digital item via the Internet; in response to receiving an indication that the first communication identity has selected the digital item from a list of digital items displayed in a first window in a graphical user interface, displaying the group of linked communication identities in a second window in the graphical user interface; in response to receiving an indication that the first communication identity has selected a communication identity from the second window, displaying a list of permissions associated with the selected communication identity in a third window in the graphical user interface, wherein the third window provides functionality for allowing the first communication identity to specify permissions governing the selected communication identity's access to the selected digital item, wherein the selected communication identity is one of the multiple communication identities, and wherein the list of permissions includes an option to deny the selected communication identity access to view annotations associated with the digital item; and in response to receiving instructions to deny access to view annotations associated with the digital item, denying the selected communication identity access to view annotations associated with the digital item, while still enabling the selected communication identity to access the digital item. 12. The method of claim 1 wherein: enabling the multiple communication identities in the first group to access the digital item includes accessing the instructions to grant the multiple communication identities in the first group access to the digital item via the Internet and identifying the multiple communication identities in the first group as communication identities included in the instructions to grant access. | 0.501188 |
9,665,275 | 1 | 10 | 1. A computer-implemented method, comprising: displaying, at a touch display of a computing device having one or more processors, a first virtual keyboard having characters in a source language; receiving, at the touch display of the computing device, a particular spot input indicating a start character of the first virtual keyboard; displaying, at the touch display of the computing device, a second virtual keyboard having characters in the source language, the second virtual keyboard simultaneously displaying all characters for inputting a remainder of all possible multi-character compound consonants or vowels beginning with the start character using a single slide input; receiving, at the touch display of the computing device, a particular slide input from the start character to an end character from the second virtual keyboard; determining, at the computing device, a string of characters including the (i) start character, (ii) one or more additional characters of the second virtual keyboard along a path of the particular slide input, and (iii) the end character; and displaying, at the touch display of the computing device, the string of characters. | 1. A computer-implemented method, comprising: displaying, at a touch display of a computing device having one or more processors, a first virtual keyboard having characters in a source language; receiving, at the touch display of the computing device, a particular spot input indicating a start character of the first virtual keyboard; displaying, at the touch display of the computing device, a second virtual keyboard having characters in the source language, the second virtual keyboard simultaneously displaying all characters for inputting a remainder of all possible multi-character compound consonants or vowels beginning with the start character using a single slide input; receiving, at the touch display of the computing device, a particular slide input from the start character to an end character from the second virtual keyboard; determining, at the computing device, a string of characters including the (i) start character, (ii) one or more additional characters of the second virtual keyboard along a path of the particular slide input, and (iii) the end character; and displaying, at the touch display of the computing device, the string of characters. 10. The computer-implemented method of claim 1 , wherein the second virtual keyboard is displayed via a pop-up window overlaying the first virtual keyboard. | 0.721429 |
9,552,345 | 1 | 9 | 1. A method at a computing device comprising: rendering, by an application that at least one of reads or writes documents, a document at a display device, the application executing on the computing device or at a remote computing entity in communication with the computing device; receiving sensor data from one or more sensors monitoring user annotation events associated with the rendered document, whilst also, monitoring state data of the application; recognizing one or more gestures by analyzing the received sensor data; storing the state data with associated timestamps; storing the recognized gestures with associated timestamps; and calculating and storing a compressed record of the sensor data on the basis of the recognized gestures, the state data, and the timestamps, wherein the compressed record of the sensor data comprises identifiers of a plurality of views of the document having associated recognized gestures, the plurality of views of the document together forming a storyboard. | 1. A method at a computing device comprising: rendering, by an application that at least one of reads or writes documents, a document at a display device, the application executing on the computing device or at a remote computing entity in communication with the computing device; receiving sensor data from one or more sensors monitoring user annotation events associated with the rendered document, whilst also, monitoring state data of the application; recognizing one or more gestures by analyzing the received sensor data; storing the state data with associated timestamps; storing the recognized gestures with associated timestamps; and calculating and storing a compressed record of the sensor data on the basis of the recognized gestures, the state data, and the timestamps, wherein the compressed record of the sensor data comprises identifiers of a plurality of views of the document having associated recognized gestures, the plurality of views of the document together forming a storyboard. 9. The method according to claim 1 , wherein the compressed record of the sensor data further comprises an animation of at least part of one of the recognized gestures. | 0.867925 |
8,699,677 | 3 | 4 | 3. The method of claim 1 , further comprising: transcribing the second segment separately from the first segment. | 3. The method of claim 1 , further comprising: transcribing the second segment separately from the first segment. 4. The method of claim 3 , wherein transcribing the second segment separately from the first segment comprises transcribing the second segment in its own thread. | 0.935237 |
7,836,394 | 1 | 14 | 1. A computer program product, comprising a computer-readable storage medium including computer-readable instructions embodied therein, that when executed by one or more processors, implement a method for the retrieval, analysis and display of electronically tagged financial data, the instructions comprising: an integrated file access component, analysis component and presentation component for accessing, analyzing and presenting electronically tagged financial data within the application; the file access component comprising: one or more user selection modules for selecting a plurality of files, the files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content, the analysis component comprising: one or more analysis modules for calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and the presentation component comprising: one or more presentation modules for presenting information associated with the selected files, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure. | 1. A computer program product, comprising a computer-readable storage medium including computer-readable instructions embodied therein, that when executed by one or more processors, implement a method for the retrieval, analysis and display of electronically tagged financial data, the instructions comprising: an integrated file access component, analysis component and presentation component for accessing, analyzing and presenting electronically tagged financial data within the application; the file access component comprising: one or more user selection modules for selecting a plurality of files, the files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content, the analysis component comprising: one or more analysis modules for calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and the presentation component comprising: one or more presentation modules for presenting information associated with the selected files, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure. 14. The computer program product of claim 1 , wherein the one or more presentation modules includes a financial statement module comprising means for creating as part of the presented information, financial statements from the presented information. | 0.77847 |
9,406,080 | 1 | 4 | 1. A computer-implemented method comprising: receiving a plurality of keywords to be trafficked on a search engine; automatically selecting at least one of the plurality of keywords to be omitted from trafficking on the search engine based on pruning criteria, the automatically selecting comprising: for each one of the selected at least one of the plurality of keywords, determining a corresponding confidence level with which a corresponding predicted value of the at least one of the plurality of keywords is expected to satisfy the pruning criteria; and for each one of the selected at least one of the plurality of keywords, determining that the corresponding confidence level satisfies a configurable confidence level threshold, the automatic selection of each one of the selected at least one of the plurality of keywords being based on the determination that the corresponding confidence level satisfies the configurable confidence level threshold; generating, by a machine having a memory and at least one processor, a report, the report comprising the selected at least one of the plurality of keywords and a corresponding value for each one of the selected at least one of the plurality of keywords, the corresponding value being based on the corresponding one of the selected at least one of the plurality of keywords being omitted from trafficking on the search engine; causing the report to be displayed to a user; and removing at least a portion of the selected at least one of the plurality of keywords from being trafficked on the search engine based on the selection of the at least one of the plurality of keywords to be omitted, the removing of the at least a portion of the selected at least one of the plurality of keywords being performed in response to a user input corresponding to the report, the user input being used to determine the at least a portion of the selected at least one of the plurality of keywords to be omitted. | 1. A computer-implemented method comprising: receiving a plurality of keywords to be trafficked on a search engine; automatically selecting at least one of the plurality of keywords to be omitted from trafficking on the search engine based on pruning criteria, the automatically selecting comprising: for each one of the selected at least one of the plurality of keywords, determining a corresponding confidence level with which a corresponding predicted value of the at least one of the plurality of keywords is expected to satisfy the pruning criteria; and for each one of the selected at least one of the plurality of keywords, determining that the corresponding confidence level satisfies a configurable confidence level threshold, the automatic selection of each one of the selected at least one of the plurality of keywords being based on the determination that the corresponding confidence level satisfies the configurable confidence level threshold; generating, by a machine having a memory and at least one processor, a report, the report comprising the selected at least one of the plurality of keywords and a corresponding value for each one of the selected at least one of the plurality of keywords, the corresponding value being based on the corresponding one of the selected at least one of the plurality of keywords being omitted from trafficking on the search engine; causing the report to be displayed to a user; and removing at least a portion of the selected at least one of the plurality of keywords from being trafficked on the search engine based on the selection of the at least one of the plurality of keywords to be omitted, the removing of the at least a portion of the selected at least one of the plurality of keywords being performed in response to a user input corresponding to the report, the user input being used to determine the at least a portion of the selected at least one of the plurality of keywords to be omitted. 4. The method of claim 1 , wherein receiving the plurality of keywords comprises receiving the plurality of keywords from a source, the source being from the group: a search query and a product listing. | 0.786469 |
8,755,596 | 1 | 7 | 1. A computer-based method of inferring and utilizing aesthetic quality of photographs and other images, comprising the steps of: receiving a plurality of digitized images along with aesthetic-based ratings of the images; performing one or more software operations on the digitized images to automatically extract a plurality of visual features representative of each image; receiving an image without an aesthetic-based rating; automatically extracting a plurality of visual features representative of the received image; computing a familiarity measure for the received image by correlating the visual features extracted from the received image to the visual features extracted from the other images; determining an aesthetic-based rating for the received image on the basis of the familiarity measure, wherein a lower familiarity is indicative of originality and a higher rating; and using one or more statistical methods to correlate the extracted visual features and the aesthetic-based ratings to classify the images on the basis of aesthetic value, rate the images on a scale relating to aesthetics value, or select/eliminate an image based upon aesthetic quality. | 1. A computer-based method of inferring and utilizing aesthetic quality of photographs and other images, comprising the steps of: receiving a plurality of digitized images along with aesthetic-based ratings of the images; performing one or more software operations on the digitized images to automatically extract a plurality of visual features representative of each image; receiving an image without an aesthetic-based rating; automatically extracting a plurality of visual features representative of the received image; computing a familiarity measure for the received image by correlating the visual features extracted from the received image to the visual features extracted from the other images; determining an aesthetic-based rating for the received image on the basis of the familiarity measure, wherein a lower familiarity is indicative of originality and a higher rating; and using one or more statistical methods to correlate the extracted visual features and the aesthetic-based ratings to classify the images on the basis of aesthetic value, rate the images on a scale relating to aesthetics value, or select/eliminate an image based upon aesthetic quality. 7. The method of claim 1 , further including the use of a naïve Bayes classifier to classify the image based on aesthetic-based rating. | 0.669118 |
7,644,286 | 1 | 15 | 1. A computer-implemented method of restricting data access, comprising: performing the following on a computer: detecting an attempt by a first requester to access a first data resource, said first requester comprising computer executable instructions for accessing data; if the attempted access is to retrieve data: allowing the attempted access; and adding a get token corresponding to the first data resource to a first set of get tokens maintained for the first requester; and if the attempted access is to send data: if said first set of get tokens is empty, allowing the attempted access; if said first set of get tokens includes only a single get token, allowing the attempted access if the first data resource is the same data resource corresponding to said single get token; and if said first set of get tokens includes multiple get tokens, restricting the attempted access if the first requestor previously sent data to the first data resource and said first set of get tokens has changed since the first requester last sent data to the first data resource. | 1. A computer-implemented method of restricting data access, comprising: performing the following on a computer: detecting an attempt by a first requester to access a first data resource, said first requester comprising computer executable instructions for accessing data; if the attempted access is to retrieve data: allowing the attempted access; and adding a get token corresponding to the first data resource to a first set of get tokens maintained for the first requester; and if the attempted access is to send data: if said first set of get tokens is empty, allowing the attempted access; if said first set of get tokens includes only a single get token, allowing the attempted access if the first data resource is the same data resource corresponding to said single get token; and if said first set of get tokens includes multiple get tokens, restricting the attempted access if the first requestor previously sent data to the first data resource and said first set of get tokens has changed since the first requester last sent data to the first data resource. 15. The method of claim 1 , wherein the first requestor comprises an electronic document. | 0.949718 |
9,525,746 | 1 | 2 | 1. A computer-implemented method of creating a user-specific playlist based on feedback received during playing of a song in a virtual environment, the method being implemented by a computer that includes one or more physical processors, the method comprising: receiving, by the computer, an instance of feedback about a song, from a user, during playing of the song in a virtual environment; determining, by the computer, a first situational context that corresponds to a first situation of an avatar of the user in the virtual environment at a time of receipt of the instance of feedback; populating, by the computer, a data structure with an entry for the instance of feedback, wherein the entry comprises, for the instance of feedback: (i) information identifying the song, and (ii) information corresponding to the first situational context; determining, by the computer, a second situational context that corresponds to a second situation of the avatar of the user in the virtual environment; and generating, by the computer, a playlist specific to the user in the virtual environment based on the instance of feedback responsive to a determination that the second situational context corresponds to the first situational context. | 1. A computer-implemented method of creating a user-specific playlist based on feedback received during playing of a song in a virtual environment, the method being implemented by a computer that includes one or more physical processors, the method comprising: receiving, by the computer, an instance of feedback about a song, from a user, during playing of the song in a virtual environment; determining, by the computer, a first situational context that corresponds to a first situation of an avatar of the user in the virtual environment at a time of receipt of the instance of feedback; populating, by the computer, a data structure with an entry for the instance of feedback, wherein the entry comprises, for the instance of feedback: (i) information identifying the song, and (ii) information corresponding to the first situational context; determining, by the computer, a second situational context that corresponds to a second situation of the avatar of the user in the virtual environment; and generating, by the computer, a playlist specific to the user in the virtual environment based on the instance of feedback responsive to a determination that the second situational context corresponds to the first situational context. 2. The computer-implemented method of claim 1 , wherein the instance of feedback comprises at least one of a command to repeat the song, or a command to increase volume of the song. | 0.797085 |
7,542,903 | 10 | 14 | 10. A system for determining predictive discourse function models comprising: an input/output circuit for retrieving a training corpus of speech utterances; and a processor for: determining prosodic features associated with speech utterances in the training corpus, determining discourse functions associated with the speech utterances in the training corpus, the discourse functions being determined automatically based on a theory of discourse analysis, and determining a predictive model for discourse functions by associating the prosodic features determined from the speech utterances in the training corpus with the discourse functions determined from the speech utterances in the training corpus, wherein the predictive model of discourse functions is used to predict from prosodic features of a specific recognized speech, a likelihood that speech utterances of the specific recognized speech reflect a specific discourse function, and wherein the predictive model of discourse functions is used to predict, based, at least in part, on the prosodic features, a likelihood of a first portion of a speech utterance being associated with a command directed at an application and a second portion of the speech utterance being associated with content being provided to the application. | 10. A system for determining predictive discourse function models comprising: an input/output circuit for retrieving a training corpus of speech utterances; and a processor for: determining prosodic features associated with speech utterances in the training corpus, determining discourse functions associated with the speech utterances in the training corpus, the discourse functions being determined automatically based on a theory of discourse analysis, and determining a predictive model for discourse functions by associating the prosodic features determined from the speech utterances in the training corpus with the discourse functions determined from the speech utterances in the training corpus, wherein the predictive model of discourse functions is used to predict from prosodic features of a specific recognized speech, a likelihood that speech utterances of the specific recognized speech reflect a specific discourse function, and wherein the predictive model of discourse functions is used to predict, based, at least in part, on the prosodic features, a likelihood of a first portion of a speech utterance being associated with a command directed at an application and a second portion of the speech utterance being associated with content being provided to the application. 14. The system of claim 10 , in which the prosodic features occur in at least one of a location: preceding, within and following the associated discourse function. | 0.694757 |
7,849,363 | 11 | 12 | 11. A computer-readable recording medium having recorded therein a program for supporting troubleshooting executed by analyzing logs created in a substrate processing apparatus that executes a specific type of processing on a processing target substrate in the event of trouble in said substrate processing apparatus, enabling a computer to execute: a keyword setting step in which a keyword file storage unit having stored therein a single keyword file or a plurality of keyword files with keyword constituted with character string set in advance, each corresponding to a single log or a plurality of logs related to a specific type of trouble that occurs in said substrate processing apparatus is searched for a single keyword file or a plurality of keyword files based upon input information provided via an input unit and a keyword to be used for log search, selected from a keyword file obtained through the search, is set; a category-specific log file setting step in which a category-specific log file to be used in log analysis, selected based upon input information provided via said input unit from a log file storage unit having stored therein a plurality of category-specific log files each holding a specific category of log created in said substrate processing apparatus, is set; an analysis log file creation step in which logs are extracted from said category-specific log file having been set, incorporated and sorted in time sequence, thereby creating an analysis log file; and a display control step in which said logs in said analysis log file are brought up on display at a display unit and each log containing said keyword having been set is obtained for a highlighted display by searching said analysis log file, wherein said keyword setting step searches said keyword file storage unit for a single keyword file or a plurality of keyword files specified based upon keyword file information input via said input unit and sets all said keywords contained in each keyword file obtained through the search as keywords to be used for log search. | 11. A computer-readable recording medium having recorded therein a program for supporting troubleshooting executed by analyzing logs created in a substrate processing apparatus that executes a specific type of processing on a processing target substrate in the event of trouble in said substrate processing apparatus, enabling a computer to execute: a keyword setting step in which a keyword file storage unit having stored therein a single keyword file or a plurality of keyword files with keyword constituted with character string set in advance, each corresponding to a single log or a plurality of logs related to a specific type of trouble that occurs in said substrate processing apparatus is searched for a single keyword file or a plurality of keyword files based upon input information provided via an input unit and a keyword to be used for log search, selected from a keyword file obtained through the search, is set; a category-specific log file setting step in which a category-specific log file to be used in log analysis, selected based upon input information provided via said input unit from a log file storage unit having stored therein a plurality of category-specific log files each holding a specific category of log created in said substrate processing apparatus, is set; an analysis log file creation step in which logs are extracted from said category-specific log file having been set, incorporated and sorted in time sequence, thereby creating an analysis log file; and a display control step in which said logs in said analysis log file are brought up on display at a display unit and each log containing said keyword having been set is obtained for a highlighted display by searching said analysis log file, wherein said keyword setting step searches said keyword file storage unit for a single keyword file or a plurality of keyword files specified based upon keyword file information input via said input unit and sets all said keywords contained in each keyword file obtained through the search as keywords to be used for log search. 12. A computer-readable recording medium according to claim 11 , wherein: in each keyword file, a character string indicating a specific type of trouble that occurs in said substrate processing apparatus and a keyword corresponding to a single log or a plurality of logs related to the particular trouble type is stored in correspondence to each trouble type; and said keyword setting step searches said keyword file storage unit for a single keyword file or a plurality of keyword files each corresponding to a specific type of trouble indicated by a character string matching character string information input via said input unit and then sets only a keyword set in relation to the trouble type among said keywords contained in said keyword file obtained through the search as a keyword to be used for log search. | 0.500612 |
3,938,103 | 17 | 19 | 17. A method for executing an interpretable language string and for executing one of a plurality of stored elementary language programs which is represented by a machine level code contained in said interpretable language string, comprising the steps of: a. storing in a first register a word address and a bit address within said word which represents the machine level operation code to be extracted from said interpretable language string; b. storing the word thus identified in a second register; c. shifting bits of the stored word from said second register to a third register and simultaneously incrementing said bit address in said first register; d. outputting the machine level operation code from said third register when a predetermined shift of said bits has occurred; e. locating the stored elementary language program which is represented by the extracted machine level code; f. extracting an elementary language operation code from said elementary language program as located; g. decoding the extracted elementary language operation code; and h. executing the elementary operation which is represented by the elementary language operation code. | 17. A method for executing an interpretable language string and for executing one of a plurality of stored elementary language programs which is represented by a machine level code contained in said interpretable language string, comprising the steps of: a. storing in a first register a word address and a bit address within said word which represents the machine level operation code to be extracted from said interpretable language string; b. storing the word thus identified in a second register; c. shifting bits of the stored word from said second register to a third register and simultaneously incrementing said bit address in said first register; d. outputting the machine level operation code from said third register when a predetermined shift of said bits has occurred; e. locating the stored elementary language program which is represented by the extracted machine level code; f. extracting an elementary language operation code from said elementary language program as located; g. decoding the extracted elementary language operation code; and h. executing the elementary operation which is represented by the elementary language operation code. 19. A method as set forth in claim 17 which includes the step of updating said stored word address in said first register whenever all of the bits in the second register are shifted to said third register, and transferring the new word represented by the updated address to said second register. | 0.908951 |
8,630,919 | 13 | 14 | 13. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: receive a data record, the data record having associated activity information; retrieve an assertion model, wherein the assertion model comprises at least one assertion template having a data field, wherein the data field is associated with one of a plurality of scenarios and wherein the plurality of scenarios include an activity scenario; fill in the data field of the at least one assertion template with the associated activity information based at least in part on a determination that the scenario associated with the data field is an activity scenario to thereby generate an assertion describing the associated activity information; and publish a narrative based on the assertion. | 13. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: receive a data record, the data record having associated activity information; retrieve an assertion model, wherein the assertion model comprises at least one assertion template having a data field, wherein the data field is associated with one of a plurality of scenarios and wherein the plurality of scenarios include an activity scenario; fill in the data field of the at least one assertion template with the associated activity information based at least in part on a determination that the scenario associated with the data field is an activity scenario to thereby generate an assertion describing the associated activity information; and publish a narrative based on the assertion. 14. The at least one non-transitory computer-readable medium of claim 13 , wherein the at least one assertion template includes a grammatical pattern and a field name representing the data field. | 0.814639 |
8,526,577 | 9 | 14 | 9. A method of providing content at a speech-enabled automated system, the method comprising: storing a plurality of content items at an information store, wherein each of the plurality of content items is associated with an action-object; receiving a query at the information store from an interactive voice response system, wherein the information store is logically external to the interactive voice response system; determining whether a modification of content is in progress at the information store; determining, when the modification is in progress, whether to suspend processing of the query until the modification is complete; and processing the query after the modification is complete, in response to a determination to suspend the processing of the query. | 9. A method of providing content at a speech-enabled automated system, the method comprising: storing a plurality of content items at an information store, wherein each of the plurality of content items is associated with an action-object; receiving a query at the information store from an interactive voice response system, wherein the information store is logically external to the interactive voice response system; determining whether a modification of content is in progress at the information store; determining, when the modification is in progress, whether to suspend processing of the query until the modification is complete; and processing the query after the modification is complete, in response to a determination to suspend the processing of the query. 14. The method of claim 9 , further comprising: providing an answer to the interactive voice response system, wherein the answer is used as part of a response to a caller by the interactive voice response system. | 0.834116 |
8,311,835 | 12 | 13 | 12. The computer implemented method of claim 10 further comprising re-using, by the companion controls, logic and presentation capabilities of the primary controls by synchronizing values with the primary controls, the companion controls including a QA control, a command control, a compare validator control, and a custom validator control, wherein the QA control references prompt objects using a prompt property to perform the functions for output control. | 12. The computer implemented method of claim 10 further comprising re-using, by the companion controls, logic and presentation capabilities of the primary controls by synchronizing values with the primary controls, the companion controls including a QA control, a command control, a compare validator control, and a custom validator control, wherein the QA control references prompt objects using a prompt property to perform the functions for output control. 13. The computer implemented method of claim 12 further comprising: comparing two values by the compare validator according to an operator and initiating an action based on the comparison; and maintaining a library at the web server for providing visual, recognition and audible prompting markup information. | 0.934663 |
8,073,850 | 10 | 11 | 10. The method of claim 9 , further comprising responding to user selection of the link by causing content related to the key phrase to be displayed in a panel on the web page, said content including an advertisement associated with the key phrase and non-advertisement social media content associated with the key phrase. | 10. The method of claim 9 , further comprising responding to user selection of the link by causing content related to the key phrase to be displayed in a panel on the web page, said content including an advertisement associated with the key phrase and non-advertisement social media content associated with the key phrase. 11. The method of claim 10 , wherein the social media content includes a thumbnail image of a video on a social media site, said thumbnail image being selectable by a user to view the video in said panel. | 0.891949 |
9,443,169 | 1 | 3 | 1. A computer implemented method of classifying a digital image of an object, the method comprising: a) receiving a digital image of an object to be classified with a processor; and b) classifying the digital image with a constrained multiple-instance support vector machine (MI-SVM) classifier, the constrained MI-SVM classifier having been automatically trained using a plurality of training images, the training images including a plurality of object types from a plurality of viewpoints, each training image including an image of an object associated with one of the plurality of object types and one of the plurality of object viewpoints, an associated object type label and an associated viewpoint label, the constrained MI-SVM classifier trained by sampling each training image to generate a bag of image regions associated with each training image, discovering a discriminative image region associated with each training image, and generating a collection of discriminative image regions for each of the plurality of object types and each of the plurality of viewpoints, wherein the constrained MI-SVM classifier is trained using an iterative process that initially selects an initial discriminative image region for a first object type at the plurality of viewpoints and iteratively selects subsequent discriminative image regions of the first object type at the plurality of viewpoints where the selection of a subsequent discriminate image region is constrained by one or more characteristics of selected discriminative image regions associated with other viewpoints of the first object type. | 1. A computer implemented method of classifying a digital image of an object, the method comprising: a) receiving a digital image of an object to be classified with a processor; and b) classifying the digital image with a constrained multiple-instance support vector machine (MI-SVM) classifier, the constrained MI-SVM classifier having been automatically trained using a plurality of training images, the training images including a plurality of object types from a plurality of viewpoints, each training image including an image of an object associated with one of the plurality of object types and one of the plurality of object viewpoints, an associated object type label and an associated viewpoint label, the constrained MI-SVM classifier trained by sampling each training image to generate a bag of image regions associated with each training image, discovering a discriminative image region associated with each training image, and generating a collection of discriminative image regions for each of the plurality of object types and each of the plurality of viewpoints, wherein the constrained MI-SVM classifier is trained using an iterative process that initially selects an initial discriminative image region for a first object type at the plurality of viewpoints and iteratively selects subsequent discriminative image regions of the first object type at the plurality of viewpoints where the selection of a subsequent discriminate image region is constrained by one or more characteristics of selected discriminative image regions associated with other viewpoints of the first object type. 3. The computer implemented method of classifying a digital image according to claim 1 , wherein the plurality of object types are associated with a plurality of vehicle types. | 0.913129 |
9,213,885 | 16 | 17 | 16. The method of claim 3 , further comprising: performing a lighting correction on one or more of said plurality of transform coefficients prior to classifying said 2D image. | 16. The method of claim 3 , further comprising: performing a lighting correction on one or more of said plurality of transform coefficients prior to classifying said 2D image. 17. The method of claim 16 , wherein said performing includes one or more of the following: adjusting a value of each of said plurality of transform coefficients as a function of other transform coefficients in said wavelet transform; linearly scaling an intensity of one or more of said plurality of transform coefficients; and scaling the intensity of one or more of said plurality of transform coefficients with reference to a coefficient with the brightest intensity. | 0.833569 |
9,003,393 | 14 | 17 | 14. A system for providing HyperText Markup Language (HTML) directed adaptive features for a mobile application, the system comprising: an application server providing access to an application database through an application marketplace service; a server including a remote file manifest; a mobile device having a processor configured to: downloading the mobile application from an application marketplace, the mobile application including a local file manifest and a native binary including all of executable binary code of the mobile application; execute, by the processor, the native binary of the mobile application, the native binary implementing a plurality of Uniform Resource Locator (URL) handlers each registered to a function of the mobile application; determine, by the processor, the local file manifest of the mobile application needs to be updated, the local file manifest referencing a HTML document including a plurality of URLs associated with a subset of the plurality of URL handlers; update, by the processor, the local file manifest of the mobile application from a remote server without updating any of the executable binary code of the mobile application, the updating modifying the plurality of URLs in the HTML document; render, by the processor, the HTML document from the updated local file manifest on a display. | 14. A system for providing HyperText Markup Language (HTML) directed adaptive features for a mobile application, the system comprising: an application server providing access to an application database through an application marketplace service; a server including a remote file manifest; a mobile device having a processor configured to: downloading the mobile application from an application marketplace, the mobile application including a local file manifest and a native binary including all of executable binary code of the mobile application; execute, by the processor, the native binary of the mobile application, the native binary implementing a plurality of Uniform Resource Locator (URL) handlers each registered to a function of the mobile application; determine, by the processor, the local file manifest of the mobile application needs to be updated, the local file manifest referencing a HTML document including a plurality of URLs associated with a subset of the plurality of URL handlers; update, by the processor, the local file manifest of the mobile application from a remote server without updating any of the executable binary code of the mobile application, the updating modifying the plurality of URLs in the HTML document; render, by the processor, the HTML document from the updated local file manifest on a display. 17. The system of claim 14 , wherein the modifying of the plurality of URLs is by modifying a URL from the plurality of URLs. | 0.743852 |
9,170,994 | 10 | 11 | 10. A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising: performing speech recognition to perform speech recognition of speech in source language to obtain a recognition result text as a result of the speech recognition; dividing the recognition result text into a plurality of parts to obtain a plurality of source language strings for translating from the source language into target language; translating the plurality of source language strings into a plurality of target language strings in a chronological order, the plurality of target language strings including a first target language strings and one or more second language string which chronologically precedes the first target language string; detecting ambiguity in interpretation of the speech corresponding to the first target language string, based on a relationship between the first target language string and the second target language strings; and adding an additional phrase to the first target language string if ambiguity is detected, the additional phrase being one of words and phrases to interpret uniquely a modification relationship between the first target language string and the second target language strings. | 10. A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising: performing speech recognition to perform speech recognition of speech in source language to obtain a recognition result text as a result of the speech recognition; dividing the recognition result text into a plurality of parts to obtain a plurality of source language strings for translating from the source language into target language; translating the plurality of source language strings into a plurality of target language strings in a chronological order, the plurality of target language strings including a first target language strings and one or more second language string which chronologically precedes the first target language string; detecting ambiguity in interpretation of the speech corresponding to the first target language string, based on a relationship between the first target language string and the second target language strings; and adding an additional phrase to the first target language string if ambiguity is detected, the additional phrase being one of words and phrases to interpret uniquely a modification relationship between the first target language string and the second target language strings. 11. The medium according to claim 10 , further comprising generating the additional phrase in accordance with a type of the detected ambiguity. | 0.842857 |
7,694,145 | 1 | 2 | 1. A computer-implemented method for presenting status of digital signatures, the method comprising: receiving a digital document that defines a presentation structure and includes a digital signature, the digital document specifying a representation of the digital signature and a location in the presentation structure for the representation of the digital signature; determining a status for the digital signature; associating a status representation with the digital signature, the status representation identifying the status determined for the digital signature; without altering the representation of the digital signature, presenting at least a portion of the digital document and the status representation of the digital signature in a user interface, the status representation being presented in the presentation structure at a location that depends upon the location in the presentation structure for the representation of the digital signature; and presenting information in the user interface about the status determined for the digital signature in response to a user input, wherein the user input comprises an indication of a selection of the digital signature in the user interface. | 1. A computer-implemented method for presenting status of digital signatures, the method comprising: receiving a digital document that defines a presentation structure and includes a digital signature, the digital document specifying a representation of the digital signature and a location in the presentation structure for the representation of the digital signature; determining a status for the digital signature; associating a status representation with the digital signature, the status representation identifying the status determined for the digital signature; without altering the representation of the digital signature, presenting at least a portion of the digital document and the status representation of the digital signature in a user interface, the status representation being presented in the presentation structure at a location that depends upon the location in the presentation structure for the representation of the digital signature; and presenting information in the user interface about the status determined for the digital signature in response to a user input, wherein the user input comprises an indication of a selection of the digital signature in the user interface. 2. The method of claim 1 , wherein: determining a status for the digital signature includes selecting a status from a plurality of predefined statuses. | 0.929241 |
8,607,155 | 16 | 17 | 16. A device, comprising a processor configured to present to a user a graphical interface for displaying and managing arrays of documents, the graphical interface comprising: a first display area that is operable to display a first axis of information elements; a second display area that is operable to display a second axis of information elements, the first axis of information elements and the second axis of information elements being adapted to be acted upon independently from one another, the first axis of information elements and the second axis of information elements being further adapted to be grouped together on a basis of a user input; a first command that is operable to group the first axis of information elements and the second axis of information elements in a group of axes of information elements, the group of axes of information elements being adapted to collectively perform an action on the first axis of information elements and the second axis of information elements; and a third display area that is operable to display the group of axes of information elements, the first axis of information elements being adapted to graphically represent information elements therein along a first substantially rectilinear arrangement and the second axis of information elements being adapted to graphically represent information elements therein along a second substantially rectilinear arrangement, a second command that is operable to ungroup the first axis of information elements and the second axis of information elements from the group of axes of information elements, the first axis of information elements and the second axis of information elements from the group of axes of information elements being adapted to be ungrouped on a basis of a user input. | 16. A device, comprising a processor configured to present to a user a graphical interface for displaying and managing arrays of documents, the graphical interface comprising: a first display area that is operable to display a first axis of information elements; a second display area that is operable to display a second axis of information elements, the first axis of information elements and the second axis of information elements being adapted to be acted upon independently from one another, the first axis of information elements and the second axis of information elements being further adapted to be grouped together on a basis of a user input; a first command that is operable to group the first axis of information elements and the second axis of information elements in a group of axes of information elements, the group of axes of information elements being adapted to collectively perform an action on the first axis of information elements and the second axis of information elements; and a third display area that is operable to display the group of axes of information elements, the first axis of information elements being adapted to graphically represent information elements therein along a first substantially rectilinear arrangement and the second axis of information elements being adapted to graphically represent information elements therein along a second substantially rectilinear arrangement, a second command that is operable to ungroup the first axis of information elements and the second axis of information elements from the group of axes of information elements, the first axis of information elements and the second axis of information elements from the group of axes of information elements being adapted to be ungrouped on a basis of a user input. 17. The device of claim 16 , wherein the group of axes of information elements is a first group of axes of information elements, the method further comprising displaying a second group of axes of information elements, the second group of axes of information elements being adapted to display at least one axis of information elements. | 0.637744 |
9,679,107 | 4 | 5 | 4. The method of claim 1 , wherein transmitting the structured data set comprises transmitting at least one clarification request generated by the medical documentation system, the at least one clarification request requesting clarification regarding at least one first medical fact of the one or more medical facts that the medical documentation selected to transmit to the CDI system for review and/or regarding at least a portion of the text documenting the patient encounter from which the at least one first medical fact was extracted by the medical documentation system. | 4. The method of claim 1 , wherein transmitting the structured data set comprises transmitting at least one clarification request generated by the medical documentation system, the at least one clarification request requesting clarification regarding at least one first medical fact of the one or more medical facts that the medical documentation selected to transmit to the CDI system for review and/or regarding at least a portion of the text documenting the patient encounter from which the at least one first medical fact was extracted by the medical documentation system. 5. The method of claim 4 , further comprising an act of: with the medical documentation system, receiving a clarification response from the CDI system addressing the at least one clarification request. | 0.954214 |
8,843,852 | 16 | 17 | 16. The method of claim 15 , wherein the medical file is accessed from the clearinghouse and displayed with a selectable graphical indicator of proximate areas of the selected annotation which, when selected, render the selected annotation. | 16. The method of claim 15 , wherein the medical file is accessed from the clearinghouse and displayed with a selectable graphical indicator of proximate areas of the selected annotation which, when selected, render the selected annotation. 17. The method of claim 16 , wherein rendering the selected annotation comprises playing an audio comment. | 0.973619 |
9,552,420 | 11 | 13 | 11. A method of providing search results comprising: receiving a first signal indicative of a first query; identifying user sessions of a search history log that comprise at least one search query similar to the first query; generating a surrogate document derived from the search history log and based on the identified user sessions, the surrogate document describing: at least one document; one or more queries related to the first query and associated with the at least one document; and one or more corresponding actions associated with each of the one or more queries by a set of multiple users, said one or more queries and one or more corresponding actions associated with the at least one document in the search history log; generating attributes from the surrogate document; ranking a first set of documents described in the search history log based on the attributes to generate a ranked first set of documents; and transmitting a second signal indicative of the ranked first set of documents. | 11. A method of providing search results comprising: receiving a first signal indicative of a first query; identifying user sessions of a search history log that comprise at least one search query similar to the first query; generating a surrogate document derived from the search history log and based on the identified user sessions, the surrogate document describing: at least one document; one or more queries related to the first query and associated with the at least one document; and one or more corresponding actions associated with each of the one or more queries by a set of multiple users, said one or more queries and one or more corresponding actions associated with the at least one document in the search history log; generating attributes from the surrogate document; ranking a first set of documents described in the search history log based on the attributes to generate a ranked first set of documents; and transmitting a second signal indicative of the ranked first set of documents. 13. The method of claim 11 , wherein ranking each document of the first set of document results comprises executing a machine learned ranking function using the feature values. | 0.851602 |
9,454,696 | 5 | 7 | 5. A receiving device comprising: an optical scanner receiving a document comprising raster images; and a processor operatively connected to said optical scanner, said processor automatically identifying topical items within said raster images based only on distinct font styles of images of text characters in said raster images, said images of text characters being pixel-based and being distinct from recognized characters produced in optical character recognition processing, said processor automatically ranking said topical items based on previously established rules for identifying topical sections in documents, said processor automatically filtering said topical items based on said ranking to identify highest-ranking topical items, said processor automatically associating said highest-ranking topical items with topics and subtopics in said document based on said previously established rules, said processor automatically cropping said highest-ranking topical items from said raster images by copying pixel patterns of said topical items within said raster images to produce cropped-image portions of said raster images, said processor automatically creating a cropped-image index for said document by combining said cropped-image portions of said raster images organized by said topics and subtopics, said cropped-image index comprising multiple ones of said cropped-image portions combined together and organized by said topics and subtopics, and said processor outputting said cropped-image index. | 5. A receiving device comprising: an optical scanner receiving a document comprising raster images; and a processor operatively connected to said optical scanner, said processor automatically identifying topical items within said raster images based only on distinct font styles of images of text characters in said raster images, said images of text characters being pixel-based and being distinct from recognized characters produced in optical character recognition processing, said processor automatically ranking said topical items based on previously established rules for identifying topical sections in documents, said processor automatically filtering said topical items based on said ranking to identify highest-ranking topical items, said processor automatically associating said highest-ranking topical items with topics and subtopics in said document based on said previously established rules, said processor automatically cropping said highest-ranking topical items from said raster images by copying pixel patterns of said topical items within said raster images to produce cropped-image portions of said raster images, said processor automatically creating a cropped-image index for said document by combining said cropped-image portions of said raster images organized by said topics and subtopics, said cropped-image index comprising multiple ones of said cropped-image portions combined together and organized by said topics and subtopics, and said processor outputting said cropped-image index. 7. The receiving device according to claim 5 , pages of said cropped-image index each comprising a different combination of said topical items from any individual pages of said document. | 0.736544 |
9,514,470 | 8 | 13 | 8. A method for facilitating the searching of personal information items comprising: identifying a search query for searching a plurality of personal information items entered through a search element in a user interface to a personal information service; identifying, based at least in part on the search query, a search suggestion for searching the plurality of personal information items and a contact suggestion; identifying, based at least in part on the search query, an event suggestion by examining at least one personal information item included in search results associated with the search query for an indication of an event and searching a plurality of events for at least one scheduled event that satisfies event criteria comprising the indication of the event, wherein the event suggestion comprises at least the one scheduled event; presenting at least the event suggestion, the search suggestion and the contact suggestion through a suggestion element in the user interface; and in response to a selection of the contact suggestion, presenting associated contact details while persisting the presentation of at least the search suggestion through the suggestion element in the user interface. | 8. A method for facilitating the searching of personal information items comprising: identifying a search query for searching a plurality of personal information items entered through a search element in a user interface to a personal information service; identifying, based at least in part on the search query, a search suggestion for searching the plurality of personal information items and a contact suggestion; identifying, based at least in part on the search query, an event suggestion by examining at least one personal information item included in search results associated with the search query for an indication of an event and searching a plurality of events for at least one scheduled event that satisfies event criteria comprising the indication of the event, wherein the event suggestion comprises at least the one scheduled event; presenting at least the event suggestion, the search suggestion and the contact suggestion through a suggestion element in the user interface; and in response to a selection of the contact suggestion, presenting associated contact details while persisting the presentation of at least the search suggestion through the suggestion element in the user interface. 13. The method of claim 8 wherein identifying the contact suggestion based at least in part on the search query comprises: examining at least one personal information item included in search results associated with the search query for an identity of at least one person; and searching a plurality of contacts for at least one contact that satisfies contact criteria comprising the identity of at least the one person, wherein the contact suggestion comprises at least the one contact. | 0.711653 |
9,087,332 | 11 | 15 | 11. A non-transitory computer readable medium comprising a set of instructions for adaptive display of an advertisement to look-alike users using a desired user profile dataset which, when executed by a computer, cause the computer to perform actions of: obtaining a plurality of known user profiles of known users who have been recorded to interact with an advertiser, wherein each of the plurality of known user profiles includes: historical components reflecting a stream of events of the known user prior to a current time, and a temporary component reflecting a state of the known user at the current time; automatically creating a plurality of desired user profiles of desired users who are not included in the plurality of known user profiles, wherein each of the plurality of the desired user profiles includes historical components reflecting a stream of events of the desired user prior to the current time, and a temporary component reflecting a state of the desired user at the current time; scoring, with a machine-learned model, similarities between the plurality of desired user profiles with the plurality of known user profiles based on the temporal component of the plurality of known user profile and the temporal component of the plurality of desired user profile for adapting to changes of user behavior; selecting, by a computer, a plurality of predicted users from the desired users based on the score of the plurality of desired user profile and; and serving an advertisement to the predicted user. | 11. A non-transitory computer readable medium comprising a set of instructions for adaptive display of an advertisement to look-alike users using a desired user profile dataset which, when executed by a computer, cause the computer to perform actions of: obtaining a plurality of known user profiles of known users who have been recorded to interact with an advertiser, wherein each of the plurality of known user profiles includes: historical components reflecting a stream of events of the known user prior to a current time, and a temporary component reflecting a state of the known user at the current time; automatically creating a plurality of desired user profiles of desired users who are not included in the plurality of known user profiles, wherein each of the plurality of the desired user profiles includes historical components reflecting a stream of events of the desired user prior to the current time, and a temporary component reflecting a state of the desired user at the current time; scoring, with a machine-learned model, similarities between the plurality of desired user profiles with the plurality of known user profiles based on the temporal component of the plurality of known user profile and the temporal component of the plurality of desired user profile for adapting to changes of user behavior; selecting, by a computer, a plurality of predicted users from the desired users based on the score of the plurality of desired user profile and; and serving an advertisement to the predicted user. 15. The non-transitory computer readable medium of claim 11 , wherein the scoring of the similarities is based on a clustering model. | 0.760791 |
8,396,709 | 20 | 21 | 20. A system comprising: one or more processors; and a computer-readable medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the system to perform operations comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. | 20. A system comprising: one or more processors; and a computer-readable medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the system to perform operations comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. 21. The system of claim 20 , wherein identifying the multiple sets of weighting values for the plurality of language models comprises identifying multiple sets of weighting values, each set of weighting values indicating probabilities that the respective language models of the plurality of language models will indicate a correct transcription for speech when a key phrase associated with the set of weighting values occurs in the speech. | 0.827437 |
7,526,735 | 1 | 9 | 1. A method of aiding a visual search in a list of learnable speech commands by making less frequently-used commands more salient and more frequently-used commands less salient comprising: presenting a display list of commands to a user; monitoring whether the user has uttered one of said commands; measuring an evidentiary value related to the utterance of said uttered one of said commands, wherein said measuring comprises determining an initial time that a previous utterance uttered by the user ended, determining a succeeding time that the utterance of said uttered one of said commands started, and computing a time elapsed between the initial and succeeding times, said evidentiary value being the time elapsed between the initial and succeeding times, said evidentiary value being the time elapsed between the end of a previous utterance and the start of the utterance of said uttered one of said commands; comparing the measured evidentiary value to a programmed value; if the measured evidentiary value is less than the programmed value, decreasing a salience of the command; and if the measured evidentiary value is equal to or greater than the programmed value, maintaining the salience of the command unchanged or increasing the salience of the command. | 1. A method of aiding a visual search in a list of learnable speech commands by making less frequently-used commands more salient and more frequently-used commands less salient comprising: presenting a display list of commands to a user; monitoring whether the user has uttered one of said commands; measuring an evidentiary value related to the utterance of said uttered one of said commands, wherein said measuring comprises determining an initial time that a previous utterance uttered by the user ended, determining a succeeding time that the utterance of said uttered one of said commands started, and computing a time elapsed between the initial and succeeding times, said evidentiary value being the time elapsed between the initial and succeeding times, said evidentiary value being the time elapsed between the end of a previous utterance and the start of the utterance of said uttered one of said commands; comparing the measured evidentiary value to a programmed value; if the measured evidentiary value is less than the programmed value, decreasing a salience of the command; and if the measured evidentiary value is equal to or greater than the programmed value, maintaining the salience of the command unchanged or increasing the salience of the command. 9. The method of claim 1 , wherein the saliency of the display of said uttered one of said commands is reduced by moving the uttered one of said commands from the display list of commands to an inactive location. | 0.502347 |
4,847,784 | 42 | 43 | 42. The method as claimed in claim 41, wherein said knowledge base includes rules concluding values for expressions, and said step (a) of operating said computer to scan the knowledge base includes determining a list of expressions concluded by the rules, said step (b) includes transmitting to the human user said list of expressions concluded by the rules, and step (c) includes receiving from the user a subset of the expressions included in said list, said step (d) includes interrupting the operation of the knowledge base interpreter each time when the knowledge base interpreter finds the value for an expression in said subset, said step (e) probes the subject system for information pertaining to the expression which had its value found and caused the interruption of said knowledge base interpreter. | 42. The method as claimed in claim 41, wherein said knowledge base includes rules concluding values for expressions, and said step (a) of operating said computer to scan the knowledge base includes determining a list of expressions concluded by the rules, said step (b) includes transmitting to the human user said list of expressions concluded by the rules, and step (c) includes receiving from the user a subset of the expressions included in said list, said step (d) includes interrupting the operation of the knowledge base interpreter each time when the knowledge base interpreter finds the value for an expression in said subset, said step (e) probes the subject system for information pertaining to the expression which had its value found and caused the interruption of said knowledge base interpreter. 43. The method as claimed in claim 42, wherein said rules have premises including factors which taken on values, and wherein said step (e) includes operating said computer to probe the subject system for the values of factors in rules which conclude values for the expression which had its value found and caused the interruption of said knowledge base interpreter. | 0.896189 |
9,977,802 | 18 | 19 | 18. The database system of claim 14 , the operations further comprising: loading one or more intermediate dictionary blocks, each of the one or more intermediate dictionary blocks containing one or more logical pointers to one or more value blocks of one or more of the multiple dictionary blocks for normal string values and/or one or more logical pointers to one or more large string dictionary blocks for large string values. | 18. The database system of claim 14 , the operations further comprising: loading one or more intermediate dictionary blocks, each of the one or more intermediate dictionary blocks containing one or more logical pointers to one or more value blocks of one or more of the multiple dictionary blocks for normal string values and/or one or more logical pointers to one or more large string dictionary blocks for large string values. 19. The database system of claim 18 , wherein the large string values are retrieved from the large string dictionary blocks. | 0.97696 |
8,793,593 | 1 | 5 | 1. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; receiving user interactions on one or more external systems, the user interactions including graph actions performed on a first set of graph objects by users of the social networking system; providing a social content product interface to a viewing user, the social content product interface including selectable links associated with the received user interactions on the one or more external systems, the social content product interface associated with a user profile object on the social networking system and provided for display to users of the social networking system; receiving a selection of a link of the selectable links from the viewing user to perform a graph action on a graph object on an external system associated with a particular user interaction of the received user interactions, the particular user interaction associated with a particular user; sending a request to the external system for the viewing user to perform the graph action on the graph object associated with the particular user interaction, the request including an instruction to the external system to execute user input associated with the graph action on a user device associated with the viewing user; and responsive to the request, receiving an indication from the external system that the user device associated with the viewing user executed the user input associated with the graph action performed on the graph object associated with the particular user interaction, and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. | 1. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; receiving user interactions on one or more external systems, the user interactions including graph actions performed on a first set of graph objects by users of the social networking system; providing a social content product interface to a viewing user, the social content product interface including selectable links associated with the received user interactions on the one or more external systems, the social content product interface associated with a user profile object on the social networking system and provided for display to users of the social networking system; receiving a selection of a link of the selectable links from the viewing user to perform a graph action on a graph object on an external system associated with a particular user interaction of the received user interactions, the particular user interaction associated with a particular user; sending a request to the external system for the viewing user to perform the graph action on the graph object associated with the particular user interaction, the request including an instruction to the external system to execute user input associated with the graph action on a user device associated with the viewing user; and responsive to the request, receiving an indication from the external system that the user device associated with the viewing user executed the user input associated with the graph action performed on the graph object associated with the particular user interaction, and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. 5. The method of claim 1 , further comprising: communicating the graph action performed on the graph object on the external system as a content item in a stream directed to one or more other users of the social networking system with whom the viewing user has established a connection. | 0.822097 |
9,727,925 | 25 | 27 | 25. A system, comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements a process for, identifying an internal social network for an enterprise, collecting a set of messages from the internal social network, performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise, performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages, identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points, as a result of the performed semantic analysis, clustering together messages that are similar to each other, categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages, associating each category of the plurality of categories with one or more tags, associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages, determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations, and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. | 25. A system, comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements a process for, identifying an internal social network for an enterprise, collecting a set of messages from the internal social network, performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise, performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages, identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points, as a result of the performed semantic analysis, clustering together messages that are similar to each other, categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages, associating each category of the plurality of categories with one or more tags, associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages, determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations, and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. 27. The system of claim 25 , in which the collected set of messages comprises business objects and conversations associated with the business objects. | 0.708171 |
8,275,662 | 1 | 16 | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. 16. The method of claim 1 , wherein when the selected geo-targeted area is zip code, then presenting platform(s) selection options for at least one a search engine and electronic commerce. | 0.922951 |
8,370,869 | 1 | 17 | 1. A non-transitory computer readable media containing digital information with at least one description record representing video content embedded within corresponding video information, the at least one description record generated by the method comprising: generating one or more video object descriptions from said video information using video object extraction processing; generating one or more video object hierarchy descriptions from said generated video object descriptions using object hierarchy construction and extraction processing, each video object hierarchy description describing at least one relationship between at least two objects in the video information; and generating one or more entity relation graph descriptions from said generated video object descriptions using entity relation graph generation processing, wherein said one or more generated entity relation graph descriptions describes non-hierarchical relationships between said objects associated with said one or more generated video object descriptions. | 1. A non-transitory computer readable media containing digital information with at least one description record representing video content embedded within corresponding video information, the at least one description record generated by the method comprising: generating one or more video object descriptions from said video information using video object extraction processing; generating one or more video object hierarchy descriptions from said generated video object descriptions using object hierarchy construction and extraction processing, each video object hierarchy description describing at least one relationship between at least two objects in the video information; and generating one or more entity relation graph descriptions from said generated video object descriptions using entity relation graph generation processing, wherein said one or more generated entity relation graph descriptions describes non-hierarchical relationships between said objects associated with said one or more generated video object descriptions. 17. The computer readable media of claim 1 , wherein said entity relation graph descriptions are based on relationships of video objects represented by said video object descriptions, wherein said relationships are selected from the group consisting of visual feature relationships, semantic feature relationships, temporal feature relationships and media feature relationships. | 0.501319 |
7,936,341 | 2 | 3 | 2. The method as recited in claim 1 , wherein the act of receiving a set of points comprises an act of receiving a set of coordinate locations on the multi-touch input display surface that were abstracted from areas of contact on the multi-touch input display surface. | 2. The method as recited in claim 1 , wherein the act of receiving a set of points comprises an act of receiving a set of coordinate locations on the multi-touch input display surface that were abstracted from areas of contact on the multi-touch input display surface. 3. The method as recited in claim 2 , wherein the act of receiving a set of coordinate locations on the multi-touch input display surface that were abstracted from areas of contact comprises an act of receiving a set of coordinate locations on the multi-touch input display surface that were abstracted from areas of contact between a human hand and the multi-touch input display surface. | 0.918385 |
8,566,340 | 1 | 4 | 1. A method that facilitates output of query suggestions responsive to receipt of a query, the method comprising: receiving the query from a user; locating a document in a document corpus based upon the query, the document comprising a phrase, the phrase having a first value and a second value assigned thereto, the first value being indicative of a number of documents from the document corpus that are retrievable when querying the document corpus using the phrase, the second value being indicative of a syntactic structure of the phrase, the first value being above a first threshold value and the second value being above a second threshold value; responsive to locating the document, selecting the phrase as a suggested query based at least in part upon the first value assigned to the phrase and the second value assigned to the phrase, wherein the selecting of the phrase as the suggested query is undertaken independent of a query log; and displaying the suggested query on a display screen of a computing device as a selectable graphical object, wherein selection of the suggested query from the user causes a search to be executed over the document corpus using the suggested query. | 1. A method that facilitates output of query suggestions responsive to receipt of a query, the method comprising: receiving the query from a user; locating a document in a document corpus based upon the query, the document comprising a phrase, the phrase having a first value and a second value assigned thereto, the first value being indicative of a number of documents from the document corpus that are retrievable when querying the document corpus using the phrase, the second value being indicative of a syntactic structure of the phrase, the first value being above a first threshold value and the second value being above a second threshold value; responsive to locating the document, selecting the phrase as a suggested query based at least in part upon the first value assigned to the phrase and the second value assigned to the phrase, wherein the selecting of the phrase as the suggested query is undertaken independent of a query log; and displaying the suggested query on a display screen of a computing device as a selectable graphical object, wherein selection of the suggested query from the user causes a search to be executed over the document corpus using the suggested query. 4. The method of claim 1 , further comprising: locating a first plurality of documents in the document corpus based upon the query; displaying first graphical data that identifies, respectively, the first plurality of documents on the display screen of the computing device; receiving a selection of the suggested query from the user; and displaying second graphical data that identifies, respectively, a second plurality of documents that are retrievable from the document corpus when querying the document corpus using the suggested query, the second graphical data displayed simultaneously with the first graphical data. | 0.651955 |
8,515,160 | 1 | 5 | 1. A method of actionable intelligence for detecting anomalous entities, comprising an act of initializing one or more processors to perform operations of: receiving an input signal; selecting a class of entities to be recognized; recognizing a set of entities of the selected class in the input signal using an Adaptive Resonance Theory (ART)-based neural network; selecting a set of threshold criteria by which a set of anomalous entities can be detected within the set of recognized entities; detecting the set of anomalous entities by comparing the set of recognized entities against the set of threshold criteria; alerting an operator to the presence of the set of anomalous entities, whereby anomalous entities are detected; prompting the operator to assign new labels to the set of anomalous entities; discovering underlying hierarchical relationships between the new labels assigned by the operator; and updating a knowledge database with the new labels and hierarchical relationships, whereby anomalous entities are classified and hierarchically related. | 1. A method of actionable intelligence for detecting anomalous entities, comprising an act of initializing one or more processors to perform operations of: receiving an input signal; selecting a class of entities to be recognized; recognizing a set of entities of the selected class in the input signal using an Adaptive Resonance Theory (ART)-based neural network; selecting a set of threshold criteria by which a set of anomalous entities can be detected within the set of recognized entities; detecting the set of anomalous entities by comparing the set of recognized entities against the set of threshold criteria; alerting an operator to the presence of the set of anomalous entities, whereby anomalous entities are detected; prompting the operator to assign new labels to the set of anomalous entities; discovering underlying hierarchical relationships between the new labels assigned by the operator; and updating a knowledge database with the new labels and hierarchical relationships, whereby anomalous entities are classified and hierarchically related. 5. The method of claim 1 , where in the operation of recognizing a set of entities, the entities recognized are selected from the group consisting of objects, spatial patterns, events and behaviors. | 0.870079 |
9,674,066 | 1 | 11 | 1. A method of extracting a desired status value related to a remotely monitored image output device, by a monitoring computer automatically without human intervention, wherein the monitoring computer is configured to communicate with the image output device using plural application-layer communication protocols, the method comprising: accessing a memory associated with the monitoring computer to determine, based on a vendor type of the image output device, a communication protocol of the plural application-layer communication protocols, to use to extract the desired status value from the image output device, the memory storing, for each of the plural application-layer communication protocols, information of at least one vendor, the accessing step determining which of the plural application-layer communication protocols can should be used to obtain the desired status value based on the information of at least one vendor stored in the memory and the vendor information of the image output device; accessing, by the monitoring computer, the image output device without human intervention using the determined communication protocol to obtain device information of the monitored image output device that is stored on the image output device; extracting the desired status value from the obtained device information; and storing the extracted desired status value. | 1. A method of extracting a desired status value related to a remotely monitored image output device, by a monitoring computer automatically without human intervention, wherein the monitoring computer is configured to communicate with the image output device using plural application-layer communication protocols, the method comprising: accessing a memory associated with the monitoring computer to determine, based on a vendor type of the image output device, a communication protocol of the plural application-layer communication protocols, to use to extract the desired status value from the image output device, the memory storing, for each of the plural application-layer communication protocols, information of at least one vendor, the accessing step determining which of the plural application-layer communication protocols can should be used to obtain the desired status value based on the information of at least one vendor stored in the memory and the vendor information of the image output device; accessing, by the monitoring computer, the image output device without human intervention using the determined communication protocol to obtain device information of the monitored image output device that is stored on the image output device; extracting the desired status value from the obtained device information; and storing the extracted desired status value. 11. The monitoring method of claim 1 , wherein when the determining step determines that an HTTP protocol is to be used to extract the desired status value, the method further includes determining, based on the vendor information and model information of the image output device, data extraction information for extracting the desired status value from the image output device, parsing the obtained device information according to the data extraction information to identify substrings related to the image output device, and extracting the desired status value based on the identified substrings. | 0.500836 |
8,495,742 | 17 | 18 | 17. A method for identifying attack-related queries made to a search engine, comprising: extracting a set of queries associated with suspect IP (Internet protocol) address from a plurality of search logs stored in a storage server; generating a plurality of regular expressions at a regular expression generator that capture variations of the set of queries, the regular expressions being assigned a score that measures the likelihood that a particular regular expression matches a random string; discarding the regular expressions that exceed the score; applying the regular expressions to the search logs to extract the attack-related queries from the search logs; and outputting the attack-related queries, the regular expressions, and the IP address. | 17. A method for identifying attack-related queries made to a search engine, comprising: extracting a set of queries associated with suspect IP (Internet protocol) address from a plurality of search logs stored in a storage server; generating a plurality of regular expressions at a regular expression generator that capture variations of the set of queries, the regular expressions being assigned a score that measures the likelihood that a particular regular expression matches a random string; discarding the regular expressions that exceed the score; applying the regular expressions to the search logs to extract the attack-related queries from the search logs; and outputting the attack-related queries, the regular expressions, and the IP address. 18. The method of claim 17 , further comprising feeding back the attack-related queries to extract a subsequent suspect IP address or a subsequent set of attack-related queries from the search logs. | 0.828125 |
9,235,848 | 1 | 8 | 1. A method comprising: receiving, by a computer processor, a set of data entities representing users' physical interactions with tangible real-world entities, wherein the tangible real-world entities include geographical locations and physical objects located at the geographical locations; providing a metadata collector to at least one user, wherein the metadata collector is associated with at least one metadata element; receiving user interaction data generated based on interaction between the at least one user and the metadata collector, wherein the user interaction data identifies at least one data entity of the set of data entities, wherein the at least one data entity is added to at least one user profile associated with the at least one user, and wherein the at least one user profile is created to describe the at least one user; attempting to validate a physical interaction of the user with at least one tangible real-world entity represented by the identified at least one data entity using one or more of the group consisting of: location data of the at least one user; photographs associated with the at least one user; the user interaction data; or any combination thereof, wherein the location data of the at least one user, the photographs associated with the at least one user, or the user interaction data indicate whether the user has been at geographical locations of the at least one tangible real-world entity; in an instance in which the physical interaction is validated, generating an association between the at least one metadata element and the at least one data entity, and the user profile associated with the at least one user; and evaluating the user interaction data and the user profile associated with the at least one user to determine an association weight of the generated association between the at least one metadata element and the at least one data entity added to the user profile associated with the at least one user, wherein the generated association either increases or decreases based on the determined association weight. | 1. A method comprising: receiving, by a computer processor, a set of data entities representing users' physical interactions with tangible real-world entities, wherein the tangible real-world entities include geographical locations and physical objects located at the geographical locations; providing a metadata collector to at least one user, wherein the metadata collector is associated with at least one metadata element; receiving user interaction data generated based on interaction between the at least one user and the metadata collector, wherein the user interaction data identifies at least one data entity of the set of data entities, wherein the at least one data entity is added to at least one user profile associated with the at least one user, and wherein the at least one user profile is created to describe the at least one user; attempting to validate a physical interaction of the user with at least one tangible real-world entity represented by the identified at least one data entity using one or more of the group consisting of: location data of the at least one user; photographs associated with the at least one user; the user interaction data; or any combination thereof, wherein the location data of the at least one user, the photographs associated with the at least one user, or the user interaction data indicate whether the user has been at geographical locations of the at least one tangible real-world entity; in an instance in which the physical interaction is validated, generating an association between the at least one metadata element and the at least one data entity, and the user profile associated with the at least one user; and evaluating the user interaction data and the user profile associated with the at least one user to determine an association weight of the generated association between the at least one metadata element and the at least one data entity added to the user profile associated with the at least one user, wherein the generated association either increases or decreases based on the determined association weight. 8. The method of claim 1 , wherein the association weight is based on factors including a determination of user expertise. | 0.921493 |
5,406,626 | 16 | 17 | 16. The device of claim 1, wherein the speech synthesizer includes means for generating a plurality of voices. | 16. The device of claim 1, wherein the speech synthesizer includes means for generating a plurality of voices. 17. The device of claim 16, wherein the means for generating a plurality of voices includes voice selection depending on a category of the selected data. | 0.882848 |
7,685,585 | 15 | 16 | 15. A computer implemented method comprising: creating a plurality of explicit control functions in a software library stored on a storage device, where said software library is operable with an implicit control application development environment (ADE) executed by a central processing unit (CPU) coupled to said storage device; relating each of said plurality of explicit control functions with a progression of implicit logic, wherein said progression is selected to programmatically perform one or more operations defined by said each of said plurality of explicit control functions; and exposing said plurality of explicit control functions to a developer using said implicit control ADE. | 15. A computer implemented method comprising: creating a plurality of explicit control functions in a software library stored on a storage device, where said software library is operable with an implicit control application development environment (ADE) executed by a central processing unit (CPU) coupled to said storage device; relating each of said plurality of explicit control functions with a progression of implicit logic, wherein said progression is selected to programmatically perform one or more operations defined by said each of said plurality of explicit control functions; and exposing said plurality of explicit control functions to a developer using said implicit control ADE. 16. The computer implemented method of claim 15 further comprising: defining one or more properties for ones of said plurality of explicit control functions, wherein said one or more properties are used by said progression in performing said one or more operations. | 0.781353 |
8,548,797 | 1 | 3 | 1. A computer-implemented method comprising: determining a particular language based at least in part on both content of text submitted by a user and a source IP address that is associated with the user; and based on having determined the particular language for the user, presenting, to the user, one or more content items that are associated with the particular language; wherein the content of the text does not expressly state the particular language. | 1. A computer-implemented method comprising: determining a particular language based at least in part on both content of text submitted by a user and a source IP address that is associated with the user; and based on having determined the particular language for the user, presenting, to the user, one or more content items that are associated with the particular language; wherein the content of the text does not expressly state the particular language. 3. The method of claim 1 , wherein determining the particular language comprises: determining a particular market based on a top-level domain of a particular URL; determining whether the text is encoded in ASCII; determining whether only one language is mapped to the particular market in a stored set of market-to-language mappings; determining whether the top-level domain is within a specified subset of top-level domains that consists only of “cn,” “tw,” “jp,” “kr,” and “hk”; and in response to determining that (a) the text is encoded in ASCII, (b) more than one language is mapped to the particular market in the stored set of market-to-language mappings, and (c) the top-level domain is within the specified subset of top-level domains, determining that the particular language is English. | 0.815509 |
10,055,391 | 9 | 11 | 9. A method, comprising: determining, by a computer, a first token of a plurality of tokens in an unstructured input document, the first token having a visual style; producing, by the computer, a first probability distribution of the first token across a plurality of classes, each class of the plurality of classes being related to a corresponding content of one or more of the plurality of tokens; modifying, by the computer, the first probability distribution to produce a second probability distribution of the first token across the plurality of classes, the second probability distribution being based on one or more classes of the plurality of classes, the one or more classes being likely to contain a plurality of surrounding tokens appearing near the first token in context of the input document; producing, by the computer, a third probability distribution of the first token across the plurality of classes, the third probability distribution being based on the visual style of the first token and the second probability distribution; determining, by the computer based at least on the third probability distribution, a classification of the first token into one of the plurality of classes; and forming, by the computer, a structured document from the first token and the classification. | 9. A method, comprising: determining, by a computer, a first token of a plurality of tokens in an unstructured input document, the first token having a visual style; producing, by the computer, a first probability distribution of the first token across a plurality of classes, each class of the plurality of classes being related to a corresponding content of one or more of the plurality of tokens; modifying, by the computer, the first probability distribution to produce a second probability distribution of the first token across the plurality of classes, the second probability distribution being based on one or more classes of the plurality of classes, the one or more classes being likely to contain a plurality of surrounding tokens appearing near the first token in context of the input document; producing, by the computer, a third probability distribution of the first token across the plurality of classes, the third probability distribution being based on the visual style of the first token and the second probability distribution; determining, by the computer based at least on the third probability distribution, a classification of the first token into one of the plurality of classes; and forming, by the computer, a structured document from the first token and the classification. 11. The method of claim 9 , further comprising: displaying, by the computer, the plurality of tokens on a video display; receiving, by the computer, an indication from an individual viewing the video display that a second token of the plurality of tokens has been misclassified; and reclassifying the second token into a different class according to the indication. | 0.843213 |
8,060,491 | 15 | 16 | 15. An apparatus for extracting semantic information from unstructured text associated with a plurality of content items, each content item having associated metadata, the apparatus comprising a processor and a memory device storing executable instructions thereon that when executed causes the processor to perform a method comprising: selecting an ordered set of scale values for a plurality of scales; determining for each scale value at least one subset of metadata related to a subset of the scale value; determining for each of the scales and associated subsets a statistic on occurrences of one or more content items from the subset of metadata, the statistic comprising a number of instances of the one or more content items in a respective scale and subset; aggregating the statistics for each scale and associated subsets and determining therefrom a semantic level for each scale and associated subsets; determining which of the plurality of scales correspond to the semantics of the one or more content items on the basis of the semantic level; identifying one or more clusters of scales having a semantic level that exceeds a threshold value of occurrences; and extracting semantic information from the metadata associated with the one or more content items of one or more identified cluster of scales. | 15. An apparatus for extracting semantic information from unstructured text associated with a plurality of content items, each content item having associated metadata, the apparatus comprising a processor and a memory device storing executable instructions thereon that when executed causes the processor to perform a method comprising: selecting an ordered set of scale values for a plurality of scales; determining for each scale value at least one subset of metadata related to a subset of the scale value; determining for each of the scales and associated subsets a statistic on occurrences of one or more content items from the subset of metadata, the statistic comprising a number of instances of the one or more content items in a respective scale and subset; aggregating the statistics for each scale and associated subsets and determining therefrom a semantic level for each scale and associated subsets; determining which of the plurality of scales correspond to the semantics of the one or more content items on the basis of the semantic level; identifying one or more clusters of scales having a semantic level that exceeds a threshold value of occurrences; and extracting semantic information from the metadata associated with the one or more content items of one or more identified cluster of scales. 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. | 0.767148 |
8,583,438 | 6 | 7 | 6. A method comprising: building, by a computer and based on text, a lattice comprising speech units, wherein each speech unit in the lattice is obtained from a database comprising a plurality of candidate speech units; finding, by the computer in the lattice, a sequence of speech units that conforms to the text; pruning, by the computer from the sequence of speech units, any of the speech units in the sequence that, based on likelihood ratios and a prosody model that was trained using actual speech, are detected to have unnatural prosody, where the prosody model exhibits a bias toward detecting unnatural prosody; iterating, by the computer, the finding and the pruning until completion that is based on a condition selected from a group of conditions comprising: 1) every speech unit in the sequence corresponding to natural prosody, and 2) iterating a maximum number of iterations. | 6. A method comprising: building, by a computer and based on text, a lattice comprising speech units, wherein each speech unit in the lattice is obtained from a database comprising a plurality of candidate speech units; finding, by the computer in the lattice, a sequence of speech units that conforms to the text; pruning, by the computer from the sequence of speech units, any of the speech units in the sequence that, based on likelihood ratios and a prosody model that was trained using actual speech, are detected to have unnatural prosody, where the prosody model exhibits a bias toward detecting unnatural prosody; iterating, by the computer, the finding and the pruning until completion that is based on a condition selected from a group of conditions comprising: 1) every speech unit in the sequence corresponding to natural prosody, and 2) iterating a maximum number of iterations. 7. The method of claim 6 further comprising concatenating, in response to the completion, the speech units of the sequence resulting in a speech waveform the corresponds to the text. | 0.830224 |
9,672,203 | 1 | 3 | 1. One or more non-transitory computer-readable storage media collectively storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to collectively perform operations comprising: determining at least a portion of a text string associated with an electronic book; determining one or more nouns in the text string; associating each of the one or more nouns with one or more characters so as to create a set of characters for the electronic book; determining one or more verbs in the text string, each of the one or more verbs representing an action between one of the characters of the set of characters and at least one other of the characters of the set of characters; generating a character graph that represents relationships between the one or more characters based at least in part upon the one or more verbs and the actions between the one or more characters, the one or more characters represented as nodes in the character graph; calculating a number of the nodes in the character graph; comparing the number of the nodes to a character threshold; and determining a maturity level of the electronic book based in part on the comparison of the character threshold with the number of the nodes in the character graph. | 1. One or more non-transitory computer-readable storage media collectively storing computer-executable instructions that, when executed by one or more computer systems, configure the one or more computer systems to collectively perform operations comprising: determining at least a portion of a text string associated with an electronic book; determining one or more nouns in the text string; associating each of the one or more nouns with one or more characters so as to create a set of characters for the electronic book; determining one or more verbs in the text string, each of the one or more verbs representing an action between one of the characters of the set of characters and at least one other of the characters of the set of characters; generating a character graph that represents relationships between the one or more characters based at least in part upon the one or more verbs and the actions between the one or more characters, the one or more characters represented as nodes in the character graph; calculating a number of the nodes in the character graph; comparing the number of the nodes to a character threshold; and determining a maturity level of the electronic book based in part on the comparison of the character threshold with the number of the nodes in the character graph. 3. The one or more non-transitory computer-readable storage media of claim 1 , wherein determining the maturity level of the electronic book comprises: comparing the one or more verbs with a dictionary of verbs, the dictionary comprising an association between the verbs and one or more maturity levels; and determining the maturity level of the electronic book based in part on the comparison of the one or more verbs with the maturity level of the one or more verbs in the dictionary of verbs. | 0.667339 |
9,454,582 | 8 | 9 | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding web site; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results. | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding web site; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results. 9. The system of claim 8 , wherein determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website comprises determining that a level of agreement between the onsite ranking score and the global ranking score does not satisfy a threshold. | 0.695857 |
9,977,633 | 12 | 13 | 12. The apparatus of claim 10 , wherein the respective weights are calculated based on user information which comprises at least one of a user identification, a user's department, a user's rank and a user's current project. | 12. The apparatus of claim 10 , wherein the respective weights are calculated based on user information which comprises at least one of a user identification, a user's department, a user's rank and a user's current project. 13. The apparatus of claim 12 , wherein the respective weights are calculated based on at least one of how soon the job request must be fulfilled and the user's information. | 0.916667 |
8,508,787 | 1 | 2 | 1. A method for translating documents with the use of a multifunctional printer machine, the method comprising: capturing an image of a document; determining regions of the document captured that include original text; performing optical character recognition of the regions of the document captured that include the original text; determining a source language corresponding to the original text directly on the multifunctional printer machine; displaying a plurality of target languages on the multifunctional printer machine; receiving a selected target language from a user in response to the displaying the plurality of target languages on the multifunctional printer machine, wherein the selected target language is selected from the plurality of target languages; performing language translation of the regions of the document captured that include the original text into translated text in accordance with the source language and the selected target language; displaying a plurality of page layout templates on the multifunctional printer machine; receiving one or more page layout templates from the user in response to the displaying the plurality of page layout templates on the multifunctional printer machine, wherein the one or more page layout templates are selected from the plurality of page layout templates, the one or more page layout templates having multiple pre designated areas for receiving the original text and the translated text; and outputting one or more printouts in accordance with the one or more page layout templates, the one or more printouts comprising (i) the original text in the source language and (ii) the translated text in the selected target language. | 1. A method for translating documents with the use of a multifunctional printer machine, the method comprising: capturing an image of a document; determining regions of the document captured that include original text; performing optical character recognition of the regions of the document captured that include the original text; determining a source language corresponding to the original text directly on the multifunctional printer machine; displaying a plurality of target languages on the multifunctional printer machine; receiving a selected target language from a user in response to the displaying the plurality of target languages on the multifunctional printer machine, wherein the selected target language is selected from the plurality of target languages; performing language translation of the regions of the document captured that include the original text into translated text in accordance with the source language and the selected target language; displaying a plurality of page layout templates on the multifunctional printer machine; receiving one or more page layout templates from the user in response to the displaying the plurality of page layout templates on the multifunctional printer machine, wherein the one or more page layout templates are selected from the plurality of page layout templates, the one or more page layout templates having multiple pre designated areas for receiving the original text and the translated text; and outputting one or more printouts in accordance with the one or more page layout templates, the one or more printouts comprising (i) the original text in the source language and (ii) the translated text in the selected target language. 2. The method according to claim 1 , wherein displaying the plurality of target languages on the multifunctional printer machine and displaying the plurality of page layout templates on the multifunctional printer machine comprise utilizing a menu setting of the multifunctional printer machine. | 0.723265 |
8,972,384 | 8 | 9 | 8. A computer-implemented method, comprising acts of: accessing a search results page, the search results page being generated in response to a search query and comprising a plurality of search results, wherein each of the plurality of search results comprise a title, a link to a corresponding webpage, and a snippet of information from the corresponding webpage, the snippet of information relating to the search query; inserting a label item in a search result of the plurality of search results of the search results page as part of the search result, wherein the search result relates to a target webpage; linking the label item to additional information relevant to the target webpage; obtaining the additional information in response to interaction with the label item; presenting the additional information as visually connected to the label item in a pop-up window or in an expansion object located proximate the label item; and utilizing a processor that executes instructions in memory to perform at least one of the acts of accessing, inserting, linking, obtaining, or presenting. | 8. A computer-implemented method, comprising acts of: accessing a search results page, the search results page being generated in response to a search query and comprising a plurality of search results, wherein each of the plurality of search results comprise a title, a link to a corresponding webpage, and a snippet of information from the corresponding webpage, the snippet of information relating to the search query; inserting a label item in a search result of the plurality of search results of the search results page as part of the search result, wherein the search result relates to a target webpage; linking the label item to additional information relevant to the target webpage; obtaining the additional information in response to interaction with the label item; presenting the additional information as visually connected to the label item in a pop-up window or in an expansion object located proximate the label item; and utilizing a processor that executes instructions in memory to perform at least one of the acts of accessing, inserting, linking, obtaining, or presenting. 9. The method of claim 8 , further comprising presenting data and actions as the information. | 0.837413 |
9,870,393 | 6 | 9 | 6. A computer-implemented method comprising: receiving a request to store data representing a graph including a plurality of nodes, at least one of the nodes having a single-valued property and a multi-valued property, the multi-valued property being a non-local property and including a reference to at least one adjacent node; storing the data in a table in a relational database, each of records in the table corresponding to one of the nodes, the storing comprising storing the at least one of the nodes in the corresponding record by: storing the single-valued property in a single-valued field, and storing the multi-valued property in a multi-valued field; receiving a graph query on the graph, the query including a traversal from a first node to a second node that is adjacent to the first node, converting the graph query into a structured query language (SQL) query over the first table and a second table; retrieving the multi-valued property of the first node from the first table and obtain data of the second node from the second table with the SQL query; storing, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node; transforming the adjacency list to a temporary table; and using the temporary table to locate the corresponding record. | 6. A computer-implemented method comprising: receiving a request to store data representing a graph including a plurality of nodes, at least one of the nodes having a single-valued property and a multi-valued property, the multi-valued property being a non-local property and including a reference to at least one adjacent node; storing the data in a table in a relational database, each of records in the table corresponding to one of the nodes, the storing comprising storing the at least one of the nodes in the corresponding record by: storing the single-valued property in a single-valued field, and storing the multi-valued property in a multi-valued field; receiving a graph query on the graph, the query including a traversal from a first node to a second node that is adjacent to the first node, converting the graph query into a structured query language (SQL) query over the first table and a second table; retrieving the multi-valued property of the first node from the first table and obtain data of the second node from the second table with the SQL query; storing, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node; transforming the adjacency list to a temporary table; and using the temporary table to locate the corresponding record. 9. The method of claim 6 , wherein the multi-valued property includes a plurality of atomic values, and wherein storing the multi-valued property comprises: generating a representation of the plurality of atomic values with a data type that is supported by the relational database; and storing the generated representation in the multi-valued field. | 0.702726 |
8,959,084 | 6 | 8 | 6. The method of claim 5 , wherein querying the repository using a smaller number of the one or more tokens comprises querying the repository with a plurality of permutations of the one or more tokens, wherein each permutation is formed by removing one of the one or more tokens. | 6. The method of claim 5 , wherein querying the repository using a smaller number of the one or more tokens comprises querying the repository with a plurality of permutations of the one or more tokens, wherein each permutation is formed by removing one of the one or more tokens. 8. The method of claim 6 , further comprising, weighting each permutation of the one or more tokens and using the weights to score results from querying the repository using each permutation. | 0.915933 |
8,565,486 | 11 | 12 | 11. The classification system of claim 1 , wherein said input is an imager configured to image a scene forward of a vehicle. | 11. The classification system of claim 1 , wherein said input is an imager configured to image a scene forward of a vehicle. 12. The classification system of claim 11 , wherein said object is classified as an OOI when it is determined said object is a headlight of an oncoming vehicle. | 0.945504 |
8,538,094 | 1 | 3 | 1. A Quality of Life (“QOL”) quantification system comprising: a QOL rules engine; a QOL measure datastore, wherein the QOL measure datastore comprises quantifiable measures of QOL factors; a change option datastore; and a QOL score data archive, wherein the QOL score data archive comprises QOL score data for other users; wherein the QOL rules engine comprises instructions for: receiving user data corresponding to a selected QOL factor of the user; obtaining measures of QOL from the QOL measure datastore that correspond to the selected QOL factor; evaluating the user data against the QOL measures of the selected QOL factor to determine a user score indicative of the degree of quality of the selected QOL factor of the user; receiving at least one change option selected from the change option datastore; applying the at least one selected change option to the selected QOL factor; and determining an enhanced user score after application of the at least one selected change option. | 1. A Quality of Life (“QOL”) quantification system comprising: a QOL rules engine; a QOL measure datastore, wherein the QOL measure datastore comprises quantifiable measures of QOL factors; a change option datastore; and a QOL score data archive, wherein the QOL score data archive comprises QOL score data for other users; wherein the QOL rules engine comprises instructions for: receiving user data corresponding to a selected QOL factor of the user; obtaining measures of QOL from the QOL measure datastore that correspond to the selected QOL factor; evaluating the user data against the QOL measures of the selected QOL factor to determine a user score indicative of the degree of quality of the selected QOL factor of the user; receiving at least one change option selected from the change option datastore; applying the at least one selected change option to the selected QOL factor; and determining an enhanced user score after application of the at least one selected change option. 3. The system of claim 1 wherein the measures of QOL are selected from the group consisting of sleep measures, relationship measures, mental health measures, nutrition measures, fitness measures, physical appearance measures, and physical health measures. | 0.575 |
9,607,436 | 16 | 21 | 16. A method to render augmented reality data on a computing device, comprising: sending, by the computing device to an augmented reality service, a context of the computing device, wherein the context includes information regarding the user's environment; receiving, from the augmented reality service, data representing clusters comprising one or more groupings of augmented reality data, the data generated based on the context and comprising formats for the clusters, wherein the formats are indicative of augmented reality data grouped in the clusters, and wherein each of the formats comprises sensory representations reflecting visual properties of grouped augmented reality data exhibited by each corresponding generated cluster in a form of avatars in a virtual image, wherein the sensory representations are different from any individual augmented reality data of the grouped augmented reality data in a respective cluster; generating, via the augmented reality service, at least one lower-level cluster for at least one of the clusters based on a respective format of the formats associated with the at least one lower-level cluster, wherein the respective format comprises sensory representations reflecting visual properties of a subset of the grouped augmented reality data corresponding to the at least one of the clusters of the at least one lower-level cluster; and rendering the clusters based on the received data. | 16. A method to render augmented reality data on a computing device, comprising: sending, by the computing device to an augmented reality service, a context of the computing device, wherein the context includes information regarding the user's environment; receiving, from the augmented reality service, data representing clusters comprising one or more groupings of augmented reality data, the data generated based on the context and comprising formats for the clusters, wherein the formats are indicative of augmented reality data grouped in the clusters, and wherein each of the formats comprises sensory representations reflecting visual properties of grouped augmented reality data exhibited by each corresponding generated cluster in a form of avatars in a virtual image, wherein the sensory representations are different from any individual augmented reality data of the grouped augmented reality data in a respective cluster; generating, via the augmented reality service, at least one lower-level cluster for at least one of the clusters based on a respective format of the formats associated with the at least one lower-level cluster, wherein the respective format comprises sensory representations reflecting visual properties of a subset of the grouped augmented reality data corresponding to the at least one of the clusters of the at least one lower-level cluster; and rendering the clusters based on the received data. 21. The method of claim 16 , wherein respective ones of the rendered formats comprise a simplified representation of the augmented reality data grouped in a respective cluster. | 0.904865 |
9,128,981 | 18 | 19 | 18. The method according to claim 16 , further comprising outputting the ranked plurality of records within a spatial mapping user interface. | 18. The method according to claim 16 , further comprising outputting the ranked plurality of records within a spatial mapping user interface. 19. The method according to claim 18 , further automatically searching a set of persistently stored transcripts and associated metadata with the at least one automated processor. | 0.951866 |
7,970,808 | 1 | 3 | 1. A method of classifying entities, the method comprising: using a processor to perform acts comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of features in contexts of said occurrences, a first one of the features being derived from a first context of a first one of the occurrences in a first one of the documents, and a second one of the features being derived from a second context of a second one of the occurrences in a second one of the documents; calculating a sum of a plurality of weights, wherein each of the features is associated with one of the weights; making a first determination that said sum exceeds a first threshold; making a second determination that a label applies to said entity based on said first determination; and storing or communicating a fact that said label applies to said entity, wherein said features comprise membership in a list, and wherein said acts further comprise: choosing a subset of members of said members of said list based on members in said subset being estimated to occur more frequently in said documents than other members of said list; and comparing a string that occurs in at least one of said contexts with members of said subset; and making a third determination that said string represents a member of said list, said third determination being made (a) based on said string's being among said subset, and (b) without use of a filter that accepts all strings that are members of said list and accepts at least one string that is not a member of said list. | 1. A method of classifying entities, the method comprising: using a processor to perform acts comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of features in contexts of said occurrences, a first one of the features being derived from a first context of a first one of the occurrences in a first one of the documents, and a second one of the features being derived from a second context of a second one of the occurrences in a second one of the documents; calculating a sum of a plurality of weights, wherein each of the features is associated with one of the weights; making a first determination that said sum exceeds a first threshold; making a second determination that a label applies to said entity based on said first determination; and storing or communicating a fact that said label applies to said entity, wherein said features comprise membership in a list, and wherein said acts further comprise: choosing a subset of members of said members of said list based on members in said subset being estimated to occur more frequently in said documents than other members of said list; and comparing a string that occurs in at least one of said contexts with members of said subset; and making a third determination that said string represents a member of said list, said third determination being made (a) based on said string's being among said subset, and (b) without use of a filter that accepts all strings that are members of said list and accepts at least one string that is not a member of said list. 3. The method of claim 1 , wherein said identifying comprises: determining that a surface form of a member of said list occurs in at least one of said contexts. | 0.846154 |
5,581,652 | 7 | 9 | 7. A wideband speech signal reconstruction method comprising: a first step wherein an input narrowband speech signal is spectrum-analyzed; a second step wherein the spectrum-analyzed results in said first step are vector-quantized using a narrowband speech signal codebook; a third step wherein the quantized values obtained in said second step are decoded to codevectors, using a wideband speech signal codebook; a fourth step wherein the codevectors decoded in said third step are spectrum-synthesized to a wideband speech signal; a fifth step wherein frequency components lower than the band of said input narrowband speech signal are extracted from said wideband speech signal obtained in said fourth step; a sixth step wherein said quantized values obtained in said second step are decoded to obtain a high-frequency speech signal, using a representative waveform codebook of a high-frequency speech signal higher than the band of said input narrowband speech signal; a seventh step wherein said input narrowband speech signal is up-sampled to compute sample values; and an eighth step wherein said lower-frequency components obtained in said fifth step, said high-frequency speech signal obtained in said sixth step and said sample values computed in said seventh step are added together to obtain a wideband speech signal. | 7. A wideband speech signal reconstruction method comprising: a first step wherein an input narrowband speech signal is spectrum-analyzed; a second step wherein the spectrum-analyzed results in said first step are vector-quantized using a narrowband speech signal codebook; a third step wherein the quantized values obtained in said second step are decoded to codevectors, using a wideband speech signal codebook; a fourth step wherein the codevectors decoded in said third step are spectrum-synthesized to a wideband speech signal; a fifth step wherein frequency components lower than the band of said input narrowband speech signal are extracted from said wideband speech signal obtained in said fourth step; a sixth step wherein said quantized values obtained in said second step are decoded to obtain a high-frequency speech signal, using a representative waveform codebook of a high-frequency speech signal higher than the band of said input narrowband speech signal; a seventh step wherein said input narrowband speech signal is up-sampled to compute sample values; and an eighth step wherein said lower-frequency components obtained in said fifth step, said high-frequency speech signal obtained in said sixth step and said sample values computed in said seventh step are added together to obtain a wideband speech signal. 9. The method of claim 7 further comprising a ninth step wherein the power of said lower-frequency components extracted in said fifth step is increased to a level corresponding to the power of said narrowband signal before being supplied to said eighth step, and a tenth step wherein the power of said high-frequency speech signal obtained in said sixth step is adjusted in accordance with the power of said input narrowband speech signal. | 0.604505 |
9,241,101 | 1 | 10 | 1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string. | 1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string. 10. The portable electronic device of claim 1 wherein the user-specified input string is used to specify an E-mail address, a social networking account identifier, a website URL or an image caption. | 0.775 |
9,483,591 | 12 | 13 | 12. The system of claim 8 wherein the processor is further configured to: generate a model for formal. | 12. The system of claim 8 wherein the processor is further configured to: generate a model for formal. 13. The system of claim 12 , further comprising generating an assertion for formal. | 0.965815 |
7,646,317 | 1 | 5 | 1. A decoding method for mapping a plurality of encoding sequences to a plurality of decoding sequences, each of the encoding sequences including at least one encoding symbol chosen from an encoding symbol set, each of decoding sequences including at least one decoding symbol chosen from a decoding symbol set which is used by non-logographic languages, the decoding method comprising the steps of: receiving an entered encoding symbol; and combining the entered encoding symbol to an end of an input sequence, wherein the input sequence is temporally ambiguous such that the input sequence has possibility to be interpreted as at least two different encoding sequence combinations, each of which includes at least one of the encoding sequences. | 1. A decoding method for mapping a plurality of encoding sequences to a plurality of decoding sequences, each of the encoding sequences including at least one encoding symbol chosen from an encoding symbol set, each of decoding sequences including at least one decoding symbol chosen from a decoding symbol set which is used by non-logographic languages, the decoding method comprising the steps of: receiving an entered encoding symbol; and combining the entered encoding symbol to an end of an input sequence, wherein the input sequence is temporally ambiguous such that the input sequence has possibility to be interpreted as at least two different encoding sequence combinations, each of which includes at least one of the encoding sequences. 5. The decoding method of claim 1 , wherein interpreting the input sequence is determined by a heuristic based on a linguistic model such that linguistic score calculation is capable of being applied on only a portion of the encoding sequence combinations. | 0.771429 |
9,965,545 | 1 | 4 | 1. A method for processing parse tree data, the method comprising: receiving, by a processor, a parse tree data structure, wherein the parse tree data structure is representative of a document object model (DOM) tree data structure; concomitant to receiving the parse tree data structure, receiving, by the processor, an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node; receiving, by the processor, a request to manipulate the parse tree data structure, wherein the request comprises an insert DOM node request for a new DOM node; concomitant to receiving the request to manipulate the parse tree data structure, receiving, by the processor, an indication of a parse tree insert location for the new DOM node to be inserted; responsive to receiving the indication of the parse tree insert location: assigning a distinguishable index value to the new DOM node to be inserted; and inserting the new DOM node at the indicated parse tree insert location; receiving, by the processor, a document order comparison request to determine an earlier of a first given DOM node and a second given DOM node; responsive to receiving the document order comparison request, determining whether the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node; responsive to determining that the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node based on the comparison of the index values of the first given DOM node and the second given DOM node; responsive to a determination that the document order comparison request cannot be satisfied by the comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node using a secondary comparison method; performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node; subsequent to receiving the parse tree data structure, storing an initially empty projection containing no associations of DOM nodes to binary tree nodes; responsive to receiving, by the processor, a delete DOM node request, deleting from the binary tree structure a corresponding binary tree node associated with the DOM node for which deletion was requested only when the DOM node has an associated binary tree node; responsive to receiving, by the processor, an insert DOM node request for a new DOM node, the processor identifies the binary tree insertion point location for the corresponding binary tree node associated with the new DOM node by: obtaining a pre-order traversal predecessor DOM node, denoted P, of the new DOM node; responsive to a determination P has an associated binary tree node, identifying a binary tree successor insertion location of the binary tree node associated with P; and responsive to a determination P does not have an associated binary tree node, determining the binary tree insertion point location using a specialized binary tree search using a value of the index of P; and subsequent to performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node, returning the projection and the binary tree data structure to an empty state. | 1. A method for processing parse tree data, the method comprising: receiving, by a processor, a parse tree data structure, wherein the parse tree data structure is representative of a document object model (DOM) tree data structure; concomitant to receiving the parse tree data structure, receiving, by the processor, an assignment of index values for the DOM nodes consisting of distinct index values for each existing DOM node; receiving, by the processor, a request to manipulate the parse tree data structure, wherein the request comprises an insert DOM node request for a new DOM node; concomitant to receiving the request to manipulate the parse tree data structure, receiving, by the processor, an indication of a parse tree insert location for the new DOM node to be inserted; responsive to receiving the indication of the parse tree insert location: assigning a distinguishable index value to the new DOM node to be inserted; and inserting the new DOM node at the indicated parse tree insert location; receiving, by the processor, a document order comparison request to determine an earlier of a first given DOM node and a second given DOM node; responsive to receiving the document order comparison request, determining whether the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node; responsive to determining that the document order comparison request can be satisfied by a comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node based on the comparison of the index values of the first given DOM node and the second given DOM node; responsive to a determination that the document order comparison request cannot be satisfied by the comparison of the index values of the first given DOM node and the second given DOM node, selecting as the earlier DOM node one of the first given DOM node and the second DOM node using a secondary comparison method; performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node; subsequent to receiving the parse tree data structure, storing an initially empty projection containing no associations of DOM nodes to binary tree nodes; responsive to receiving, by the processor, a delete DOM node request, deleting from the binary tree structure a corresponding binary tree node associated with the DOM node for which deletion was requested only when the DOM node has an associated binary tree node; responsive to receiving, by the processor, an insert DOM node request for a new DOM node, the processor identifies the binary tree insertion point location for the corresponding binary tree node associated with the new DOM node by: obtaining a pre-order traversal predecessor DOM node, denoted P, of the new DOM node; responsive to a determination P has an associated binary tree node, identifying a binary tree successor insertion location of the binary tree node associated with P; and responsive to a determination P does not have an associated binary tree node, determining the binary tree insertion point location using a specialized binary tree search using a value of the index of P; and subsequent to performing a re-index operation on the assignment of index values for the DOM nodes to assign distinct index values for each existing DOM node, returning the projection and the binary tree data structure to an empty state. 4. The method of claim 1 wherein a language processor determines whether to automatically perform a re-index operation using a structural change detector, wherein the structural change detector sets a flag that indicates insertion of nodes since a last index assignment occurred. | 0.923183 |
8,140,980 | 21 | 22 | 21. A system according to claim 18 , wherein the conference scheduling application is further configured to transmit a plurality of invitation messages to the participants, and to determine confirmation status of the conference session based upon response messages received from the participants in response to the invitation messages. | 21. A system according to claim 18 , wherein the conference scheduling application is further configured to transmit a plurality of invitation messages to the participants, and to determine confirmation status of the conference session based upon response messages received from the participants in response to the invitation messages. 22. A system according to claim 21 , wherein the invitation messages are transmitted over one of a plurality of transmission mechanisms including e-mail, page, instant messaging, and Internet Protocol (IP) telephony. | 0.92111 |
8,365,138 | 1 | 26 | 1. A process to use a computer to automatically translate a Formal Language Specification defining the functionality of a computer application program modeled in a Conceptual Model, into bug-free source code of a complete application program including a user interface and a database schema, said process comprising the steps of: A) using a computer to automatically check statements in said Formal Language Specification against the rules of syntax and semantics of a formal language in which said Formal Language Specification is expressed thereby validating said Formal Language Specification to ensure said Formal Language Specification is complete in that there is no missing information in said Formal Language Specification and to ensure said Formal Language Specification is correct in that primitives of said conceptual model are syntactically and semantically consistent and not ambiguous; B) translating said validated Formal Language Specification into computer readable source code which has the capability to control a computer to provide a user interface access mechanism to allow users to log in by entering at least identification data and to use said identification data to authenticate and validate a user as an instance of a class of the validated Formal Language Specification that act as agent in at least one agent relationship, said translating done using a computer to automatically retrieve information from said Formal Language Specification and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of the code generation structures in a proper order to write one or more source code files that implement said user interface access mechanism; C) translating said validated Formal Language Specification into computer readable code which has the capability to control a computer to provide a view of the system defining the set of objects and attributes the user can query and the set of services said user can execute, the content of said system view depending on the identity of said user accessing said application, said translating done using a computer to automatically retrieve information from said Formal Language Specification which expresses concepts in a Conceptual Model of said application in a Formal Language, and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of said one or more code generation structures in a proper order to write one or more source code files that implement said capability to control a computer to provide a view of said system defining the set of objects and attributes said user can query and the set of services said user can execute; and D) translating said validated Formal Language Specification into computer readable code which has the capability to control a computer to provide user interface interaction mechanisms to interact with and execute the functionality of the application in terms of performing queries on information managed by said application and executing services to modify the state of said information managed by said application, said services comprising events, local transactions and global transactions, said translating done using a computer to automatically retrieve information from said Formal Language Specification which expresses concepts in a Conceptual Model of said application in a Formal Language, and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of said one or more code generation structures in a proper order to write one or more source code files that implement said application with capability to control a computer to provide user interface interaction mechanism to interact with and execute the functionality of said application and allow a user of said application to launch said queries and services. | 1. A process to use a computer to automatically translate a Formal Language Specification defining the functionality of a computer application program modeled in a Conceptual Model, into bug-free source code of a complete application program including a user interface and a database schema, said process comprising the steps of: A) using a computer to automatically check statements in said Formal Language Specification against the rules of syntax and semantics of a formal language in which said Formal Language Specification is expressed thereby validating said Formal Language Specification to ensure said Formal Language Specification is complete in that there is no missing information in said Formal Language Specification and to ensure said Formal Language Specification is correct in that primitives of said conceptual model are syntactically and semantically consistent and not ambiguous; B) translating said validated Formal Language Specification into computer readable source code which has the capability to control a computer to provide a user interface access mechanism to allow users to log in by entering at least identification data and to use said identification data to authenticate and validate a user as an instance of a class of the validated Formal Language Specification that act as agent in at least one agent relationship, said translating done using a computer to automatically retrieve information from said Formal Language Specification and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of the code generation structures in a proper order to write one or more source code files that implement said user interface access mechanism; C) translating said validated Formal Language Specification into computer readable code which has the capability to control a computer to provide a view of the system defining the set of objects and attributes the user can query and the set of services said user can execute, the content of said system view depending on the identity of said user accessing said application, said translating done using a computer to automatically retrieve information from said Formal Language Specification which expresses concepts in a Conceptual Model of said application in a Formal Language, and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of said one or more code generation structures in a proper order to write one or more source code files that implement said capability to control a computer to provide a view of said system defining the set of objects and attributes said user can query and the set of services said user can execute; and D) translating said validated Formal Language Specification into computer readable code which has the capability to control a computer to provide user interface interaction mechanisms to interact with and execute the functionality of the application in terms of performing queries on information managed by said application and executing services to modify the state of said information managed by said application, said services comprising events, local transactions and global transactions, said translating done using a computer to automatically retrieve information from said Formal Language Specification which expresses concepts in a Conceptual Model of said application in a Formal Language, and storing said retrieved information in one or more code generation structures in memory of a computer, said code generation structures taking the form of class objects each of which has a code generation method, and using a method in a code generation class object to call the code generation method(s) of said one or more code generation structures in a proper order to write one or more source code files that implement said application with capability to control a computer to provide user interface interaction mechanism to interact with and execute the functionality of said application and allow a user of said application to launch said queries and services. 26. The process of claim 1 wherein the translating steps in step D further comprise retrieving information from said Formal Language Specification, said retrieved information being stored in said code generation structures so as to create code generation structures which are structured such that execution of code generation methods of said code generation structures generates computer readable source code which is structured to control a computer to allow a logged on user to execute one or more services of an instance of a class said logged on user is allowed to access and/or navigate to displays displaying information pertaining to other objects related with said instance of said class, said source code generated by execution of said code generation methods of said code generation structures being structured to control a computer to perform the following steps: display an Application Main Form containing a menu of services of objects or instances of said classes to which a user who has logged onto said application has privileges to access and services of which said user has privileges to execute, and, for each class the user who has logged on can access, generating and displaying a Query/Selection Form which allows said logged on user to query data instances of said class, search instances that fulfill a given filter condition, select objects of a class, and, for each selected object, observe instances related to said selected object and know which services for a given object said user has privileges to launch, and wherein, more specifically, said Query/Selection form having a visual component to show objects of a class which satisfy filter condition(s) set by said user with the attributes of said objects which are displayed determined by a Display Set user interface pattern selected and articulated by said designer, said Query/Selection form for each said class said user who logged in can access also having graphic items representing filters which have fields a user can fill in to supply filter criteria to allow said logged on user to filter objects in said class which will be displayed in said visual component, said Query/Selection form visual component allowing said user to control said computer to select an object that satisfies filter criteria, if any, and display services which said user can launch, and launch a service of a selected object said user requests to be launched, and said Query/Selection form visual component displaying links which allow a user to navigate to other data items related to the selected object thereby causing another Query/Selection Form to be displayed, said source code structured to control said computer to receive data regarding the previous object so that only data related to the initial object is displayed; for each service said user can launch, locate appropriate object server code in system logic code which has been automatically generated, said object server code being code which can control a computer to carry out said service, said source code also structured to control a computer to generate and display a Service Form that points to said object server code which can perform said service, said Service Form having an introduction field for each argument said user must provide to execute said service; supply initialization default values from said Formal Language Specification and/or values supplied by context from a recently visited objects list for some or all arguments if said designer has entered default values and/or if context values can be obtained, and/or receive user supplied values for some or all arguments needed to execute said service, and, if said user has supplied values for some or all of said arguments, check the user supplied values for each argument to ensure the data type and size is correct, the value is within an acceptable range for said argument and whether or not a null value is acceptable, and display a warning to said user if an argument's value fails any validation check; check dependencies between arguments, and, if a dependency is found to exist, display a form requesting said user to input data to satisfy said dependency and validate said data input by said user to ensure it has a valid data type, a proper size, and is within an acceptable range and whether a null value is acceptable if null; once all service arguments have been validated, and dependencies satisfied, send a message containing said service arguments to said object server code so as to launch said service; and wait for results from execution of said service, and display an error message if an error has occurred, otherwise wait for further user input. | 0.596493 |
7,992,079 | 3 | 6 | 3. The method of claim 1 , further including: receiving, at a content management application, a request to create updated content for a content page within said company website, wherein said updated content comprises components; creating said components according to said request; storing each of said components within a markup language file globally accessible by a reviewer, wherein said components are decoupled from said content page; and, creating an updated content page when each of said components has been authorized, wherein said updated content page does not include said components and comprises said content mapping data. | 3. The method of claim 1 , further including: receiving, at a content management application, a request to create updated content for a content page within said company website, wherein said updated content comprises components; creating said components according to said request; storing each of said components within a markup language file globally accessible by a reviewer, wherein said components are decoupled from said content page; and, creating an updated content page when each of said components has been authorized, wherein said updated content page does not include said components and comprises said content mapping data. 6. The method of claim 3 , wherein storing said components as said markup language file includes storing said markup language file in an extensible database that is platform and software independent. | 0.895812 |
8,713,445 | 1 | 6 | 1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified. | 1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified. 6. The method of claim 1 , wherein the response message includes a notification requesting additional description information from a user when the comparison result does not identify at least one of the generic user interface and adaptor. | 0.80067 |
9,262,719 | 11 | 12 | 11. The engine of claim 10 , wherein the sensor data represents human modalities. | 11. The engine of claim 10 , wherein the sensor data represents human modalities. 12. The engine of claim 11 , wherein the sensor data comprises at least one of the following modal data types: audible data, visual data, kinesthetic data, olfactory data, and taste data. | 0.93434 |
7,890,331 | 8 | 10 | 8. A method for automatically generating audio-visual summaries for audio-visual program content on a multimedia device, which method comprises: the multimedia device, locating a pre-generated text summary associated with the program content but not provided with the program content; synthesizing the selected text summary into speech; generating a video summary of the audio-visual program content; mixing the synthesized speech with the video summary. | 8. A method for automatically generating audio-visual summaries for audio-visual program content on a multimedia device, which method comprises: the multimedia device, locating a pre-generated text summary associated with the program content but not provided with the program content; synthesizing the selected text summary into speech; generating a video summary of the audio-visual program content; mixing the synthesized speech with the video summary. 10. A method according to claim 8 wherein locating and/or selecting a pre-generated text summary is performed according to the user preferences. | 0.717647 |
8,856,143 | 11 | 13 | 11. A system comprising: one or more server devices to: identify a plurality of geographically relevant strings in the document; retrieve a plurality of histograms respectively associated with the plurality of identified strings, each histogram relating occurrences of a particular identified string to geographic regions; combine the plurality of histograms associated with the plurality of identified strings to obtain a combined histogram for the document; and associate a particular geographic region with the document based on the combined histogram. | 11. A system comprising: one or more server devices to: identify a plurality of geographically relevant strings in the document; retrieve a plurality of histograms respectively associated with the plurality of identified strings, each histogram relating occurrences of a particular identified string to geographic regions; combine the plurality of histograms associated with the plurality of identified strings to obtain a combined histogram for the document; and associate a particular geographic region with the document based on the combined histogram. 13. The system of claim 11 , where the document includes a search query. | 0.938879 |
9,224,394 | 19 | 21 | 19. An interactive automated speech recognition system, comprising: a telematics processing system located in proximity to a person; a remote data center; a wireless link that transmits processed speech information from the processing system to the remote data center, wherein the processing system: receives in a first interaction an indication of intent from the person and, thereafter, in a second interaction that is separate from the first interaction, receives from the person a spoken utterance associated with the indicated intent wherein the spoken utterance associated with the indicated intent matches intended text of a type of intent available to the person; and processes the spoken utterance of the second interaction and transmits the processed speech information to the remote data center using the wireless link, wherein the transmitted processed speech information is analyzed to scale and end-point the speech utterance and is converted into packet data format; at least one optimal speech recognition engine selected to translate the converted speech information into text format, the at least one optimal speech recognition engine being selected from a set of speech recognition engines based upon the indicated intent; an internet protocol transport network that transports the converted speech information to the selected at least one optimal speech recognition engine; and wherein the at least one optimal speech recognition engine produces recognition results and an associated confidence score and, based upon the confidence score: an automated dialog is continued with the person if the confidence score meets or exceeds a pre-determined threshold for the best match; or at least one alternative speech recognition engine is selected to translate the converted speech information into text format if the confidence score is low such that it is below a pre-determined threshold for the best match. | 19. An interactive automated speech recognition system, comprising: a telematics processing system located in proximity to a person; a remote data center; a wireless link that transmits processed speech information from the processing system to the remote data center, wherein the processing system: receives in a first interaction an indication of intent from the person and, thereafter, in a second interaction that is separate from the first interaction, receives from the person a spoken utterance associated with the indicated intent wherein the spoken utterance associated with the indicated intent matches intended text of a type of intent available to the person; and processes the spoken utterance of the second interaction and transmits the processed speech information to the remote data center using the wireless link, wherein the transmitted processed speech information is analyzed to scale and end-point the speech utterance and is converted into packet data format; at least one optimal speech recognition engine selected to translate the converted speech information into text format, the at least one optimal speech recognition engine being selected from a set of speech recognition engines based upon the indicated intent; an internet protocol transport network that transports the converted speech information to the selected at least one optimal speech recognition engine; and wherein the at least one optimal speech recognition engine produces recognition results and an associated confidence score and, based upon the confidence score: an automated dialog is continued with the person if the confidence score meets or exceeds a pre-determined threshold for the best match; or at least one alternative speech recognition engine is selected to translate the converted speech information into text format if the confidence score is low such that it is below a pre-determined threshold for the best match. 21. The system of claim 19 , wherein the selected at least one optimal speech recognition engine is not local. | 0.6875 |
8,930,176 | 1 | 2 | 1. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive exposing of word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI); receiving a user selection of an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to the receiving, performing actions including: highlighting the of-interest word or phrase via the UI; finding a linked word in a second sentence of the bilingual sentence pair that corresponds to the of-interest word; and highlighting the linked word via the UI; and presenting to a user, via the UI, a control to reassign the highlighted word-alignment between the bilingual sentence pair. | 1. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive exposing of word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI); receiving a user selection of an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to the receiving, performing actions including: highlighting the of-interest word or phrase via the UI; finding a linked word in a second sentence of the bilingual sentence pair that corresponds to the of-interest word; and highlighting the linked word via the UI; and presenting to a user, via the UI, a control to reassign the highlighted word-alignment between the bilingual sentence pair. 2. One or more computer-readable storage devices as recited in claim 1 , wherein the finding and highlighting actions are performed while still concurrently displaying each sentence of the bilingual sentence pair via the UI. | 0.888335 |
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