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15. A computing system comprising a processor with access to a non-transitory computer-readable medium embodying one or more program components that configure the computing system to: detect selection of content within a page while the page is edited in an application, the content defined by markup code; responsive to input received by the application, automatically capture one or more stylistic changes to said content; responsive to capturing, automatically access a style data structure, the style data structure defined in a style sheet included in the page or in a separate style sheet file referenced by the page, wherein the style data structure comprises a plurality of style sheet rules, wherein each rule is applicable to one or more elements in the page to control an appearance of the one or more elements, and wherein the style sheet rules are logically distinct from the markup code defining the content; automatically search the style data structure for a style sheet rule defining a style having attributes that match said one or more stylistic changes; if a style sheet rule matching said one or more stylistic changes is found, automatically apply the discovered style sheet rule to said content by modifying markup defining a structural element of said web page corresponding to said content; otherwise automatically generate one or more style sheet rules for one or more stylistic changes associated with said selection; update the style sheet to include the generated one or more style sheet rules; and automatically apply said generated style sheet rule to said content by changing the markup code defining the content. | 15. A computing system comprising a processor with access to a non-transitory computer-readable medium embodying one or more program components that configure the computing system to: detect selection of content within a page while the page is edited in an application, the content defined by markup code; responsive to input received by the application, automatically capture one or more stylistic changes to said content; responsive to capturing, automatically access a style data structure, the style data structure defined in a style sheet included in the page or in a separate style sheet file referenced by the page, wherein the style data structure comprises a plurality of style sheet rules, wherein each rule is applicable to one or more elements in the page to control an appearance of the one or more elements, and wherein the style sheet rules are logically distinct from the markup code defining the content; automatically search the style data structure for a style sheet rule defining a style having attributes that match said one or more stylistic changes; if a style sheet rule matching said one or more stylistic changes is found, automatically apply the discovered style sheet rule to said content by modifying markup defining a structural element of said web page corresponding to said content; otherwise automatically generate one or more style sheet rules for one or more stylistic changes associated with said selection; update the style sheet to include the generated one or more style sheet rules; and automatically apply said generated style sheet rule to said content by changing the markup code defining the content. 16. The system set forth in claim 15 , wherein the page comprises a web page. | 0.806466 |
1. A non-transitory machine-readable medium which when executed by a data processing device to perform a method, the method comprising: receiving a search query from a user; retrieving a plurality of citations, wherein content from each of the plurality of citations matches the search query and the plurality of citations cites a plurality of objects; generating a subject list that includes a plurality of subjects, wherein each of the plurality of subjects are connected to the user either directly or indirectly in an influence network of a user; calculating an influence score for each of the plurality of subjects based at least on a distance on a path from the user to that subject in the influence network and each subject is a representation of a different user in the influence network; ranking the plurality of objects using a bias filter that includes a ranking function based on at least the influence scores of the subjects of each matching citation, wherein the influence scores are obtained from the user's subject list for those citing subjects that are on the list; and selecting a subset of objects from the ranked plurality of objects as the search results for presentation to the user. | 1. A non-transitory machine-readable medium which when executed by a data processing device to perform a method, the method comprising: receiving a search query from a user; retrieving a plurality of citations, wherein content from each of the plurality of citations matches the search query and the plurality of citations cites a plurality of objects; generating a subject list that includes a plurality of subjects, wherein each of the plurality of subjects are connected to the user either directly or indirectly in an influence network of a user; calculating an influence score for each of the plurality of subjects based at least on a distance on a path from the user to that subject in the influence network and each subject is a representation of a different user in the influence network; ranking the plurality of objects using a bias filter that includes a ranking function based on at least the influence scores of the subjects of each matching citation, wherein the influence scores are obtained from the user's subject list for those citing subjects that are on the list; and selecting a subset of objects from the ranked plurality of objects as the search results for presentation to the user. 3. The machine-readable medium of claim 1 , wherein the method further comprises: accepting and enforcing the searching query on citation searching, retrieving and ranking, each of which is either be explicitly described by a user or best guessed by a system based on internal statistical data. | 0.581274 |
52. A non-transitory computer readable medium for use on a computing device, the medium storing instructions executable using the computing device, the instructions for: identifying a plurality of entities having relationships therebetween; accessing a first entity from the plurality of entities, the first entity including a graphical model that has a graphical affordance; accessing a second entity from the plurality of entities, the second entity including at least one of a generated code or an intermediate representation that corresponds to the graphical model; and mapping the first entity to the second entity, using a computer, to facilitate graphical identification of a bi-directional mapping between a first part, of the first entity, that includes the graphical affordance depicted in the graphical model, and a second part, of the second entity, that includes a segment, of the at least one of the generated code or the intermediate representation, associated with the graphical affordance. | 52. A non-transitory computer readable medium for use on a computing device, the medium storing instructions executable using the computing device, the instructions for: identifying a plurality of entities having relationships therebetween; accessing a first entity from the plurality of entities, the first entity including a graphical model that has a graphical affordance; accessing a second entity from the plurality of entities, the second entity including at least one of a generated code or an intermediate representation that corresponds to the graphical model; and mapping the first entity to the second entity, using a computer, to facilitate graphical identification of a bi-directional mapping between a first part, of the first entity, that includes the graphical affordance depicted in the graphical model, and a second part, of the second entity, that includes a segment, of the at least one of the generated code or the intermediate representation, associated with the graphical affordance. 81. The computer readable medium of claim 52 , where the instructions are further for: specifying a scope for aspects in the graphical model, the aspects related to graphically identifying the second part as at least one segment that is within the scope that is specified. | 0.706215 |
1. A method comprising: receiving a plurality of optical signals on a plurality of optical channels from an optical fiber communication system; digitizing the received plurality of optical signals to obtain a plurality of data streams corresponding to the plurality of optical signals; identifying unique words in each of the plurality of data streams; determining one or more characteristics of the plurality of data streams based at least in part on the unique words, wherein the one or more characteristics includes at least one of particular received optical channels corresponding to the plurality of data streams or a timing offset between one or more of the plurality of data streams; and demodulating and decoding the plurality of data streams into data transport frames using the one or more characteristics of the plurality of data streams determined using the identified unique words. | 1. A method comprising: receiving a plurality of optical signals on a plurality of optical channels from an optical fiber communication system; digitizing the received plurality of optical signals to obtain a plurality of data streams corresponding to the plurality of optical signals; identifying unique words in each of the plurality of data streams; determining one or more characteristics of the plurality of data streams based at least in part on the unique words, wherein the one or more characteristics includes at least one of particular received optical channels corresponding to the plurality of data streams or a timing offset between one or more of the plurality of data streams; and demodulating and decoding the plurality of data streams into data transport frames using the one or more characteristics of the plurality of data streams determined using the identified unique words. 2. The method of claim 1 , wherein the timing offset is determined by comparing times of receipt of the unique words associated with the plurality of data streams. | 0.633688 |
1. A computerized method for generating and evaluating natural language-generated text, the method comprising: receiving, in a computer, data input by a user, the received data to be used to generate multiple different story instances; accessing a corpus stored in non volatile storage, using a processor of the computer; generating, using a natural language generation technique, multiple instances of text stories based upon both contents of the corpus and the received data; analyzing each of the multiple instances of text stories by computing a geographic score using the processor, computing a distance score using the processor, computing an information content score using the processor, computing a replacement score using the processor, and computing an extra aspect score using the processor; for each of the multiple instances of text stories, normalizing, using the processor, each of the computed geographic score, the computed distance score, the computed information content score, the computed replacement score, and the computed extra aspect score, to a common scale so as to obtain, for each of the multiple instances of text stories, a normalized geographic score, a normalized distance score, a normalized information content score, a normalized replacement score, and a normalized extra aspect score; applying, using the processor, a first weighting factor to all of the normalized geographic scores of each of the multiple instances of text stories to obtain weighted geographic scores; applying, using the processor, a second weighting factor to all of the normalized distance scores of each of the multiple instances of text stories to obtain weighted distance scores; applying, using the processor, a third weighting factor to all of the normalized information content scores of each of the multiple instances of text stories to obtain weighted information content scores; applying, using the processor, a fourth weighting factor to all of the normalized replacement scores of each of the multiple instances of text stories to obtain weighted replacement scores; applying, using the processor, a fifth weighting factor to all of the normalized extra aspect scores of each of the multiple instances of text stories to obtain weighted extra aspect scores; using the processor, computing a total score for each of the multiple instances of text stories from the respective weighted geographic score, weighted distance score, weighted information content score, weighted replacement score, and weighted extra aspect score; generating, for display on a screen associated with the user, an ordered set of the multiple instances of text stories, using the processor, ranked according to their total score; receiving from the user, at the processor, a selection of at least one of the displayed instances of text stories in the ordered set; creating an electronic record in the non-volatile storage containing the selected at least one of the displayed instances of text stories; employing a grammar checker on the multiple instances of text stories; maintaining, using the processor, a record of corrections made by the grammar checker; utilizing the processor to automatically learn, based on the record of corrections, circumstances where corrections were made; utilizing the processor to determine, based on the learned circumstances, one or more changes to be made to the corpus; and applying, using the processor, the determined changes to the corpus. | 1. A computerized method for generating and evaluating natural language-generated text, the method comprising: receiving, in a computer, data input by a user, the received data to be used to generate multiple different story instances; accessing a corpus stored in non volatile storage, using a processor of the computer; generating, using a natural language generation technique, multiple instances of text stories based upon both contents of the corpus and the received data; analyzing each of the multiple instances of text stories by computing a geographic score using the processor, computing a distance score using the processor, computing an information content score using the processor, computing a replacement score using the processor, and computing an extra aspect score using the processor; for each of the multiple instances of text stories, normalizing, using the processor, each of the computed geographic score, the computed distance score, the computed information content score, the computed replacement score, and the computed extra aspect score, to a common scale so as to obtain, for each of the multiple instances of text stories, a normalized geographic score, a normalized distance score, a normalized information content score, a normalized replacement score, and a normalized extra aspect score; applying, using the processor, a first weighting factor to all of the normalized geographic scores of each of the multiple instances of text stories to obtain weighted geographic scores; applying, using the processor, a second weighting factor to all of the normalized distance scores of each of the multiple instances of text stories to obtain weighted distance scores; applying, using the processor, a third weighting factor to all of the normalized information content scores of each of the multiple instances of text stories to obtain weighted information content scores; applying, using the processor, a fourth weighting factor to all of the normalized replacement scores of each of the multiple instances of text stories to obtain weighted replacement scores; applying, using the processor, a fifth weighting factor to all of the normalized extra aspect scores of each of the multiple instances of text stories to obtain weighted extra aspect scores; using the processor, computing a total score for each of the multiple instances of text stories from the respective weighted geographic score, weighted distance score, weighted information content score, weighted replacement score, and weighted extra aspect score; generating, for display on a screen associated with the user, an ordered set of the multiple instances of text stories, using the processor, ranked according to their total score; receiving from the user, at the processor, a selection of at least one of the displayed instances of text stories in the ordered set; creating an electronic record in the non-volatile storage containing the selected at least one of the displayed instances of text stories; employing a grammar checker on the multiple instances of text stories; maintaining, using the processor, a record of corrections made by the grammar checker; utilizing the processor to automatically learn, based on the record of corrections, circumstances where corrections were made; utilizing the processor to determine, based on the learned circumstances, one or more changes to be made to the corpus; and applying, using the processor, the determined changes to the corpus. 9. The computerized method of claim 1 : wherein the computing the replacement score is performed according to the formula S replace = [ ∏ aspect ∈ t , t ∈ P ( 1 + input [ aspect ] · value original_aspect · value ) ] - 1 where “input[aspect].value” is a value obtained from the data input by the user and “original_aspect.value” is a value specified within a sentence component of a corpus unit. | 0.537734 |
1. A computing device, comprising: at least one processor, and a memory connected to the at least one processor, wherein the at least one memory and the at least one processor are respectively configured to store and execute instructions for causing the computing device to perform operations, the operations comprising: receiving one or more modules of a machine learning workflow; composing the one or more received modules of the machine learning workflow into at least a portion of a machine learning application; and processing a machine learning dataset with the composed machine learning application, the processing of the machine learning dataset including: automatically interfacing the dataset, at runtime, between a first execution environment configured to execute machine learning code in a first programming language and a second execution environment configured to execute code written in a second programming language; and interfacing metadata schema, at runtime, between the first execution environment configured to execute the machine learning code in the first programming language and the second execution environment configured to execute the code written in the second programming language. | 1. A computing device, comprising: at least one processor, and a memory connected to the at least one processor, wherein the at least one memory and the at least one processor are respectively configured to store and execute instructions for causing the computing device to perform operations, the operations comprising: receiving one or more modules of a machine learning workflow; composing the one or more received modules of the machine learning workflow into at least a portion of a machine learning application; and processing a machine learning dataset with the composed machine learning application, the processing of the machine learning dataset including: automatically interfacing the dataset, at runtime, between a first execution environment configured to execute machine learning code in a first programming language and a second execution environment configured to execute code written in a second programming language; and interfacing metadata schema, at runtime, between the first execution environment configured to execute the machine learning code in the first programming language and the second execution environment configured to execute the code written in the second programming language. 3. The computing device of claim 1 , wherein interfacing the metadata schema comprises: translating a machine learning-specific schema associated with the second execution environment to a schema associated with the first machine learning execution environment without loss of information. | 0.5 |
23. The system of claim 19 , wherein the plurality of second entities correspond to one or more concept nodes in the social graph. | 23. The system of claim 19 , wherein the plurality of second entities correspond to one or more concept nodes in the social graph. 24. The system of claim 23 , wherein the plurality of second entities correspond to one or more places represented by the one or more concept nodes. | 0.959409 |
7. A method of handling events generated by user interaction with a display that includes a first window and a second iframe that is not contained within the first window, including: generating a popup control of the first window responsive to a first user event representing user interaction with the first window; in circumstances when the user relocates a cursor from the first window to the second iframe and a focus event generated from a mouse or touch event within the second iframe is suppressed from propagation to the first window, receiving a blur event and a location of the blur event propagated from the second iframe, and responsive to the blur event in the second iframe, triggering a dismiss class within the first window, wherein the dismiss class dismisses at least a target portion of the generated popup control of the first window. | 7. A method of handling events generated by user interaction with a display that includes a first window and a second iframe that is not contained within the first window, including: generating a popup control of the first window responsive to a first user event representing user interaction with the first window; in circumstances when the user relocates a cursor from the first window to the second iframe and a focus event generated from a mouse or touch event within the second iframe is suppressed from propagation to the first window, receiving a blur event and a location of the blur event propagated from the second iframe, and responsive to the blur event in the second iframe, triggering a dismiss class within the first window, wherein the dismiss class dismisses at least a target portion of the generated popup control of the first window. 11. The method of claim 7 , further including: displaying a trigger component within the popup control; and receiving an event that selects the trigger component and displaying a target component that displays a list of choices responsive to selection of the trigger; wherein the portion of the popup control that is dismissed by the dismiss class is the target component, leaving the trigger component active after shift of focus to the second iframe. | 0.718284 |
1. A method comprising: conducting a campaign experiment that reflects implementation of a campaign change in an experiment environment to generate experimental results that reflect a causal measurement of value of a campaign, wherein the campaign change includes a current change to one or more campaign parameters for providing content items over a computer network for presentation by user computing devices; determining, by one or more computing servers, a measure of effectiveness of the campaign change to within a predetermined confidence level, based at least in part on analyzing the experimental results; determining, by the one or more computing servers, an estimate of effectiveness of the campaign change, wherein determining the estimate of effectiveness comprises referencing campaign data related to the campaign change, referencing interaction data that indicates user interactions with one or more of the content items, correlating the campaign data with the interaction data over a predetermined time period, and applying rules of an identified attribution model that assigns credit to user interactions with one or more of the content items that lead to user conversions; comparing, by the one or more computing servers, the determined estimate of effectiveness of the campaign change to the determined measure of effectiveness of the campaign change; determining, based on the comparison, that the identified attribution model provides an estimate of the measure of effectiveness that is within a predetermined range of the measure of effectiveness of the campaign change; for one or more subsequent campaign changes that include a change to the one or more campaign parameters that matches the current change to the one or more campaign parameters, determining a subsequent estimate of effectiveness of the subsequent campaign change, based at least in part on applying the identified attribution model in lieu of conducting another campaign experiment to determine the subsequent estimate of effectiveness of the subsequent campaign change; and using subsequent determined estimates of effectiveness of the subsequent campaign changes obtained from application of the identified attribution model as a proxy for measures of effectiveness in lieu of conducting another campaign experiment to determine the measure of effectiveness. | 1. A method comprising: conducting a campaign experiment that reflects implementation of a campaign change in an experiment environment to generate experimental results that reflect a causal measurement of value of a campaign, wherein the campaign change includes a current change to one or more campaign parameters for providing content items over a computer network for presentation by user computing devices; determining, by one or more computing servers, a measure of effectiveness of the campaign change to within a predetermined confidence level, based at least in part on analyzing the experimental results; determining, by the one or more computing servers, an estimate of effectiveness of the campaign change, wherein determining the estimate of effectiveness comprises referencing campaign data related to the campaign change, referencing interaction data that indicates user interactions with one or more of the content items, correlating the campaign data with the interaction data over a predetermined time period, and applying rules of an identified attribution model that assigns credit to user interactions with one or more of the content items that lead to user conversions; comparing, by the one or more computing servers, the determined estimate of effectiveness of the campaign change to the determined measure of effectiveness of the campaign change; determining, based on the comparison, that the identified attribution model provides an estimate of the measure of effectiveness that is within a predetermined range of the measure of effectiveness of the campaign change; for one or more subsequent campaign changes that include a change to the one or more campaign parameters that matches the current change to the one or more campaign parameters, determining a subsequent estimate of effectiveness of the subsequent campaign change, based at least in part on applying the identified attribution model in lieu of conducting another campaign experiment to determine the subsequent estimate of effectiveness of the subsequent campaign change; and using subsequent determined estimates of effectiveness of the subsequent campaign changes obtained from application of the identified attribution model as a proxy for measures of effectiveness in lieu of conducting another campaign experiment to determine the measure of effectiveness. 11. The method of claim 1 , wherein the campaign experiment is a geographic campaign experiment that uses a control group in one geographic region that does not present content from the campaign as compared to other geographic areas where content from the campaign is presented. | 0.616101 |
11. A computer storage media medium having computer executable instructions for providing collaborative authoring features in a document editor program, the instructions comprising: providing a document editor program that includes a line of business integration mode; activating the line of business integration mode; displaying a document editing pane in the document editor program, wherein the document editing pane includes a document having at least one section; displaying a document assembly pane in the document editing program, wherein the document assembly pane includes a document details pane and a section details pane; obtaining document details metadata, wherein the document details metadata includes metadata associated with collaboratively authoring the document; obtaining section details metadata, wherein the section details metadata includes data associated with an author assigned to the at least one section of the document; displaying the document details metadata in the document details pane; displaying the section details metadata in the section details pane; and publishing the document, wherein publishing the document includes disabling the line of business integration mode and hiding the document assembly pane. | 11. A computer storage media medium having computer executable instructions for providing collaborative authoring features in a document editor program, the instructions comprising: providing a document editor program that includes a line of business integration mode; activating the line of business integration mode; displaying a document editing pane in the document editor program, wherein the document editing pane includes a document having at least one section; displaying a document assembly pane in the document editing program, wherein the document assembly pane includes a document details pane and a section details pane; obtaining document details metadata, wherein the document details metadata includes metadata associated with collaboratively authoring the document; obtaining section details metadata, wherein the section details metadata includes data associated with an author assigned to the at least one section of the document; displaying the document details metadata in the document details pane; displaying the section details metadata in the section details pane; and publishing the document, wherein publishing the document includes disabling the line of business integration mode and hiding the document assembly pane. 14. The computer storage media medium of claim 11 , wherein the section details pane includes a list of sections and assignments, wherein an expanded section details pane is populated with assignment metadata associated with a selected section. | 0.522883 |
1. A computer-implemented method for resolving ambiguities in date values associated with an attribute of an entity, the method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: obtaining a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determining that the first text string conforms to one or more date formats; assigning a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtaining a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determining that the second text string conforms to one or more of the date formats; assigning a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determining a first date string expressed in a date format with a highest first confidence value for the first text string; determining a second date string expressed in a date format with a highest second confidence value for the second text string; and merging a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute. | 1. A computer-implemented method for resolving ambiguities in date values associated with an attribute of an entity, the method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: obtaining a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determining that the first text string conforms to one or more date formats; assigning a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtaining a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determining that the second text string conforms to one or more of the date formats; assigning a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determining a first date string expressed in a date format with a highest first confidence value for the first text string; determining a second date string expressed in a date format with a highest second confidence value for the second text string; and merging a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute. 12. The method of claim 1 , wherein one of the date formats is a United States date format. | 0.599456 |
28. A computer-implemented method for recommending items to a customer comprising: causing a display of a hub associated with a primary item on a computer display; causing a display of a plurality of nodes on the computer display, wherein each of the nodes is associated with a secondary item; determining a first quantity related to a countable event associated with the primary item and each of the secondary items during a first period of time; determining a second quantity related to the countable event during a second period of time; and wherein a characteristic of each of the nodes on the computer display is based at least in part on at least one of the first quantity or the second quantity for each of the secondary items, and wherein the countable event is an order of the secondary item following a selection of the primary item by at least one customer. | 28. A computer-implemented method for recommending items to a customer comprising: causing a display of a hub associated with a primary item on a computer display; causing a display of a plurality of nodes on the computer display, wherein each of the nodes is associated with a secondary item; determining a first quantity related to a countable event associated with the primary item and each of the secondary items during a first period of time; determining a second quantity related to the countable event during a second period of time; and wherein a characteristic of each of the nodes on the computer display is based at least in part on at least one of the first quantity or the second quantity for each of the secondary items, and wherein the countable event is an order of the secondary item following a selection of the primary item by at least one customer. 33. The method according to claim 28 , wherein the second period of time is at least one of shorter in duration or more recent in time than the first period of time. | 0.785568 |
4. The apparatus according to claim 1 , wherein the second acquisition unit is configured to acquire the estimated value of each of the words, based on an article of each of the words and a frequency of detection of each of the words. | 4. The apparatus according to claim 1 , wherein the second acquisition unit is configured to acquire the estimated value of each of the words, based on an article of each of the words and a frequency of detection of each of the words. 5. The apparatus according to claim 4 , wherein the extraction unit is configured to extract, from the estimated value distributions, a start time and an end time of a zone of the video content corresponding to one of the estimated value distributions which exceeds a threshold value. | 0.881002 |
6. A computer readable storage device storing a computer program which when executed by a processor causes the processor to perform a method comprising: receiving an electronic document including content items, a rule and a digital signature, wherein the rule specifies what parts of the electronic document are allowed to change based on user interaction with the electronic document; generating a digest for the electronic document by digesting all of the content items, using multiple functions based upon complexity of the content items, except for at least a first content item that is ignored in the digestion based on the rule; comparing the generated digest with a stored digest that is associated with the electronic document; and invalidating the digital signature if the generated digest indicates a difference in any of the digested content items, wherein if the generated digest indicates no difference in any of the digested content items, the method further comprises: subsequently receiving a user input attempting to create a new state of the received electronic document; determining whether the user input is allowed by the rule; and invalidating the digital signature if the user input is not allowed by the rule, and wherein the rule applies differently to a first author and a second author, such that the user input causes a first digital signature of the first author to be invalidated but does not cause a second digital signature of the second author to be invalidated. | 6. A computer readable storage device storing a computer program which when executed by a processor causes the processor to perform a method comprising: receiving an electronic document including content items, a rule and a digital signature, wherein the rule specifies what parts of the electronic document are allowed to change based on user interaction with the electronic document; generating a digest for the electronic document by digesting all of the content items, using multiple functions based upon complexity of the content items, except for at least a first content item that is ignored in the digestion based on the rule; comparing the generated digest with a stored digest that is associated with the electronic document; and invalidating the digital signature if the generated digest indicates a difference in any of the digested content items, wherein if the generated digest indicates no difference in any of the digested content items, the method further comprises: subsequently receiving a user input attempting to create a new state of the received electronic document; determining whether the user input is allowed by the rule; and invalidating the digital signature if the user input is not allowed by the rule, and wherein the rule applies differently to a first author and a second author, such that the user input causes a first digital signature of the first author to be invalidated but does not cause a second digital signature of the second author to be invalidated. 10. The method of claim 6 , wherein the first content item is ignored in the digestion on another basis than the rule specifying a content item type. | 0.794495 |
4. A system according to claim 1, wherein when the message is posted, said server adds an identification code to the quotation sentence which cites said posted message and posts the message into said database. | 4. A system according to claim 1, wherein when the message is posted, said server adds an identification code to the quotation sentence which cites said posted message and posts the message into said database. 5. A system according to claim 4, wherein when a plurality of messages are merged on the basis of said information for related subject, said summary forming means discriminates duplicated quotation sentences from said identification code and merges said plurality of messages while leaving at least one quotation sentence. | 0.875 |
10. One or more tangible computer-readable media encoding software operable when executed to: search a search space of a corpus to yield a plurality of results, the corpus comprising a plurality of documents associated with a plurality of keywords, each document associated with at least one keyword indicating at least one theme of the document; determine that one or more of the plurality of keywords are irrelevant keywords; expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by: determining one or more irrelevant themes indicated by the irrelevant keywords; identifying one or more affine themes that are highly affine to the irrelevant themes, wherein the affine themes are highly affine if they satisfy an affinity threshold; determining one or more affine keywords that correspond to the affine themes; and identifying the affine keywords as the keywords related to the irrelevant keywords; and refine the search space according to the irrelevant keywords. | 10. One or more tangible computer-readable media encoding software operable when executed to: search a search space of a corpus to yield a plurality of results, the corpus comprising a plurality of documents associated with a plurality of keywords, each document associated with at least one keyword indicating at least one theme of the document; determine that one or more of the plurality of keywords are irrelevant keywords; expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by: determining one or more irrelevant themes indicated by the irrelevant keywords; identifying one or more affine themes that are highly affine to the irrelevant themes, wherein the affine themes are highly affine if they satisfy an affinity threshold; determining one or more affine keywords that correspond to the affine themes; and identifying the affine keywords as the keywords related to the irrelevant keywords; and refine the search space according to the irrelevant keywords. 15. The computer-readable media of claim 10 , the software further operable to refine the search according to the irrelevant keywords by: removing, from the plurality of results that were yielded from the search of the search space of the corpus, the irrelevant keywords from the search. | 0.678766 |
1. In a grammar checking system, a system for detection and correction of inflection for words in a sentence, comprising: means for providing a list of incorrect words which do not follow normal language rules as to pluralization, past tense, past participle and superlative formation, along with the roots and morphological features thereof, said list being based on incorrect grammar; means for detecting words in said sentence which match a word in said list of incorrect words, thereby to identify an incorrect word; and, means for suggesting replacement words for a detected incorrect word including means responsive to the root and morphologic features of said incorrect words for identifying the incorrect word and its root and morphology and means including a natural language dictionary for selecting appropriate form of the word with said root and morphological features, thereby to suggest the correct word. | 1. In a grammar checking system, a system for detection and correction of inflection for words in a sentence, comprising: means for providing a list of incorrect words which do not follow normal language rules as to pluralization, past tense, past participle and superlative formation, along with the roots and morphological features thereof, said list being based on incorrect grammar; means for detecting words in said sentence which match a word in said list of incorrect words, thereby to identify an incorrect word; and, means for suggesting replacement words for a detected incorrect word including means responsive to the root and morphologic features of said incorrect words for identifying the incorrect word and its root and morphology and means including a natural language dictionary for selecting appropriate form of the word with said root and morphological features, thereby to suggest the correct word. 3. The system of claim 1, and further including a part of speech tagger for detecting the most likely part of speech of said detected incorrect word, and means for coupling said part of speech tagger to said means for identifying said morphological features to permit more accurate determination thereof. | 0.707294 |
5. The method of claim 1 , wherein: the execution tree for the semantic web query comprises an access method and an execution node for each triple pattern in the semantic web query; and transforming the execution tree for the semantic web query into an equivalent entity-oriented storage query plan comprises merging execution nodes for triple patterns having at least one of a common subject and a common object into merged plan nodes. | 5. The method of claim 1 , wherein: the execution tree for the semantic web query comprises an access method and an execution node for each triple pattern in the semantic web query; and transforming the execution tree for the semantic web query into an equivalent entity-oriented storage query plan comprises merging execution nodes for triple patterns having at least one of a common subject and a common object into merged plan nodes. 9. The method of claim 5 , wherein transforming the execution tree for the semantic web query into an equivalent entity-oriented storage query plan further comprises merging execution nodes only for which equivalent SQL statements exist for the merged plan nodes. | 0.847149 |
1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. | 1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. 7. The system of claim 1 , wherein the statistics correspond to a frequency of occurrence for each of the results. | 0.568732 |
1. A method, comprising: performing optical character recognition (OCR) on an image of a first document; generating a list of hypotheses mapping the first document to a complementary document using: textual information from the first document, textual information from the complementary document, and predefined business rules; at least one of: correcting OCR errors in the first document, and normalizing data from the complementary document, using at least one of the textual information from the complementary document and the predefined business rules; determining a validity of the first document based on the hypotheses; and outputting an indication of the determined validity. | 1. A method, comprising: performing optical character recognition (OCR) on an image of a first document; generating a list of hypotheses mapping the first document to a complementary document using: textual information from the first document, textual information from the complementary document, and predefined business rules; at least one of: correcting OCR errors in the first document, and normalizing data from the complementary document, using at least one of the textual information from the complementary document and the predefined business rules; determining a validity of the first document based on the hypotheses; and outputting an indication of the determined validity. 9. A method as recited in claim 1 , wherein determining the validity of the first document includes automatically correcting values for expected or actual line items or header field items in the first document based on at least one of the textual information from the complementary document and the business rules. | 0.596206 |
1. Vital digital communication system responsive to the selection of a desired command to be sent for encoding a corresponding message, transmitting and decoding the message to derive said command in a vital manner comprising: a transmitter including encoding means responsive to the selection of a desired command for generating and outputting said message, said message comprising a pair of multi-bit words, each word separated from other words by an identical multi-bit framing sequence, a second word of said pair complementary to a first word of said pair, the ratio of ones and zeroes in either said first or second word being constant, a receiver including vital decoding means responsive to the output of said encoder for identifying said framing bits and for identifying each word of said message, said vital decoding means including, means for sequentially producing multi-bit words in response to sequential receipt of said encoded words and means for checking that said sequentially produced multi-bit words are complementary to each other, said last-named means including, a multi-bit comparator for comparing said produced multi-bit word with a multi-bit pattern, said comparator sequentially emitting different outputs if sequential ones of said produced multi-bit words are complementary, said vital decoding means providing an output indicative of said command if, and only if, said sequentially emitted outputs are provided. | 1. Vital digital communication system responsive to the selection of a desired command to be sent for encoding a corresponding message, transmitting and decoding the message to derive said command in a vital manner comprising: a transmitter including encoding means responsive to the selection of a desired command for generating and outputting said message, said message comprising a pair of multi-bit words, each word separated from other words by an identical multi-bit framing sequence, a second word of said pair complementary to a first word of said pair, the ratio of ones and zeroes in either said first or second word being constant, a receiver including vital decoding means responsive to the output of said encoder for identifying said framing bits and for identifying each word of said message, said vital decoding means including, means for sequentially producing multi-bit words in response to sequential receipt of said encoded words and means for checking that said sequentially produced multi-bit words are complementary to each other, said last-named means including, a multi-bit comparator for comparing said produced multi-bit word with a multi-bit pattern, said comparator sequentially emitting different outputs if sequential ones of said produced multi-bit words are complementary, said vital decoding means providing an output indicative of said command if, and only if, said sequentially emitted outputs are provided. 2. The apparatus of claim 1 wherein said encoding means includes a clock shift register loading means, a shift register coupled to said clock, said shift register responding to said shift register loading means for alternately storing in said shift register a pair of framing bits and an encoded word or its complement, said shift register outputing said message in response to said clock. | 0.586933 |
5. The method of claim 2 , comprising assigning a score to the one or more query term optionalization rules that are specific to the particular query term based at least on the click count and the skip count. | 5. The method of claim 2 , comprising assigning a score to the one or more query term optionalization rules that are specific to the particular query term based at least on the click count and the skip count. 7. The method of claim 5 , comprising: determining that the score assigned to the one or more query term optionalization rules that are specific to the particular query term does not satisfy a threshold; and removing the one or more query term optionalization rules that are specific to the particular query term from a set of query term optionalization rules that includes other query term optionalization rules that are specific to other query terms, the other query term optionalization rules indicating whether the other query terms should be made optional in revisions of search queries that include the other query terms, based on determining that the score assigned to the one or more query term optionalization rules that are specific to the particular query term does not satisfy the threshold. | 0.867564 |
81. A computer program product (CPP) comprising a computer usable medium having computer readable program code (CRPC) means embodied in the medium for causing an application program to execute on a computer processor to perform inverse quantization of a vector representative of a portion of a speech or audio signal, the vector being quantized according to the steps of determining, among a set of candidate codevectors that include line spectral frequencies (LSFs), a best candidate codevector not belonging to an illegal space representative of illegal vectors, wherein the illegal space is defined by invalid spacing characteristics of LSF parameters, wherein the best candidate codevector corresponds to a quantization of the vector, and outputting a quantizer index identifying the best legal candidate codevector, the CRPC means comprising: producing CRPC means for causing the processor to produce a reconstructed codevector based on a received quantizer index; determining CRPC means for causing the processor to determine whether the reconstructed codevector does not belong to the illegal space; and outputting CRPC means for causing the processor to output a reconstructed portion of the speech or audio signal based on the reconstructed codevector when the reconstructed codevector does not belong to the illegal space. | 81. A computer program product (CPP) comprising a computer usable medium having computer readable program code (CRPC) means embodied in the medium for causing an application program to execute on a computer processor to perform inverse quantization of a vector representative of a portion of a speech or audio signal, the vector being quantized according to the steps of determining, among a set of candidate codevectors that include line spectral frequencies (LSFs), a best candidate codevector not belonging to an illegal space representative of illegal vectors, wherein the illegal space is defined by invalid spacing characteristics of LSF parameters, wherein the best candidate codevector corresponds to a quantization of the vector, and outputting a quantizer index identifying the best legal candidate codevector, the CRPC means comprising: producing CRPC means for causing the processor to produce a reconstructed codevector based on a received quantizer index; determining CRPC means for causing the processor to determine whether the reconstructed codevector does not belong to the illegal space; and outputting CRPC means for causing the processor to output a reconstructed portion of the speech or audio signal based on the reconstructed codevector when the reconstructed codevector does not belong to the illegal space. 87. The CPP of claim 81 , wherein: the determining CRPC means comprises CRPC means for causing the processor to determine whether at least a portion of the reconstructed codevector does not belong to the illegal space; and the outputting CRPC means comprises CRPC means for causing the processor to output a reconstructed portion of the speech or audio signal based on the reconstructed codevector when at least a portion thereof does not belong to the illegal space. | 0.555911 |
15. A computer program product in a non-transitory computer readable medium for use in one or more data processing systems, the computer program product holding computer program instructions executed by the one or more data processing systems to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, the computer program instructions operative to: associate a social networking platform with the application development environments; enable anonymous access to the social networking platform by users of the application development environments, the anonymous access enabling users to upload messages for posting to a forum; prior to posting, filter a message and, responsive to the filtering, automatically obfuscate sensitive data associated with a particular application development environment and any application code included in the message; receive security findings generated as users of the application development environments use the cloud-based static analysis security tool; process the received security findings using machine learning, and store the processed security findings into a knowledgebase; and provide social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. | 15. A computer program product in a non-transitory computer readable medium for use in one or more data processing systems, the computer program product holding computer program instructions executed by the one or more data processing systems to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, the computer program instructions operative to: associate a social networking platform with the application development environments; enable anonymous access to the social networking platform by users of the application development environments, the anonymous access enabling users to upload messages for posting to a forum; prior to posting, filter a message and, responsive to the filtering, automatically obfuscate sensitive data associated with a particular application development environment and any application code included in the message; receive security findings generated as users of the application development environments use the cloud-based static analysis security tool; process the received security findings using machine learning, and store the processed security findings into a knowledgebase; and provide social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. 17. The computer program product as described in claim 15 wherein the social network content includes analytics generated from execution of the static security analysis tool in association with the set of application development environments. | 0.552288 |
1. A method for using a model for pattern recognition, the method comprising: executing instructions stored in memory, wherein execution of the instructions by a processor: configures a pattern matching engine based on user input, the user input comprising one or more user configurable bounds on searching; and executes the pattern matching engine to search a pre-classified document for a plurality of features, wherein the pre-classified document is pre-classified into a category of content, the search results in a set of scores for the pre-classified document, and a model is established for the category of content based on the set of scores for the pre-classified document; and storing in memory the established model for the category of content based on the set of scores for the pre-classified document, wherein further execution of instructions by the processor: executes the pattern matching engine to perform a search for the plurality of features in an incoming string; updates a plurality of scores based on presence of any of the plurality of features in the incoming string; terminates the search before reaching an end of the string if the one or more user configurable bounds are met; outputs the plurality of scores after terminating the search; and classifies the incoming string into the category of content based on a comparison of the scores for the incoming string with the model established based on the set of scores for the pre-classified document. | 1. A method for using a model for pattern recognition, the method comprising: executing instructions stored in memory, wherein execution of the instructions by a processor: configures a pattern matching engine based on user input, the user input comprising one or more user configurable bounds on searching; and executes the pattern matching engine to search a pre-classified document for a plurality of features, wherein the pre-classified document is pre-classified into a category of content, the search results in a set of scores for the pre-classified document, and a model is established for the category of content based on the set of scores for the pre-classified document; and storing in memory the established model for the category of content based on the set of scores for the pre-classified document, wherein further execution of instructions by the processor: executes the pattern matching engine to perform a search for the plurality of features in an incoming string; updates a plurality of scores based on presence of any of the plurality of features in the incoming string; terminates the search before reaching an end of the string if the one or more user configurable bounds are met; outputs the plurality of scores after terminating the search; and classifies the incoming string into the category of content based on a comparison of the scores for the incoming string with the model established based on the set of scores for the pre-classified document. 5. The method of claim 1 , wherein the outputted plurality of scores is further based on a weight assigned to one or more of the features. | 0.518971 |
17. A computer-implemented method for generating client side markup for a client in a client/server system comprising: specifying a website application from a set of controls for defining a dialog, the controls comprising at least a control for generating markup related to audible prompting of a question and for generating markup related to a grammar for recognition, said control having means for referring to another control of the same type in order to duplicate at least a portion of the dialog of said another control, wherein said control includes a prompt property for defining a prompt, an answer property defining the processing of responses by the user to the prompt, and wherein said means for referring to another control includes an imported answer property for identifying said another control, wherein said control includes an extra answer property defining processing of responses by the user which were unsolicited in the prompt, and wherein said means for referring to another control includes an imported extra answer property for identifying said another control; and generating client side markup from the specified website application and sending the client side markup to a client, wherein generating client side markup includes combining the processing of responses in the answer property with the processing of responses in the answer property of said another control identified in the imported answer property. | 17. A computer-implemented method for generating client side markup for a client in a client/server system comprising: specifying a website application from a set of controls for defining a dialog, the controls comprising at least a control for generating markup related to audible prompting of a question and for generating markup related to a grammar for recognition, said control having means for referring to another control of the same type in order to duplicate at least a portion of the dialog of said another control, wherein said control includes a prompt property for defining a prompt, an answer property defining the processing of responses by the user to the prompt, and wherein said means for referring to another control includes an imported answer property for identifying said another control, wherein said control includes an extra answer property defining processing of responses by the user which were unsolicited in the prompt, and wherein said means for referring to another control includes an imported extra answer property for identifying said another control; and generating client side markup from the specified website application and sending the client side markup to a client, wherein generating client side markup includes combining the processing of responses in the answer property with the processing of responses in the answer property of said another control identified in the imported answer property. 18. The computer-implemented method of claim 17 wherein generating client side markup includes combining the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property. | 0.560231 |
20. The computer readable storage medium of claim 19 , wherein the instructions for constructing a facet hierarchy include instructions for constructing a facet hierarchy based on the metadata describing the hierarchical relationship associated with the documents that satisfy the query. | 20. The computer readable storage medium of claim 19 , wherein the instructions for constructing a facet hierarchy include instructions for constructing a facet hierarchy based on the metadata describing the hierarchical relationship associated with the documents that satisfy the query. 22. The computer readable storage medium of claim 20 , wherein: the facet hierarchy includes a plurality of facets; and the instructions for creating the cube structure comprise instructions for creating dimensions for the cube structure based on the plurality of facets. | 0.802727 |
20. A method, comprising: determining a validity of a first document by simultaneously considering: textual information from the first document, textual information from a complementary document, and predefined business rules; at least one of: correcting OCR errors in the first document, and normalizing data from the first document prior to determining the validity, using at least one of the textual information from the complementary document and the predefined business rules; and outputting an indication of the determined validity. | 20. A method, comprising: determining a validity of a first document by simultaneously considering: textual information from the first document, textual information from a complementary document, and predefined business rules; at least one of: correcting OCR errors in the first document, and normalizing data from the first document prior to determining the validity, using at least one of the textual information from the complementary document and the predefined business rules; and outputting an indication of the determined validity. 27. A method as recited in claim 20 , further comprising: acquiring an electronic second document; identifying a second complementary document associated with the second document; generating a list of hypotheses mapping the second document to the second complementary document using: textual information from the second document, textual information from the second complementary document, and predefined business rules; determining a validity of the second document based on the hypotheses; and outputting an indication of the determined validity of the second document. | 0.545619 |
15. The method of claim 13 wherein the computing device comprises a geo-aware computing device, the geo-aware computing device selecting the demarcated area on the Earth by detecting and identifying virtual perimeters of said demarcated area on the Earth once said geo-aware computing device resides at said demarcated area on the Earth. | 15. The method of claim 13 wherein the computing device comprises a geo-aware computing device, the geo-aware computing device selecting the demarcated area on the Earth by detecting and identifying virtual perimeters of said demarcated area on the Earth once said geo-aware computing device resides at said demarcated area on the Earth. 17. The method of claim 15 wherein the virtual perimeters of said demarcated area on the Earth encompasses one or more physical structure associated with records of human activity selected from the group consisting of inscribed memorials, geotagged digital images of inscribed memorials, buildings, homes, apartments, churches, factories, offices, ports, cemeteries or modes of transportation. | 0.856754 |
1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results. | 1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results. 12. A method as recited in claim 1 wherein storing search data comprises storing the search data in a database within the user device. | 0.660425 |
3. The computing system of claim 1 wherein the component that displays the retrieved images displays the images as a slideshow. | 3. The computing system of claim 1 wherein the component that displays the retrieved images displays the images as a slideshow. 5. The computing system of claim 3 wherein the component that displays the retrieved images displays a map encompassing the start location and the end location and displays an indication of the travel location associated with images of the slideshow. | 0.913004 |
1. A computer-implemented method for creating at least one n-dimensional map by utilizing one or more processors, comprising: obtaining, by utilizing said one or more processors, data from a plurality of data sources, said data containing information of a plurality of items each having one or more of an entity, a meaning, a place, a time, a word, a phrase, or a symbol; ascribing, by utilizing said one or more processors, meaning to position or location within an n-dimensional space represented by a fixed point for each item within a space among n-dimensional spaces, wherein a fixed point for one item is different from a fixed point for another item; arranging, by utilizing said one or more processors, said fixed point for one item relative to the fixed point for another item in corresponding space according to a set of predefined variable; creating, by utilizing a mapping unit, an n-dimensional map by correlating each of said fixed points defining corresponding location within the space; translating, by utilizing said one or more processors, content associated with each item into its corresponding location within the n-dimensional map and storing said translated content as a set of coordinates with corresponding relationship to each other to perpetually correspond to one or more of said entity, meaning, place, time, word, phrase, or symbol; and comparing, by utilizing said one or more processors, said translated content with a new set of data to determine differences or similarities between the translated content and the new set of data to provide a fused data on one or more output device with meaningful attributes, wherein said n-dimensional map is an EMPT (entity, meaning, place, and time) map created by correlating different types of data over the same entities, meanings, times, and places according to corresponding fixed points in the n-dimensional space in the form of a Cartesian or other type of coordinate representing greater than two (2) dimensions coordinate. | 1. A computer-implemented method for creating at least one n-dimensional map by utilizing one or more processors, comprising: obtaining, by utilizing said one or more processors, data from a plurality of data sources, said data containing information of a plurality of items each having one or more of an entity, a meaning, a place, a time, a word, a phrase, or a symbol; ascribing, by utilizing said one or more processors, meaning to position or location within an n-dimensional space represented by a fixed point for each item within a space among n-dimensional spaces, wherein a fixed point for one item is different from a fixed point for another item; arranging, by utilizing said one or more processors, said fixed point for one item relative to the fixed point for another item in corresponding space according to a set of predefined variable; creating, by utilizing a mapping unit, an n-dimensional map by correlating each of said fixed points defining corresponding location within the space; translating, by utilizing said one or more processors, content associated with each item into its corresponding location within the n-dimensional map and storing said translated content as a set of coordinates with corresponding relationship to each other to perpetually correspond to one or more of said entity, meaning, place, time, word, phrase, or symbol; and comparing, by utilizing said one or more processors, said translated content with a new set of data to determine differences or similarities between the translated content and the new set of data to provide a fused data on one or more output device with meaningful attributes, wherein said n-dimensional map is an EMPT (entity, meaning, place, and time) map created by correlating different types of data over the same entities, meanings, times, and places according to corresponding fixed points in the n-dimensional space in the form of a Cartesian or other type of coordinate representing greater than two (2) dimensions coordinate. 3. The computer-implemented method according to claim 1 , further comprising: ascribing a subordinate fixed point for each item, having a specific attribute or classification, within a subordinate space to create a plurality of subordinate n-dimensional spaces. | 0.658389 |
7. A computer-implemented method comprising: under control of one or more processors configured with executable instructions, performing machine-based optical character recognition on individual pages of a print version of a book to obtain page labels and page text from the individual pages; finding positions within an electronic version of the book that correspond to individual pages of the print version, wherein the finding is based at least in part on: autocorrelation between the page text and the electronic version to identify a plurality of candidate positions for respective ones of the individual pages, and comparing the page text and text of the electronic version at the plurality of candidate positions to select found positions from the plurality of candidate positions determined from the autocorrelation; and associating the found positions within the electronic version with the page labels of the corresponding individual pages of the print version. | 7. A computer-implemented method comprising: under control of one or more processors configured with executable instructions, performing machine-based optical character recognition on individual pages of a print version of a book to obtain page labels and page text from the individual pages; finding positions within an electronic version of the book that correspond to individual pages of the print version, wherein the finding is based at least in part on: autocorrelation between the page text and the electronic version to identify a plurality of candidate positions for respective ones of the individual pages, and comparing the page text and text of the electronic version at the plurality of candidate positions to select found positions from the plurality of candidate positions determined from the autocorrelation; and associating the found positions within the electronic version with the page labels of the corresponding individual pages of the print version. 8. The computer-implemented method of claim 7 , wherein the associating comprises: creating a page/position map that indicates correspondences between page labels of the print version and positions within the electronic version; and associating the page/position map with the electronic version. | 0.636285 |
17. The system of claim 11 , the operations further comprising offering an incentive to the user for providing the feedback. | 17. The system of claim 11 , the operations further comprising offering an incentive to the user for providing the feedback. 18. The system of claim 17 , wherein the incentive comprises at least one of a virtual good and a virtual currency, for use in an online game. | 0.972672 |
1. An information processing device, comprising: a learning module configured to extract an image feature amount of each frame of an image of learning content and extracting word frequency information regarding a frequency of appearance of each word in a description text describing a content of the image of the learning content as a text feature amount of the description text, wherein the learning content includes a text of a caption, and wherein the description text is the text of the caption included in the learning content, and learn an annotation model, which is a multi-stream HMM (Hidden Markov Model), by using an annotation sequence for annotation, which is a multi-stream including the image feature amount and the text feature amount; and a browsing controller configured to extract a scene, which is a group of one or more temporally continuous frames, from target content from which the scene is to be extracted by using the annotation model, and display representative images of scenes so as to be arranged in chronological order. | 1. An information processing device, comprising: a learning module configured to extract an image feature amount of each frame of an image of learning content and extracting word frequency information regarding a frequency of appearance of each word in a description text describing a content of the image of the learning content as a text feature amount of the description text, wherein the learning content includes a text of a caption, and wherein the description text is the text of the caption included in the learning content, and learn an annotation model, which is a multi-stream HMM (Hidden Markov Model), by using an annotation sequence for annotation, which is a multi-stream including the image feature amount and the text feature amount; and a browsing controller configured to extract a scene, which is a group of one or more temporally continuous frames, from target content from which the scene is to be extracted by using the annotation model, and display representative images of scenes so as to be arranged in chronological order. 3. The information processing device according to claim 1 , wherein the learning means extracts words included in the text of the caption displayed in a window as one document while shifting the window of a predetermined time length at regular intervals, and extracts multinomial distribution, which represents a frequency of appearance of each word in the document, as the text feature amount, and the browsing controlling means extracts the image feature amount of each frame of the image of the target content and composes the annotation sequence by using the image feature amount, obtains a maximum likelihood state sequence in which the annotation sequence is observed in the annotation model, selects a word with high frequency in the multinomial distribution observed in a state corresponding to a noted frame of interest out of states of the maximum likelihood state sequence as an annotation to be added to the frame of interest, extracts a group of one or more temporally continuous frames to which the same annotation is added as the scene from the target content, and displays the representative images of the scenes so as to be arranged in chronological order. | 0.677813 |
1. A machine-implemented method, comprising: receiving an indication of a request from a user to view a stream associated with the user; generating a request for one or more items, of a plurality of items, that are visible to the user for display within the stream, wherein each of the plurality of items includes one or more user tokens up to a threshold number of user tokens, the one or more user tokens indicate viewability of the item by users associated with the one or more user tokens, wherein the request comprises a search query identifying search criteria including one or more tokens up to a threshold number of tokens, the one or more tokens includes at least a user token identifying the user, and wherein generating the request comprises: determining that a super followee token is to be included in the search query, the super followee token corresponding to a super followee user that owns an item visible to a number of users that meets a threshold number of users, replacing the super followee token with a super doc token when the included super followee token causes the one or more tokens to exceed the threshold number of tokens, the super doc token identifying a type of item owned by the super followee user; receiving one or more items in response to the request, the one or more items including at least one of the one or more tokens and further being visible to the user; and providing the one or more items for display to the user within the stream in response to the request. | 1. A machine-implemented method, comprising: receiving an indication of a request from a user to view a stream associated with the user; generating a request for one or more items, of a plurality of items, that are visible to the user for display within the stream, wherein each of the plurality of items includes one or more user tokens up to a threshold number of user tokens, the one or more user tokens indicate viewability of the item by users associated with the one or more user tokens, wherein the request comprises a search query identifying search criteria including one or more tokens up to a threshold number of tokens, the one or more tokens includes at least a user token identifying the user, and wherein generating the request comprises: determining that a super followee token is to be included in the search query, the super followee token corresponding to a super followee user that owns an item visible to a number of users that meets a threshold number of users, replacing the super followee token with a super doc token when the included super followee token causes the one or more tokens to exceed the threshold number of tokens, the super doc token identifying a type of item owned by the super followee user; receiving one or more items in response to the request, the one or more items including at least one of the one or more tokens and further being visible to the user; and providing the one or more items for display to the user within the stream in response to the request. 3. The method of claim 1 , the one or more tokens further including at least one owner token, the owner token identifying a second user associated with the first user. | 0.626218 |
1. A method comprising: by one or more computers, accessing a graph, the graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user; by the one or more computers, determining, from the graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers, aggregating the user's “like” of the first page to a main page that is associated with the particular version and one or more other versions of the media content; by the one or more computers, determining that the user “likes” more than one page associated with the media content; and by the one or more computers, removing all “likes” of the user associated with each page except the main page. | 1. A method comprising: by one or more computers, accessing a graph, the graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user; by the one or more computers, determining, from the graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers, aggregating the user's “like” of the first page to a main page that is associated with the particular version and one or more other versions of the media content; by the one or more computers, determining that the user “likes” more than one page associated with the media content; and by the one or more computers, removing all “likes” of the user associated with each page except the main page. 6. The method of claim 1 , wherein the “like” comprises an indication that the user likes the media content. | 0.814208 |
11. A computer-readable media including program instructions for performing a method, comprising the steps of: obtaining a search query; generating one or more semantic query key terms each including at least one semantic query token representing a semantic relationship derived from the search query, comprising: selecting a word and at least one further word that is linguistically related to the word from the search query; determining information regarding use of the word and the further word within the search query comprising one or more of a part of speech and a grammatical role; and concatenating each of the word and the further word with the respective information into a single string as the semantic index key terms; accessing an inverted index comprising at least one semantic index key term indexed against at least one of the references; querying the inverted index with the semantic query key term; and receiving a set of references to information passages associated with the semantic query key term that corresponds to the semantic index key term indexed by the inverted index, wherein the steps are performed by a central processing unit. | 11. A computer-readable media including program instructions for performing a method, comprising the steps of: obtaining a search query; generating one or more semantic query key terms each including at least one semantic query token representing a semantic relationship derived from the search query, comprising: selecting a word and at least one further word that is linguistically related to the word from the search query; determining information regarding use of the word and the further word within the search query comprising one or more of a part of speech and a grammatical role; and concatenating each of the word and the further word with the respective information into a single string as the semantic index key terms; accessing an inverted index comprising at least one semantic index key term indexed against at least one of the references; querying the inverted index with the semantic query key term; and receiving a set of references to information passages associated with the semantic query key term that corresponds to the semantic index key term indexed by the inverted index, wherein the steps are performed by a central processing unit. 12. The computer-readable media of claim 11 , further comprising program instructions for: determining a set of candidate passages from the set of references to information passages associated with the semantic query key term obtained from the inverted index, comprising: determining a relevance score for at least one semantic query token matching a semantic index token; and filtering the set of candidate information passages based at least in part upon the relevance score; and returning the filtered set of candidate information passages as a set of match candidates. | 0.5 |
1. A computer controlled method comprising: presenting a workspace window responsive to a relationship data structure that represents relationships between pieces of information; presenting a presentation set of an ordered set of text strings from an electronic document, said presentation set including one or more identified strings; receiving a quick-click command invocation on said one or more identified strings by said workspace window; modifying said relationship data structure by adding an entity/relationship object to said relationship data structure responsive to said quick-click command invocation and said one or more identified strings; detecting a drag-and-drop operation dragging a first instance representation to a drop point; combining the first instance representation with a second instance representation, the second instance representation determined to be nearest to the drop point and within a threshold distance from the drop point, wherein the threshold distance is a multidimensional vector, a selection of strength of a relationship being responsive to weighted values of the multidimensional vector's elements, so that: if the nearest instance representation is an entity object, a new composite object is created that includes the entity object and an entity/relationship object represented by the dragged instance representation, and if the nearest instance representation is a first composite object, the entity/relationship object represented by the dragged instance representation is added to the first composite object. | 1. A computer controlled method comprising: presenting a workspace window responsive to a relationship data structure that represents relationships between pieces of information; presenting a presentation set of an ordered set of text strings from an electronic document, said presentation set including one or more identified strings; receiving a quick-click command invocation on said one or more identified strings by said workspace window; modifying said relationship data structure by adding an entity/relationship object to said relationship data structure responsive to said quick-click command invocation and said one or more identified strings; detecting a drag-and-drop operation dragging a first instance representation to a drop point; combining the first instance representation with a second instance representation, the second instance representation determined to be nearest to the drop point and within a threshold distance from the drop point, wherein the threshold distance is a multidimensional vector, a selection of strength of a relationship being responsive to weighted values of the multidimensional vector's elements, so that: if the nearest instance representation is an entity object, a new composite object is created that includes the entity object and an entity/relationship object represented by the dragged instance representation, and if the nearest instance representation is a first composite object, the entity/relationship object represented by the dragged instance representation is added to the first composite object. 2. The computer controlled method of claim 1 , wherein said entity/relationship object includes a reference to said electronic document. | 0.611933 |
12. The apparatus of claim 11 , wherein the user interaction with the selected one of the displayed paths includes: selecting at least one class attribute for inclusion in the returned search results; and applying the defined at least one constraint to the selected at least one class attribute. | 12. The apparatus of claim 11 , wherein the user interaction with the selected one of the displayed paths includes: selecting at least one class attribute for inclusion in the returned search results; and applying the defined at least one constraint to the selected at least one class attribute. 13. The apparatus of claim 12 , wherein the displayed at least one graphically illustrated path includes at least two illustrated paths, the at least two illustrated paths including a first path and a second path; the processor further operative with the program instructions to receive input from the user to select one of the at least two illustrated paths; and wherein the received input indicative of the user interaction includes input indicative of the user's interaction with the selected one of the at least two illustrative paths. | 0.883066 |
1. A computer-implemented method comprising: accessing a directory of entities that indicates, for each entity, (i) a reference name of the entity, (ii) an entity type associated with the entity, and (iii) a geographic location associated with the entity; obtaining, for each of one or more of the entities, a set of one or more canonical names for the entity, wherein the set of canonical names for the entity includes the reference name for the entity; obtaining, for each of the one or more entities, a phonetic representation of each canonical name of the set of canonical names for the entity; selecting a particular geographic area and a particular entity type; selecting entities from the directory that (i) have an entity type that matches the particular entity type, and (ii) have a geographic location that matches the particular geographic area; generating, for each of the selected entities, a record in an entity type-specific, geo-localized entity database for the particular geographic area, wherein, for each of the selected entities, the record indicates at least (i) a reference name of the selected entity, (ii) a respective phonetic representation of each canonical name of the set of canonical names for the selected entity; receiving an utterance that includes (i) a first term that indicates the particular entity type, (ii) a second term that indicates an entity name, and (iii) a third term that is associated with the particular geographic area; determining a candidate transcription of the utterance, the candidate transcription including a type term corresponding to the first term, a name term corresponding to the second term, and a geographic term corresponding to the third term; determining that the candidate transcription includes (i) the type term, (ii) the name term, and (iii) the geographic term; in response to determining that the candidate transcription includes (i) the type term, (ii) the name term, and (iii) the geographic term, determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, a phonetic representation of the second term matches a particular phonetic representation of a particular canonical name of a set of canonical names associated with a particular entity; and in response to determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, the phonetic representation of the second term matches the particular phonetic representation of the particular canonical name of the set of canonical names associated with the particular entity, outputting the reference name associated with the particular entity as a transcription of the second term. | 1. A computer-implemented method comprising: accessing a directory of entities that indicates, for each entity, (i) a reference name of the entity, (ii) an entity type associated with the entity, and (iii) a geographic location associated with the entity; obtaining, for each of one or more of the entities, a set of one or more canonical names for the entity, wherein the set of canonical names for the entity includes the reference name for the entity; obtaining, for each of the one or more entities, a phonetic representation of each canonical name of the set of canonical names for the entity; selecting a particular geographic area and a particular entity type; selecting entities from the directory that (i) have an entity type that matches the particular entity type, and (ii) have a geographic location that matches the particular geographic area; generating, for each of the selected entities, a record in an entity type-specific, geo-localized entity database for the particular geographic area, wherein, for each of the selected entities, the record indicates at least (i) a reference name of the selected entity, (ii) a respective phonetic representation of each canonical name of the set of canonical names for the selected entity; receiving an utterance that includes (i) a first term that indicates the particular entity type, (ii) a second term that indicates an entity name, and (iii) a third term that is associated with the particular geographic area; determining a candidate transcription of the utterance, the candidate transcription including a type term corresponding to the first term, a name term corresponding to the second term, and a geographic term corresponding to the third term; determining that the candidate transcription includes (i) the type term, (ii) the name term, and (iii) the geographic term; in response to determining that the candidate transcription includes (i) the type term, (ii) the name term, and (iii) the geographic term, determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, a phonetic representation of the second term matches a particular phonetic representation of a particular canonical name of a set of canonical names associated with a particular entity; and in response to determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, the phonetic representation of the second term matches the particular phonetic representation of the particular canonical name of the set of canonical names associated with the particular entity, outputting the reference name associated with the particular entity as a transcription of the second term. 2. The method of claim 1 , wherein obtaining, for each of the one or more entities, a phonetic representation of each canonical name of the set of canonical names for the entity, comprises: generating the phonetic representations for each canonical name by applying one or more pronunciation rules to each canonical name. | 0.634323 |
13. The system of claim 12 , wherein the instructions that, when executed, further perform steps comprising: segmenting the audio data into a plurality of time segments; transforming each of the time segments into first bins representing the first amplitude data as a function of frequency; and comparing the first bins of each time segment to second bins representing the second amplitude data, wherein the second amplitude data corresponds to positively identified occurrences of the at least one spoken word sound, or portions thereof, spoken over various non-spoken word sounds, the training data accessed from a training set database. | 13. The system of claim 12 , wherein the instructions that, when executed, further perform steps comprising: segmenting the audio data into a plurality of time segments; transforming each of the time segments into first bins representing the first amplitude data as a function of frequency; and comparing the first bins of each time segment to second bins representing the second amplitude data, wherein the second amplitude data corresponds to positively identified occurrences of the at least one spoken word sound, or portions thereof, spoken over various non-spoken word sounds, the training data accessed from a training set database. 14. The system of claim 13 , wherein the training set database comprises a plurality of categories, each of the categories representing a different one of the phonemes, and each of the categories representing one of the phonemes spoken over a plurality of non-spoken word sounds. | 0.839679 |
25. A system for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the system comprising: a database maintaining at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; means for receiving an initial trigger date for an initial trigger legal event; means for selecting one or more date calculation instructions from the database based on the initial trigger legal event; means for calculating one or more event dates based on the initial trigger date and the retrieved date calculation instructions; means for transmitting the one or more calculated event dates to a user client; means for maintaining a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; means for monitoring a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; means for automatically determining whether the one or more date calculation instructions identified in the record are identified in the changes table; for each one of the one or more date calculation instructions identified in the changes table, means for recalculating the associated event date based on the change to the corresponding date calculation instruction; and means for transmitting the recalculated one or more event dates to the user client. | 25. A system for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the system comprising: a database maintaining at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; means for receiving an initial trigger date for an initial trigger legal event; means for selecting one or more date calculation instructions from the database based on the initial trigger legal event; means for calculating one or more event dates based on the initial trigger date and the retrieved date calculation instructions; means for transmitting the one or more calculated event dates to a user client; means for maintaining a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; means for monitoring a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; means for automatically determining whether the one or more date calculation instructions identified in the record are identified in the changes table; for each one of the one or more date calculation instructions identified in the changes table, means for recalculating the associated event date based on the change to the corresponding date calculation instruction; and means for transmitting the recalculated one or more event dates to the user client. 26. The system of claim 25 further comprising: means for maintaining a relationship table storing relationship information for a plurality of the date calculation instructions, the relationship table indicating whether a particular date calculation instruction is related to another date calculation instruction; and means for updating relationship information in the relationship table based on the changed date calculation instructions. | 0.55841 |
12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. | 12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. 14. The method for building and utilizing interactive software system predictive models using biometric data of claim 12 , wherein the biometric data includes at least one of the biometric data selected from the group of biometric data consisting of: data acquired from measuring the user's heart beat; data acquired from measuring the user's eye rotation; data acquired from measuring the user's eye dilation; data acquired from measuring the user's skin color; data acquired from measuring the user's perspiration; data acquired from measuring the user's respiration; data acquired from measuring the user's oxygen saturation; data acquired from measuring the user's blood pressure data acquired from measuring the user's skin temperature; data acquired from measuring the user's muscle tension; data acquired from measuring the user's neural activity; data acquired from measuring the user's eye blinking; data acquired from measuring the user's facial expression; data acquired from measuring the user's voice and/or speech; and data acquired from measuring the user's interactions with hardware associated with the user's interaction with the interactive software system. | 0.539982 |
20. A machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes: storing said collection of XML documents in one or more base database structures managed by a database system for storing said collection of XML documents; wherein each XML document of said collection of XML documents is stored, within the one or more base database structures, in an unshredded form; based on pattern data that indicates elements defined for a particular XML document type, creating a table for the particular XML document type separate from said one or more base database structures in which said collection of XML documents are stored; wherein said table includes a plurality of columns; wherein each column of said plurality of columns corresponds to a different element indicated in the pattern data; wherein each column contains only values of the element of the XML document type to which the column corresponds; wherein each row of said table corresponds to a corresponding XML document in said collection; wherein each row of said table stores values for elements from the corresponding XML document; wherein said pattern data indicates, for each column of said plurality of columns, the different element, of the particular XML document type, that corresponds to the column; using said table to answer a first query requesting data from said collection of XML documents; responding to said first query without accessing said one or more base database structures; and responding to a second query requesting data from said collection of XML documents by providing one or more unshredded XML documents from said one or more base database structures. | 20. A machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes: storing said collection of XML documents in one or more base database structures managed by a database system for storing said collection of XML documents; wherein each XML document of said collection of XML documents is stored, within the one or more base database structures, in an unshredded form; based on pattern data that indicates elements defined for a particular XML document type, creating a table for the particular XML document type separate from said one or more base database structures in which said collection of XML documents are stored; wherein said table includes a plurality of columns; wherein each column of said plurality of columns corresponds to a different element indicated in the pattern data; wherein each column contains only values of the element of the XML document type to which the column corresponds; wherein each row of said table corresponds to a corresponding XML document in said collection; wherein each row of said table stores values for elements from the corresponding XML document; wherein said pattern data indicates, for each column of said plurality of columns, the different element, of the particular XML document type, that corresponds to the column; using said table to answer a first query requesting data from said collection of XML documents; responding to said first query without accessing said one or more base database structures; and responding to a second query requesting data from said collection of XML documents by providing one or more unshredded XML documents from said one or more base database structures. 21. The machine-readable storage medium of claim 20 , further comprising instructions which, when executed by one or more processors, causes: receiving a new XML document to store in said collection of XML documents; extracting a new set of values from the new XML document, wherein each value in said set of new values corresponds to a different element contained in said collection of XML documents; populating each column of said plurality of columns from said tables with the new set of values extracted from the new XML document. | 0.5 |
3. The method of claim 2 , further including: if the ELSE or ELSEIF statements are found, searching for a THEN statement associated with the IF statement; and searching for a reset clause between the IF statement and the THEN statement. | 3. The method of claim 2 , further including: if the ELSE or ELSEIF statements are found, searching for a THEN statement associated with the IF statement; and searching for a reset clause between the IF statement and the THEN statement. 4. The method of claim 3 , further including: searching for a clock statement between the ELSE or ELSEIF statements and the THEN statement. | 0.87933 |
7. A communication device comprising: a microphone; a speaker; an input device; a display; a camera; a wireless communicating system; a voice communicating implementer to implement voice communication by utilizing said microphone and said speaker; an OCR implementer, wherein an image data is input via said camera and alphanumeric data is extracted from said image data; a caller ID implementer which retrieves a predetermined color data and/or sound data which is specific to the caller of the incoming call received by said communication device, and outputs the color and/or sound corresponding to said predetermined color data and/or sound data from said communication device; an auto time adjusting implementer which automatically adjusts the clock of said communication device in accordance with a wireless signal received by said wireless communication system; a calculating implementer which implements mathematical calculation by utilizing digits input via said input device; a word processing implementer which includes a bold formatting implementer, an italic formatting implementer, and/or a font formatting implementer, wherein said bold formatting implementer changes alphanumeric data to bold, said italic formatting implementer changes alphanumeric data to italic, and said font formatting implementer changes alphanumeric data to a selected font; a startup software implementer, wherein a startup software identification data storage area stores a startup software identification data which is an identification of a certain software program selected by the user, and when the power of said communication device is turned on, said startup software implementer retrieves said startup software identification data from said startup software identification data storage area and activates said certain software program; a stereo audio data playback implementer which playbacks and outputs in a stereo fashion the audio data selected by the user of said communication device; a digital camera implementer, wherein a photo quality identifying command is input via said input device, and when a photo taking command is input via said input device, a photo data retrieved via said camera is stored in a photo data storage area with the quality indicated by said photo quality identifying command; a multiple language displaying implementer, wherein a specific language is selected from a plurality of languages, and the interface to operate said communication device is displayed with said specific language; a caller's information displaying implementer which displays a personal information regarding caller on said display when said communication device receives a phone call; a communication device remote controlling implementer, wherein said communication device is remotely controlled by a computer via a network; a shortcut icon displaying implementer, wherein a shortcut icon is displayed on said display, and a software program indicated by said shortcut icon is activated when said shortcut icon is selected; and a multiple channel processing implementer which sends data in a wireless fashion by utilizing multiple channels. | 7. A communication device comprising: a microphone; a speaker; an input device; a display; a camera; a wireless communicating system; a voice communicating implementer to implement voice communication by utilizing said microphone and said speaker; an OCR implementer, wherein an image data is input via said camera and alphanumeric data is extracted from said image data; a caller ID implementer which retrieves a predetermined color data and/or sound data which is specific to the caller of the incoming call received by said communication device, and outputs the color and/or sound corresponding to said predetermined color data and/or sound data from said communication device; an auto time adjusting implementer which automatically adjusts the clock of said communication device in accordance with a wireless signal received by said wireless communication system; a calculating implementer which implements mathematical calculation by utilizing digits input via said input device; a word processing implementer which includes a bold formatting implementer, an italic formatting implementer, and/or a font formatting implementer, wherein said bold formatting implementer changes alphanumeric data to bold, said italic formatting implementer changes alphanumeric data to italic, and said font formatting implementer changes alphanumeric data to a selected font; a startup software implementer, wherein a startup software identification data storage area stores a startup software identification data which is an identification of a certain software program selected by the user, and when the power of said communication device is turned on, said startup software implementer retrieves said startup software identification data from said startup software identification data storage area and activates said certain software program; a stereo audio data playback implementer which playbacks and outputs in a stereo fashion the audio data selected by the user of said communication device; a digital camera implementer, wherein a photo quality identifying command is input via said input device, and when a photo taking command is input via said input device, a photo data retrieved via said camera is stored in a photo data storage area with the quality indicated by said photo quality identifying command; a multiple language displaying implementer, wherein a specific language is selected from a plurality of languages, and the interface to operate said communication device is displayed with said specific language; a caller's information displaying implementer which displays a personal information regarding caller on said display when said communication device receives a phone call; a communication device remote controlling implementer, wherein said communication device is remotely controlled by a computer via a network; a shortcut icon displaying implementer, wherein a shortcut icon is displayed on said display, and a software program indicated by said shortcut icon is activated when said shortcut icon is selected; and a multiple channel processing implementer which sends data in a wireless fashion by utilizing multiple channels. 10. The communication device of claim 7 , wherein said predetermined color data and/or sound data is the one selected by the user from multiple selections in advance to receiving said incoming call. | 0.796939 |
21. A computer program product for use at a computer system, the computer program product for implementing a method for presenting message conversation data, the computer program product comprising one or more computer-readable storage device having stored thereon computer-executable instructions that, when executed by a processor, cause the computer system to perform the method of claim 7 . | 21. A computer program product for use at a computer system, the computer program product for implementing a method for presenting message conversation data, the computer program product comprising one or more computer-readable storage device having stored thereon computer-executable instructions that, when executed by a processor, cause the computer system to perform the method of claim 7 . 26. The computer program product as recited in claim 21 , wherein computer-executable instructions that when executed cause the computer system to retrieve persisted conversation attribute values from the electronic mail conversation item comprise computer-executable instructions that when executed cause the computer system to retrieve one or more attribute values for an electronic mail message selected from among a sent time value, a sender value, a summary value, a link value, and a recipient delta value. | 0.906708 |
8. A method of efficiently mining the control flow graph from execution logs of a distributed system, said method comprising: utilizing at least one processor to execute computer code that performs the steps of: receiving a plurality of execution logs; mining at least one template from the plurality of execution logs in the first-phase; said mining comprising creating at least one template, via employing a two-stage template mining technique; said first-stage creating approximate-templates via a dictionary based logline transformation in order to attain scalability and said second-stage refining the mined approximate-templates by leveraging the multimodal (text+temporal-vicinity) signature of each approximate-template; and generating the control-flow graph between the mined templates in the second-phase via a two-stage technique; said first-stage creating for each template, the set of its temporally co-occurring templates, referred to as its Nearest-Neighbor-Group, by leveraging the time-series of occurrence of each template; and said second-stage, in a single-pass of the logstream, determining for each template, its immediate predecessors/successors by tracking predecessors/successors on the projected logstream on the Nearest-Neighbor group of the template, and stitching the mined successors of each template to construct the desired control flow graph. | 8. A method of efficiently mining the control flow graph from execution logs of a distributed system, said method comprising: utilizing at least one processor to execute computer code that performs the steps of: receiving a plurality of execution logs; mining at least one template from the plurality of execution logs in the first-phase; said mining comprising creating at least one template, via employing a two-stage template mining technique; said first-stage creating approximate-templates via a dictionary based logline transformation in order to attain scalability and said second-stage refining the mined approximate-templates by leveraging the multimodal (text+temporal-vicinity) signature of each approximate-template; and generating the control-flow graph between the mined templates in the second-phase via a two-stage technique; said first-stage creating for each template, the set of its temporally co-occurring templates, referred to as its Nearest-Neighbor-Group, by leveraging the time-series of occurrence of each template; and said second-stage, in a single-pass of the logstream, determining for each template, its immediate predecessors/successors by tracking predecessors/successors on the projected logstream on the Nearest-Neighbor group of the template, and stitching the mined successors of each template to construct the desired control flow graph. 11. The method according to claim 8 , wherein said mining comprises utilizing at least one text-clustering technique selected from the group consisting of: an edit-distance technique and a dictionary-based logline parameterization. | 0.671738 |
1. An arousal state classification model generating device for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating device characterized by comprising: learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. | 1. An arousal state classification model generating device for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating device characterized by comprising: learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. 4. The arousal state classification model generating device according to claim 1 , characterized in that an HMM (Hidden Markov Model) is used for the statistical model. | 0.622863 |
5. The system of claim 1 , further comprising an ingest actors module, the ingest actors module configured to: receive third party application data from at least one of a third party application and a third party device, and transmit the third party application data for further processing by at least one of the plurality of scoring engines, the distributed analytic platform and the real time analytic engine. | 5. The system of claim 1 , further comprising an ingest actors module, the ingest actors module configured to: receive third party application data from at least one of a third party application and a third party device, and transmit the third party application data for further processing by at least one of the plurality of scoring engines, the distributed analytic platform and the real time analytic engine. 7. The system of claim 5 , wherein the plurality of sensors, the plurality of scoring engines, the distributed analytic platform, the real time analytic engine, the control plane engine, and the ingest actors module communicate by sending associated messages over an enterprise system bus. | 0.934323 |
14. A computer-readable volatile or non-volatile storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform: maintaining a plurality of statistics about nodes in said XML documents; based upon said plurality of statistics, estimating a cost for computing at least one path expression in said query on said XML documents, said cost comprising an estimated CPU cost and an estimated I/O cost; wherein the cost of computing the at least one path expression is determined based on a mathematical function of the estimated CPU cost and the estimated I/O cost; wherein computing said at least one path expression is performed using streaming evaluation; wherein estimating a cost for computing a path expression of the at least one path expression includes: estimating an input-size of said XML documents, said input-size being based on units of bytes; based on a portion of said plurality of statistics about said nodes, estimating an output-size associated with said path expression. | 14. A computer-readable volatile or non-volatile storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform: maintaining a plurality of statistics about nodes in said XML documents; based upon said plurality of statistics, estimating a cost for computing at least one path expression in said query on said XML documents, said cost comprising an estimated CPU cost and an estimated I/O cost; wherein the cost of computing the at least one path expression is determined based on a mathematical function of the estimated CPU cost and the estimated I/O cost; wherein computing said at least one path expression is performed using streaming evaluation; wherein estimating a cost for computing a path expression of the at least one path expression includes: estimating an input-size of said XML documents, said input-size being based on units of bytes; based on a portion of said plurality of statistics about said nodes, estimating an output-size associated with said path expression. 25. The computer-readable volatile or non-volatile storage medium of claim 14 , wherein the XML documents are stored in object relational form in the database. | 0.540201 |
12. The method of claim 8 and further comprising weighting and combining the first and second sets of geographic classes. | 12. The method of claim 8 and further comprising weighting and combining the first and second sets of geographic classes. 13. The method of claim 12 wherein weighting comprises weighting the second set of geographic classes higher than the first set of geographic classes. | 0.96043 |
1. A computer-implemented method comprising: selecting at least one rule included in an operational knowledge associated with an application being monitored; associating, one or more playbook-based tasks, playbook-based views, or playbook-based links with the at least one rule, the playbook-based tasks, playbook-based views, and playbook-based links being for one or more of diagnosing, resolving, and verifying a problem associated with the application; and generating an integrated management pack responsive to the selecting and the associating, the integrated management pack enabling sharing of information between the operational knowledge and the one or more playbook-based tasks, the playbook-based views, or the playbook-based links. | 1. A computer-implemented method comprising: selecting at least one rule included in an operational knowledge associated with an application being monitored; associating, one or more playbook-based tasks, playbook-based views, or playbook-based links with the at least one rule, the playbook-based tasks, playbook-based views, and playbook-based links being for one or more of diagnosing, resolving, and verifying a problem associated with the application; and generating an integrated management pack responsive to the selecting and the associating, the integrated management pack enabling sharing of information between the operational knowledge and the one or more playbook-based tasks, the playbook-based views, or the playbook-based links. 4. A method as recited in claim 1 , wherein the selecting and associating specify information and resources for presentation in an operator or administrator management console user interface. | 0.711068 |
6. The method of claim 1 , wherein the obtaining of the second part of information associated with the first key word comprises querying a database for the second part of information. | 6. The method of claim 1 , wherein the obtaining of the second part of information associated with the first key word comprises querying a database for the second part of information. 7. The method of claim 6 , wherein the querying the database for the second part of information comprises querying a transaction system that is connected to a network for the second part of information corresponding to the first key word. | 0.884676 |
11. Non-transitory computer readable media embodying executable instructions for controlling a computer for an automatic diet tracking method, comprising: receiving text from a user that describes a food that is to be tracked; parsing the received text into text segments; identifying automatically in each parsed text segment a food quantity value and a food quantity unit for said food that is to be tracked, said identifying comprising searching said parsed text segment for a quantity value followed directly by a quantity unit, and assigning said quantity value and said quantity unit to be said food quantity value and said food quantity unit for the food to be tracked, and upon not finding a quantity value followed directly by a quantity unit, selecting as said food quantity value and said food quantity unit a most frequently occurring quantity value and quantity unit for said food to be tracked; cleaning the parsed text segments to identify and remove words, connected spaces, and punctuation that are not used to identify food and produce parsed cleaned text; processing the parsed cleaned text segments using a text match algorithm to find said food that is to be tracked in each parsed cleaned text segment comprising ranking each food text match found using a ranking process, and selecting the food with a predetermined rank to be the food that is to be tracked; and reporting diet tracking information for said food to be tracked. | 11. Non-transitory computer readable media embodying executable instructions for controlling a computer for an automatic diet tracking method, comprising: receiving text from a user that describes a food that is to be tracked; parsing the received text into text segments; identifying automatically in each parsed text segment a food quantity value and a food quantity unit for said food that is to be tracked, said identifying comprising searching said parsed text segment for a quantity value followed directly by a quantity unit, and assigning said quantity value and said quantity unit to be said food quantity value and said food quantity unit for the food to be tracked, and upon not finding a quantity value followed directly by a quantity unit, selecting as said food quantity value and said food quantity unit a most frequently occurring quantity value and quantity unit for said food to be tracked; cleaning the parsed text segments to identify and remove words, connected spaces, and punctuation that are not used to identify food and produce parsed cleaned text; processing the parsed cleaned text segments using a text match algorithm to find said food that is to be tracked in each parsed cleaned text segment comprising ranking each food text match found using a ranking process, and selecting the food with a predetermined rank to be the food that is to be tracked; and reporting diet tracking information for said food to be tracked. 17. The non-transitory computer readable media of claim 11 , wherein said searching for a food quantity value and a food quantity unit comprises performing a fuzzy logic search of said parsed text for a written number or a numeric value, and upon finding said written number or numeric value, performing a further fuzzy logic search of said parsed text for a match of a quantity unit term directly following said written number or numeric quantity and, if found, assigning said written number or numeric quantity to said food quantity value and assigning said quantity unit term to said food quantity unit. | 0.5 |
1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. | 1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. 17. The system of claim 1 : wherein the sandboxed program is configured to obtain an explicit permission to communicate with any device other than an origin server. | 0.63591 |
11. The method according to claim 1 , wherein: the formulating the plurality of different subqueries includes formulating two or more of the subqueries from the input query. | 11. The method according to claim 1 , wherein: the formulating the plurality of different subqueries includes formulating two or more of the subqueries from the input query. 12. The method according to claim 11 , wherein: the input query includes specified text; the formulating two or more of the subqueries from the input query includes modifying the specified text of the input query in a first way to formulate a first of the subqueries, and modifying the specified text of the input query in a second way to formulate a second of the subqueries; and the applying the logical synthesis component includes combining all the selected ones of the candidate answers to the subqueries in a defined manner to obtain the candidate answer for the input query. | 0.798057 |
1. A method for transcribing speech in a communication session comprising: transmitting a virtual communication session in substantially real-time to a plurality of end user devices; receiving, by one or more processors, a combined media stream comprising a plurality of media sub-streams each associated with one of the plurality of end user devices, wherein each of the plurality of media sub-streams in the combined media stream comprises a respective video component and a respective audio component; for each of the plurality of media sub-streams, separating, by the one or more processors, the respective audio component from the respective video component; for each separate audio component, transcribing, by the one or more processors, at least a portion of speech from the audio component to text; providing a transcription in substantially real-time; and annotating the text for the audio component of each respective media sub-stream to include additional content, wherein annotating the text comprises: determining one or more keywords of the text; selecting, based on the one or more keywords, one or more advertisements or a link; and updating the transcription with the one or more advertisements or the link in association with at least a portion of the text. | 1. A method for transcribing speech in a communication session comprising: transmitting a virtual communication session in substantially real-time to a plurality of end user devices; receiving, by one or more processors, a combined media stream comprising a plurality of media sub-streams each associated with one of the plurality of end user devices, wherein each of the plurality of media sub-streams in the combined media stream comprises a respective video component and a respective audio component; for each of the plurality of media sub-streams, separating, by the one or more processors, the respective audio component from the respective video component; for each separate audio component, transcribing, by the one or more processors, at least a portion of speech from the audio component to text; providing a transcription in substantially real-time; and annotating the text for the audio component of each respective media sub-stream to include additional content, wherein annotating the text comprises: determining one or more keywords of the text; selecting, based on the one or more keywords, one or more advertisements or a link; and updating the transcription with the one or more advertisements or the link in association with at least a portion of the text. 3. The method of claim 1 , wherein the one or more advertisements are provided at least one of in a border and next to a field containing the text. | 0.61466 |
10. A computer-readable storage medium having computer-executable instructions stored thereon that, when executed by a processor of a computer system, cause the computer system to perform a computer process for presenting a customized menu item in a menu display of a media application, the computer process comprising: receiving one or more application packages from a communications network at the computer system, wherein each application package contains one or more resources for customized application pages of the media application; storing the one or more application packages on the computer system in a storage system external to the media application; accessing internal menu markup data of the media application for rendering a set of menu items for the menu display; determining that the internal menu markup data indicates that the set of menu items for the menu display includes one or more built-in menu items installed with the media application, wherein: the internal menu markup data specifies a reference to a built-in application page of the media application for each built-in menu item, and selection of at least one of the built-in menu items launches a built-in application page that provides functionality for browsing and selecting broadcast television content received by the computer system; determining that the internal menu markup data includes a placeholder for an offering tile for a customized menu item within the set of menu items for the menu display, wherein: the customized menu item provides access to online television content, the placeholder references an application package and a resource for a customized application page, and selection of the offering tile for the customized menu item launches the customized application page to provide functionality for browsing and selecting categories of the online television content; searching for the application package and the resource referenced by the placeholder in the storage system external to the media application; if the application package and the resource referenced by the placeholder are found in the storage system external to the media application: accessing the application package referenced by the placeholder from the storage system external to the media application, accessing the resource referenced by the placeholder from the accessed application package, rendering the one or more built-in menu items and the offering tile for the customized menu item in the menu display of the media application, and customizing display of the offering tile for the customized menu item displays updated using content from the resource of the accessed application package; and if the application package and the resource referenced by the placeholder are not found in the storage system external to the media application: rendering the one or more built-in menu items in the menu display of the media application, and setting the offering tile for the customized menu item to be hidden from view. | 10. A computer-readable storage medium having computer-executable instructions stored thereon that, when executed by a processor of a computer system, cause the computer system to perform a computer process for presenting a customized menu item in a menu display of a media application, the computer process comprising: receiving one or more application packages from a communications network at the computer system, wherein each application package contains one or more resources for customized application pages of the media application; storing the one or more application packages on the computer system in a storage system external to the media application; accessing internal menu markup data of the media application for rendering a set of menu items for the menu display; determining that the internal menu markup data indicates that the set of menu items for the menu display includes one or more built-in menu items installed with the media application, wherein: the internal menu markup data specifies a reference to a built-in application page of the media application for each built-in menu item, and selection of at least one of the built-in menu items launches a built-in application page that provides functionality for browsing and selecting broadcast television content received by the computer system; determining that the internal menu markup data includes a placeholder for an offering tile for a customized menu item within the set of menu items for the menu display, wherein: the customized menu item provides access to online television content, the placeholder references an application package and a resource for a customized application page, and selection of the offering tile for the customized menu item launches the customized application page to provide functionality for browsing and selecting categories of the online television content; searching for the application package and the resource referenced by the placeholder in the storage system external to the media application; if the application package and the resource referenced by the placeholder are found in the storage system external to the media application: accessing the application package referenced by the placeholder from the storage system external to the media application, accessing the resource referenced by the placeholder from the accessed application package, rendering the one or more built-in menu items and the offering tile for the customized menu item in the menu display of the media application, and customizing display of the offering tile for the customized menu item displays updated using content from the resource of the accessed application package; and if the application package and the resource referenced by the placeholder are not found in the storage system external to the media application: rendering the one or more built-in menu items in the menu display of the media application, and setting the offering tile for the customized menu item to be hidden from view. 15. The computer-readable storage medium of claim 10 further comprising stored computer-executable instructions for: searching the storage system external to the media application for a resource provider identifier to find the application package referenced by the placeholder included in the internal menu markup data of the media application. | 0.5 |
12. The system of claim 11 , wherein the review set is determined based on a sampling rate. | 12. The system of claim 11 , wherein the review set is determined based on a sampling rate. 13. The system of claim 12 , wherein the method further comprises receiving a sampling rate selection from a user. | 0.944229 |
1. A method enabling cross linguistic communication through speech and text machine translation, comprising method operations of: receiving a first and a second language selection; receiving an expression in the first language; presenting the expression in the first language for verification; translating the verified expression into an expression in the second language; confirming the meaning of terms within the verified expression in the first language; back-translating the expression in the second language to a back-translated expression in the first language; and verifying the back-translated expression in the first language, wherein at least one method operation is executed through a processor. | 1. A method enabling cross linguistic communication through speech and text machine translation, comprising method operations of: receiving a first and a second language selection; receiving an expression in the first language; presenting the expression in the first language for verification; translating the verified expression into an expression in the second language; confirming the meaning of terms within the verified expression in the first language; back-translating the expression in the second language to a back-translated expression in the first language; and verifying the back-translated expression in the first language, wherein at least one method operation is executed through a processor. 2. The method of claim 1 , wherein the method operation of confirming the meaning of terms within the verified expression in the first language includes, receiving a selection of one of the terms; accessing a database supplying Meaning Cues associated with the one of the terms, each of the Meaning Cues representing a sense of the one of the terms; and selecting one of the Meaning Cues. | 0.5 |
1. A computer-implemented method for selecting one or more terms for a glossary in a document processing system, said method comprising: a processor executing program code that performs the functions of: receiving, from a spell checker, a selected term from within a document that has been rejected, where said term is one of a misspelled word or a misspelled phrase; applying a set of one or more rules to said term, each of said rule being arranged to assign a result value to said term as at least one of a Boolean or ordinal value, wherein said result value is an output score of the term when processed by a rule; applying a function to said term, said function being arranged to combine said assigned result values to produce an overall probability value relating to the likelihood of said term being a candidate for inclusion in a glossary associated with said document; presenting: said term as a candidate term for inclusion in said glossary, and said assigned result values; in response to receiving an approval to include said candidate term in the glossary, storing said candidate term to said glossary with a record of one or more of said result values assigned by said set of one or more rules; in response to receiving a denial to include said candidate term in said glossary, discarding said candidate term; and providing an indication of whether said term was subsequently included in said glossary. | 1. A computer-implemented method for selecting one or more terms for a glossary in a document processing system, said method comprising: a processor executing program code that performs the functions of: receiving, from a spell checker, a selected term from within a document that has been rejected, where said term is one of a misspelled word or a misspelled phrase; applying a set of one or more rules to said term, each of said rule being arranged to assign a result value to said term as at least one of a Boolean or ordinal value, wherein said result value is an output score of the term when processed by a rule; applying a function to said term, said function being arranged to combine said assigned result values to produce an overall probability value relating to the likelihood of said term being a candidate for inclusion in a glossary associated with said document; presenting: said term as a candidate term for inclusion in said glossary, and said assigned result values; in response to receiving an approval to include said candidate term in the glossary, storing said candidate term to said glossary with a record of one or more of said result values assigned by said set of one or more rules; in response to receiving a denial to include said candidate term in said glossary, discarding said candidate term; and providing an indication of whether said term was subsequently included in said glossary. 2. The method according to claim 1 , further comprising: comparing said probability value for said term with a threshold probability value, wherein the candidate term is only presented responsive to said probability value exceeding said threshold probability value for inclusion in said glossary. | 0.797701 |
15. A system comprising: first hardware of a first report designer to: create a business intelligence report element in a first business intelligence report specification, the first business intelligence report specification in a first file format; receive a selection of the business intelligence report element; and create a serialized description of the business intelligence report element in a second file format based on a business intelligence report element data model; a repository to store the serialized description; and second hardware of a second report designer to: create a second business intelligence report specification, the second business intelligence report specification in a third file format; receive an instruction to add the business intelligence report element to the second business intelligence report specification; and add the business intelligence report element to the second business intelligence report specification in the third file format based on the serialized description of the business intelligence report element. | 15. A system comprising: first hardware of a first report designer to: create a business intelligence report element in a first business intelligence report specification, the first business intelligence report specification in a first file format; receive a selection of the business intelligence report element; and create a serialized description of the business intelligence report element in a second file format based on a business intelligence report element data model; a repository to store the serialized description; and second hardware of a second report designer to: create a second business intelligence report specification, the second business intelligence report specification in a third file format; receive an instruction to add the business intelligence report element to the second business intelligence report specification; and add the business intelligence report element to the second business intelligence report specification in the third file format based on the serialized description of the business intelligence report element. 18. A system according to claim 15 , wherein addition of the business intelligence report element to the second business intelligence report specification in the third file format comprises: determination that at least one semantic object of the business intelligence report element is not available in the second business intelligence report specification; creation of a template object based on the business intelligence report element; reception of mappings from the at least one semantic object to at least one semantic object of the second business intelligence report specification; and addition of the business intelligence report element to the second business intelligence report specification based on the template object and the mappings. | 0.734688 |
1. An image learning method comprising: performing a segmentation operation on a first image having annotations to segment the first image into one or more image regions; extracting image feature vectors and text feature vectors from all the image regions to obtain an image feature matrix and a text feature matrix; projecting the image feature matrix and the text feature matrix into a sub-space so as to maximize covariance between an image feature and a text feature, thereby obtaining the projected image feature matrix and the text feature matrix; storing the projected image feature matrix and the text feature matrix; establishing first links between the image regions based on the projected image feature matrix; establishing second links between the first image and the image regions based on a result of the segmentation operation; establishing third links between the first image and the annotations based on the first image having the annotations; establishing fourth links between the annotations based on the projected text feature matrix; calculating weights of all the links; obtaining a graph showing a triangular relationship between the first image, the image regions, and the annotations based on all the links and the weights of the links corresponding to the links; and providing a storage device and a processor, and wherein the step of storing the projected image feature and text feature matrices includes the step of storing information in the storage device, and wherein the step of calculating weights includes the step of using the processor. | 1. An image learning method comprising: performing a segmentation operation on a first image having annotations to segment the first image into one or more image regions; extracting image feature vectors and text feature vectors from all the image regions to obtain an image feature matrix and a text feature matrix; projecting the image feature matrix and the text feature matrix into a sub-space so as to maximize covariance between an image feature and a text feature, thereby obtaining the projected image feature matrix and the text feature matrix; storing the projected image feature matrix and the text feature matrix; establishing first links between the image regions based on the projected image feature matrix; establishing second links between the first image and the image regions based on a result of the segmentation operation; establishing third links between the first image and the annotations based on the first image having the annotations; establishing fourth links between the annotations based on the projected text feature matrix; calculating weights of all the links; obtaining a graph showing a triangular relationship between the first image, the image regions, and the annotations based on all the links and the weights of the links corresponding to the links; and providing a storage device and a processor, and wherein the step of storing the projected image feature and text feature matrices includes the step of storing information in the storage device, and wherein the step of calculating weights includes the step of using the processor. 3. The image learning method according to claim 1 , wherein the image feature vectors of all the image regions are extracted by an algorithm based on a local binary pattern feature comprising mixed colors and pattern information. | 0.752951 |
17. A system for transforming sensory input received at a machine into actions by the machine, the system comprising: one or more sensors; memory; at least one processor; a consciousness module stored in the memory and coupled to the at least one processor, the consciousness module operative to receive a first sensory input from the one or more sensors, translate the first sensory input into a human language to create a human language stimulus, determine whether the human language stimulus requires a first action, and if the human language stimulus requires the first action, perform the first action; a sub-consciousness module stored in the memory and coupled to the at least one processor, the sub-consciousness module operative to receive a second sensory input from the one or more sensors, select a second action corresponding to the second sensory input, and perform the second action in response to the second sensory input; and a personality waveform generator operative to generate a waveform corresponding to an artificial personality, wherein the first action or the second action may be selected according to the waveform at a particular time or a particular time range associated with the first sensory input or the second sensory input. | 17. A system for transforming sensory input received at a machine into actions by the machine, the system comprising: one or more sensors; memory; at least one processor; a consciousness module stored in the memory and coupled to the at least one processor, the consciousness module operative to receive a first sensory input from the one or more sensors, translate the first sensory input into a human language to create a human language stimulus, determine whether the human language stimulus requires a first action, and if the human language stimulus requires the first action, perform the first action; a sub-consciousness module stored in the memory and coupled to the at least one processor, the sub-consciousness module operative to receive a second sensory input from the one or more sensors, select a second action corresponding to the second sensory input, and perform the second action in response to the second sensory input; and a personality waveform generator operative to generate a waveform corresponding to an artificial personality, wherein the first action or the second action may be selected according to the waveform at a particular time or a particular time range associated with the first sensory input or the second sensory input. 18. The system of claim 17 , wherein the personality waveform generator comprises a light source configured to produce a light wave, and wherein the waveform comprises the light wave. | 0.50037 |
1. A non-transitory computer readable medium storing computer-executable instructions for performing a method of processing an electronic document, the method comprising: providing a first post-design editing session of a first instance of a document, wherein the document is complete; during the post-design editing session, iteratively triggering transformation of the document, to produce a second instance of the document, via user interaction within a displayable interview pane that is superimposed over or juxtaposed with the document, the interview pane including multiple, separate user-interaction components arranged to provide variability in the strict content of the document, the user-interaction components including: a guided-fill component configured to guide users to enter text into data fields, with the entered text becoming part of the second instance of the document or triggering inclusion of additional content in the second instance of the document; a free-form text component configured to permit users to enter text in free-form in portions of the document, including permission to add free-form text as new portions of the document; and an interview component configured to prompt queries to the user, wherein answers to the queries determine at least one format parameter and at least one content parameter, and wherein the user is permitted to vary the strict content of the document via directly adding or removing text in free-form in the document while the interview pane is an active state and simultaneously displayed with the document; and controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content of the interactive document and user access regarding which, if any, of the respective displayable user-interaction components within the interview pane associated with the first instance of the document are accessible by a user. | 1. A non-transitory computer readable medium storing computer-executable instructions for performing a method of processing an electronic document, the method comprising: providing a first post-design editing session of a first instance of a document, wherein the document is complete; during the post-design editing session, iteratively triggering transformation of the document, to produce a second instance of the document, via user interaction within a displayable interview pane that is superimposed over or juxtaposed with the document, the interview pane including multiple, separate user-interaction components arranged to provide variability in the strict content of the document, the user-interaction components including: a guided-fill component configured to guide users to enter text into data fields, with the entered text becoming part of the second instance of the document or triggering inclusion of additional content in the second instance of the document; a free-form text component configured to permit users to enter text in free-form in portions of the document, including permission to add free-form text as new portions of the document; and an interview component configured to prompt queries to the user, wherein answers to the queries determine at least one format parameter and at least one content parameter, and wherein the user is permitted to vary the strict content of the document via directly adding or removing text in free-form in the document while the interview pane is an active state and simultaneously displayed with the document; and controlling, as a function of user characteristics including at least one of an identity, a title, or a role, user access to predetermined content of the interactive document and user access regarding which, if any, of the respective displayable user-interaction components within the interview pane associated with the first instance of the document are accessible by a user. 5. The computer readable medium of claim 1 , wherein providing instance data to form content of the document, the instance data comprising temporarily stored information retrieved from an asynchronous information source. | 0.69019 |
19. The method of claim 1 , comprising the additional step of: d) creating a timeline displayed with one or more neighbor stories which are each comprised in the video and which are closest in time of creation to a selected story. | 19. The method of claim 1 , comprising the additional step of: d) creating a timeline displayed with one or more neighbor stories which are each comprised in the video and which are closest in time of creation to a selected story. 20. The method of claim 19 , comprising the additional steps of: e) for each of the one or more neighbor stories, selecting a set of corresponding neighbor keyframes; and f) for each neighbor story, creating a neighbor collage comprising the neighbor keyframes. | 0.778807 |
11. Apparatus for parsing a document that includes data structures conforming to a document specification, the apparatus comprising: an interface, which is arranged to accept a set of rules defining valid data structures in terms of a regular expression comprising one or more nested references to respective referenced regular expressions; a regular expression processor, which is arranged to replace the nested references in the regular expression with the respective referenced regular expressions, so as to provide a modified regular expression that does not contain a reference to another regular expression and so as to provide a modified set of rules comprising the modified regular expression; and a parsing processor, which is arranged to parse the document using the modified regular expression that does not contain a reference to another regular expression and accordingly to the modified set of rules. | 11. Apparatus for parsing a document that includes data structures conforming to a document specification, the apparatus comprising: an interface, which is arranged to accept a set of rules defining valid data structures in terms of a regular expression comprising one or more nested references to respective referenced regular expressions; a regular expression processor, which is arranged to replace the nested references in the regular expression with the respective referenced regular expressions, so as to provide a modified regular expression that does not contain a reference to another regular expression and so as to provide a modified set of rules comprising the modified regular expression; and a parsing processor, which is arranged to parse the document using the modified regular expression that does not contain a reference to another regular expression and accordingly to the modified set of rules. 13. The apparatus according to claim 11 , wherein the document specification comprises an Extensible Markup Language (XML) specification. | 0.535433 |
1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node. | 1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node. 16. A method as recited in claim 1 , wherein each of the plurality of nodes includes a semantic processor configured to interpret the semantic command and apply the semantic command to the local version of the database. | 0.59242 |
1. A process of fingerprinting a document for an information leakage prevention system, the process comprising: generating a sequence of hash values for a document, a portion of said hash values to be selected as fingerprints for the document; adaptively determining a size of a window, wherein the size of the window varies depending on a minimum guaranteed match percentage and a size of the document; selecting for the document using said adaptively-sized window; and adding the fingerprints for the document to a fingerprint set for content being protected by the information leakage prevention system. | 1. A process of fingerprinting a document for an information leakage prevention system, the process comprising: generating a sequence of hash values for a document, a portion of said hash values to be selected as fingerprints for the document; adaptively determining a size of a window, wherein the size of the window varies depending on a minimum guaranteed match percentage and a size of the document; selecting for the document using said adaptively-sized window; and adding the fingerprints for the document to a fingerprint set for content being protected by the information leakage prevention system. 6. The process of claim 1 , said selection of fingerprints for the document using said adaptively-sized window comprises: positioning a current window over a portion of the sequence of hash values; examining hash values starting from one end of the current window and selecting a first-encountered hash value that is 0 modulo P to be a fingerprint for the current window, wherein P is a predetermined number; and if no 0 modulo P hash value is found in the current window, then forcibly selecting a hash value to be a fingerprint for the current window. | 0.5 |
16. The computer program product set forth in claim 15 , wherein the second generation subsystem includes a compare process configured to omit words from the set of keywords that are found in the set of synonyms. | 16. The computer program product set forth in claim 15 , wherein the second generation subsystem includes a compare process configured to omit words from the set of keywords that are found in the set of synonyms. 17. The computer program product set forth in claim 16 , wherein a corpus taxonomy service is applied to the set of keywords after omitting common words to the set of synonyms. | 0.777692 |
9. A computer-implemented method for tagging content, the method comprising: receiving a first identifier of a first natural language, of a session of a computer with a user; automatically displaying in the first natural language, at least a description of a piece of content accessible to the computer; at least one processor using the first identifier to retrieve from a memory, a first set of tags comprising strings of text expressed in the first natural language; wherein each tag in the first set comprises a string of text expressed in the first natural language and an identifier of said piece of content; and automatically checking if a number of the tags in the first set is greater than zero and if not then automatically using a second identifier to retrieve and display adjacent to the description in the first natural language, a second set tags comprising strings of text expressed in a second natural language different from the first natural language. | 9. A computer-implemented method for tagging content, the method comprising: receiving a first identifier of a first natural language, of a session of a computer with a user; automatically displaying in the first natural language, at least a description of a piece of content accessible to the computer; at least one processor using the first identifier to retrieve from a memory, a first set of tags comprising strings of text expressed in the first natural language; wherein each tag in the first set comprises a string of text expressed in the first natural language and an identifier of said piece of content; and automatically checking if a number of the tags in the first set is greater than zero and if not then automatically using a second identifier to retrieve and display adjacent to the description in the first natural language, a second set tags comprising strings of text expressed in a second natural language different from the first natural language. 10. The computer-implemented method of claim 9 further comprising: automatically using an identifier of said piece of content in addition to said first identifier, to select the first set of tags. | 0.824824 |
11. A non-transitory computer storage medium storing executable code, wherein the executable code configures a computing system to perform a process comprising: establishing a content presentation session, wherein individual portions of a content item are provided to each of a plurality of user devices concurrently during the content presentation session, and wherein the plurality of user devices are permitted to submit annotations concurrently during the content presentation session; receiving, from a first user device of the plurality of user devices, an annotation associated with the content item; determining a target amount of annotation content per unit of time to be distributed to individual user devices of the plurality of user devices; selecting a first subset of the plurality of user devices based at least partly on a quantity of the plurality of user devices and the target amount of annotation content per unit of time; transmitting the annotation to the first subset of the plurality of user devices; receiving moderation information regarding the annotation from at least a portion of the first subset of the plurality of user devices; determining that the moderation information satisfies a moderation criterion; and transmitting a plurality of annotations associated with the content item to a second subset of the plurality of user devices, wherein the plurality of annotations includes the annotation. | 11. A non-transitory computer storage medium storing executable code, wherein the executable code configures a computing system to perform a process comprising: establishing a content presentation session, wherein individual portions of a content item are provided to each of a plurality of user devices concurrently during the content presentation session, and wherein the plurality of user devices are permitted to submit annotations concurrently during the content presentation session; receiving, from a first user device of the plurality of user devices, an annotation associated with the content item; determining a target amount of annotation content per unit of time to be distributed to individual user devices of the plurality of user devices; selecting a first subset of the plurality of user devices based at least partly on a quantity of the plurality of user devices and the target amount of annotation content per unit of time; transmitting the annotation to the first subset of the plurality of user devices; receiving moderation information regarding the annotation from at least a portion of the first subset of the plurality of user devices; determining that the moderation information satisfies a moderation criterion; and transmitting a plurality of annotations associated with the content item to a second subset of the plurality of user devices, wherein the plurality of annotations includes the annotation. 17. The non-transitory computer storage medium of claim 11 , wherein the process further comprises transmitting the content item, the annotation, and display metadata to a user device, wherein the metadata indicates a time at which the annotation is to be displayed, and wherein the time corresponds to a relative time, within the content item, at which the annotation was created. | 0.616656 |
5. A method for the clustering of related terms into separate conversation in a text-based dataset, comprising the steps of: calculating, via a lexicon engine of a data processing module, a correlation K ij between combinations of words, wherein K ij is a coefficient between a correlation parameter C ij of lemmas i with lemmas j, over F i F j , where F i is frequency of word i and F j is frequency of word j; concatenating lemmas that have a correlation K ij above a predetermined level into an artificial word via the lexicon engine; recalculating, via the lexicon engine, a correlation K ij between combinations of words in an expanded dataset comprised of said text-based dataset and artificial words obtained by concatenation; repeating the steps above for N lemmas; and using a force directed graph to visually display, via a display in communication with the data processing module, the results obtained above into separate conversations, wherein each node in the graph has N outgoing partners, and the N co-words with the highest value of K ij above a minimum value are connected together. | 5. A method for the clustering of related terms into separate conversation in a text-based dataset, comprising the steps of: calculating, via a lexicon engine of a data processing module, a correlation K ij between combinations of words, wherein K ij is a coefficient between a correlation parameter C ij of lemmas i with lemmas j, over F i F j , where F i is frequency of word i and F j is frequency of word j; concatenating lemmas that have a correlation K ij above a predetermined level into an artificial word via the lexicon engine; recalculating, via the lexicon engine, a correlation K ij between combinations of words in an expanded dataset comprised of said text-based dataset and artificial words obtained by concatenation; repeating the steps above for N lemmas; and using a force directed graph to visually display, via a display in communication with the data processing module, the results obtained above into separate conversations, wherein each node in the graph has N outgoing partners, and the N co-words with the highest value of K ij above a minimum value are connected together. 6. A method according to claim 5 , wherein N=5. | 0.94571 |
11. The method of claim 1 , wherein the object represents one of an actor, a dancer, a marching band participant, or a combination thereof and wherein the text is one of a play, a television show, a movie, a musical, musical score, or a combination thereof, and the method further comprising: associating a sequential series of identification numbers with a sequential series of lines of the text; determining a set of one or more characters associated with at least a subset of the sequential series of lines of the text; and displaying at least one character in the set of one or more characters with at least the subset sequential series of numbers to enable a user to identify one or characters that may be played by one person. | 11. The method of claim 1 , wherein the object represents one of an actor, a dancer, a marching band participant, or a combination thereof and wherein the text is one of a play, a television show, a movie, a musical, musical score, or a combination thereof, and the method further comprising: associating a sequential series of identification numbers with a sequential series of lines of the text; determining a set of one or more characters associated with at least a subset of the sequential series of lines of the text; and displaying at least one character in the set of one or more characters with at least the subset sequential series of numbers to enable a user to identify one or characters that may be played by one person. 16. The information processing system of claim 11 , wherein the venue is one of a stage, an arena, a field, a stadium, or a combination thereof. | 0.903004 |
1. A user terminal device comprising: a display unit for displaying an output result of a web application process; a video output memory unit for storing the output result displayed on the display unit; a memory unit for storing data including an intermediate operation result according to a process of a processor unit; and the processor unit for executing processes including the web application process, parsing a provided web document created in a web description language and converting into a DOM tree data having a structure formed in a shape of a tree, creating a render tree data having a structure the same as that of the converted DOM tree data, in which non-output nodes excluding display output nodes corresponding to data that will be output on a display means are configured as void nodes, storing the render tree data in the video output memory unit, and providing the render tree data to the web application process. | 1. A user terminal device comprising: a display unit for displaying an output result of a web application process; a video output memory unit for storing the output result displayed on the display unit; a memory unit for storing data including an intermediate operation result according to a process of a processor unit; and the processor unit for executing processes including the web application process, parsing a provided web document created in a web description language and converting into a DOM tree data having a structure formed in a shape of a tree, creating a render tree data having a structure the same as that of the converted DOM tree data, in which non-output nodes excluding display output nodes corresponding to data that will be output on a display means are configured as void nodes, storing the render tree data in the video output memory unit, and providing the render tree data to the web application process. 2. The apparatus according to claim 1 , wherein the processor unit stores the DOM tree data in memory having a speed lower than that of the video output memory unit. | 0.711089 |
7. A method for increasing route accuracies, the method comprising: receiving a first GPS waypoint and a first position accuracy prediction (PAP) parameter associated with the first GPS waypoint, wherein the first PAP parameter comprises a first quality parameter set having a first weight value, a first confidence value for the first GPS waypoint, and a first error distance for the first GPS waypoint; comparing, with a computer processor, the first PAP parameter to a corpus PAP parameter associated with a corpus GPS waypoint, wherein the corpus PAP parameter comprises a second quality parameter set having a second weight value, a second confidence value for the corpus GPS waypoint, and a second error distance for the corpus GPS waypoint, wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the first GPS waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus GPS waypoint to provide a second probability distribution circle; and computationally generating a vector line between the first GPS waypoint and the corpus GPS waypoint; and determining, with the computer processor, an updated GPS waypoint along the vector line between the first GPS waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average. | 7. A method for increasing route accuracies, the method comprising: receiving a first GPS waypoint and a first position accuracy prediction (PAP) parameter associated with the first GPS waypoint, wherein the first PAP parameter comprises a first quality parameter set having a first weight value, a first confidence value for the first GPS waypoint, and a first error distance for the first GPS waypoint; comparing, with a computer processor, the first PAP parameter to a corpus PAP parameter associated with a corpus GPS waypoint, wherein the corpus PAP parameter comprises a second quality parameter set having a second weight value, a second confidence value for the corpus GPS waypoint, and a second error distance for the corpus GPS waypoint, wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the first GPS waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus GPS waypoint to provide a second probability distribution circle; and computationally generating a vector line between the first GPS waypoint and the corpus GPS waypoint; and determining, with the computer processor, an updated GPS waypoint along the vector line between the first GPS waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average. 13. The method of claim 7 , and further comprising determining, with the computer processor, whether the first GPS waypoint is within a predetermined coordinate area from the corpus GPS waypoint. | 0.623671 |
8. A system, comprising: one or more data processing apparatus; and a computer-readable storage device including instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: obtaining an image based on a document capture process performed on a rendered document; identifying a portion of the image, the portion comprising a sequence of text units; segmenting the portion of the image into a sequence of segmented sub-images, each segmented sub-image comprising a single text unit of the sequence of text units; for each segmented sub-image of the sequence of segmented sub-images: determining that one or more features of the segmented sub-image are classified as being similar to one or more corresponding features of a stored sub-image; and based on determining that one or more features of the segmented sub-image are classified as being similar to one or more corresponding features of the stored sub-image, assigning to the segmented sub-image a text unit identity that is associated with the stored sub-image; generating a representation of the portion of the image, based on the assigned text unit identities; and identifying the sequence of segmented sub-images, based on the generated representation. | 8. A system, comprising: one or more data processing apparatus; and a computer-readable storage device including instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: obtaining an image based on a document capture process performed on a rendered document; identifying a portion of the image, the portion comprising a sequence of text units; segmenting the portion of the image into a sequence of segmented sub-images, each segmented sub-image comprising a single text unit of the sequence of text units; for each segmented sub-image of the sequence of segmented sub-images: determining that one or more features of the segmented sub-image are classified as being similar to one or more corresponding features of a stored sub-image; and based on determining that one or more features of the segmented sub-image are classified as being similar to one or more corresponding features of the stored sub-image, assigning to the segmented sub-image a text unit identity that is associated with the stored sub-image; generating a representation of the portion of the image, based on the assigned text unit identities; and identifying the sequence of segmented sub-images, based on the generated representation. 14. The system of claim 8 , wherein segmenting a portion of the image into multiple segmented sub-images comprises identifying space between the sub-images. | 0.720896 |
14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema. | 14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema. 17. The system of claim 14 , wherein the annotation data further includes at least one of: a pre-defined notation, a user-provided text, a user-defined attribute, and at least one reference to at least one of: an element in the document, an element in an other document, a URL, and an other file. | 0.893701 |
17. A non-transitory computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: partitioning speech recognizer output into a plurality of independent clauses; and for an independent clause in the plurality of independent clauses: identifying an object; and recursively generating, via a processor, for each sub-independent clause within the independent clause, a semantic representation using the object. | 17. A non-transitory computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: partitioning speech recognizer output into a plurality of independent clauses; and for an independent clause in the plurality of independent clauses: identifying an object; and recursively generating, via a processor, for each sub-independent clause within the independent clause, a semantic representation using the object. 18. The non-transitory computer-readable storage device of claim 17 , wherein the semantic representation is used by a dialog manager in a spoken dialog system to determine a response to a user input. | 0.582536 |
1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects. | 1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects. 6. The method of claim 1 , wherein at least one of the plurality of manual test cases is imported from existing manual test cases. | 0.524526 |
1. A method for assisting a user in efficiently navigating an audible user interface at a portable computing device arranged to store a plurality of media items, the method comprising: (a) displaying a menu having a list of navigation icons each of which corresponds to a navigation command for assisting the user in navigating the plurality of media items; (b) navigating the plurality of menu items by receiving a user touch event on one of the navigation icons; (c) in response to (b), playing an audibilized navigation command associated with the navigation icon on which the user touch event is received, wherein the playing is performed only during the touch event, wherein if the user decides not to select the associated navigation icon, then the user terminates the touch event prior to the completion of the playing of the audibilized navigation command; and (d) if the user decides to select the navigation icon associated with the audibilized navigation command, then receiving a selection user input event at the navigated to navigation icon that causes the portable computing device to execute the navigation command otherwise, returning to (b). | 1. A method for assisting a user in efficiently navigating an audible user interface at a portable computing device arranged to store a plurality of media items, the method comprising: (a) displaying a menu having a list of navigation icons each of which corresponds to a navigation command for assisting the user in navigating the plurality of media items; (b) navigating the plurality of menu items by receiving a user touch event on one of the navigation icons; (c) in response to (b), playing an audibilized navigation command associated with the navigation icon on which the user touch event is received, wherein the playing is performed only during the touch event, wherein if the user decides not to select the associated navigation icon, then the user terminates the touch event prior to the completion of the playing of the audibilized navigation command; and (d) if the user decides to select the navigation icon associated with the audibilized navigation command, then receiving a selection user input event at the navigated to navigation icon that causes the portable computing device to execute the navigation command otherwise, returning to (b). 8. The method of claim 1 , wherein the audio prompt for each menu item is generated via text-to-speech processing using a voice synthesized from a limited number of key words recorded by a voice talent. | 0.671726 |
11. The system of claim 10 , wherein the operations further comprise: receiving a query image; determining one or more visual words for the query image; determining that the collection of near-duplicate images has at least a first threshold number of visual words in common with the query image; and computing a score for one or more images in the collection of near-duplicate images. | 11. The system of claim 10 , wherein the operations further comprise: receiving a query image; determining one or more visual words for the query image; determining that the collection of near-duplicate images has at least a first threshold number of visual words in common with the query image; and computing a score for one or more images in the collection of near-duplicate images. 15. The system of claim 11 , wherein computing a score comprises computing a first score for each matching visual word between the query image and the collection of near-duplicate images based on a geometric mapping between visual words of the query image and visual words of the collection of near-duplicate images. | 0.831182 |
7. A method comprising: generating one or more entries in a directory for an application to be executed by a processor, and storing the one or more entries in a set of one or more registers, the one or more entries including one or more attributes for the management of the application, the one or more entries including an entry containing an identity of a host that is running the application; receiving a request at a server interface of a startup and control framework, the request being received from a program object of a first client of a plurality of clients, the received request asking to connect the program object of the first client to the start up and control framework to manage the application, the plurality of clients including the first client running on a first computer platform and a second client running on a second computer platform, the second computer platform being different than the first computer platform, the server interface being compatible with both the first client and the second client; providing information to the requesting client regarding the application via the set of one or more registers, the information being based on the one or more entries in the directory, the information including information regarding one or more attributes of the application; and managing the application under control of the program object of the first client via the startup and control framework utilizing the information provided via the set of one or more registers. | 7. A method comprising: generating one or more entries in a directory for an application to be executed by a processor, and storing the one or more entries in a set of one or more registers, the one or more entries including one or more attributes for the management of the application, the one or more entries including an entry containing an identity of a host that is running the application; receiving a request at a server interface of a startup and control framework, the request being received from a program object of a first client of a plurality of clients, the received request asking to connect the program object of the first client to the start up and control framework to manage the application, the plurality of clients including the first client running on a first computer platform and a second client running on a second computer platform, the second computer platform being different than the first computer platform, the server interface being compatible with both the first client and the second client; providing information to the requesting client regarding the application via the set of one or more registers, the information being based on the one or more entries in the directory, the information including information regarding one or more attributes of the application; and managing the application under control of the program object of the first client via the startup and control framework utilizing the information provided via the set of one or more registers. 8. The method of claim 7 , wherein the directory comprises an LDAP (Lightweight Directory Access Protocol) directory. | 0.595405 |
6. The system of claim 5 , wherein: the context information regarding a function of the current page comprises a visual representation of the plurality of functional options of the current page. | 6. The system of claim 5 , wherein: the context information regarding a function of the current page comprises a visual representation of the plurality of functional options of the current page. 7. The system of claim 6 , wherein the contextual breadcrumbs further comprise context information regarding a function of the second different page. | 0.953939 |
9. A computer-implemented method comprising: receiving text from a user; submitting the text as a query to a remote social networking system; and receiving, from the remote social networking system, a combined result set comprising objects matching the query, the combined result set comprising objects obtained from a plurality of search algorithms performed by the social networking system; wherein at least a plurality of the objects of the combined result set are ordered based at least in part on measures of affinities of the user for the objects, wherein an affinity of the user for an object comprises a physical distance between a geographic location associated with the user and a geographic location associated with the object. | 9. A computer-implemented method comprising: receiving text from a user; submitting the text as a query to a remote social networking system; and receiving, from the remote social networking system, a combined result set comprising objects matching the query, the combined result set comprising objects obtained from a plurality of search algorithms performed by the social networking system; wherein at least a plurality of the objects of the combined result set are ordered based at least in part on measures of affinities of the user for the objects, wherein an affinity of the user for an object comprises a physical distance between a geographic location associated with the user and a geographic location associated with the object. 12. The computer-implemented method of claim 9 , wherein the combined result set comprises a first object having a first type and a second object having a second type different from the first type. | 0.827526 |
8. An apparatus for searching in an encrypted database, comprising: a memory; and a processor operatively coupled to the memory and configured to: formulate a search as a conjunct of two or more atomic search queries; select one of the conjuncts as a primary atomic search query so as to generate search capabilities for a secondary atomic search query using the primary atomic search query and the secondary atomic search query; wherein the encrypted database comprises a first data structure associated with the primary atomic search query and a second data structure associated with the secondary atomic search query; wherein the first data structure and the second data structure are generated from a raw database comprising a plurality of records, and wherein each record of the plurality of records comprises a corresponding record index value and a plurality of attribute values; wherein the first data structure is generated from the raw database by: computing a first entry for each attribute value of the plurality of attribute values; wherein the first entry comprises an encrypted tuple list and a search tag, the search tag being obtained by applying a pseudorandom function to the attribute value of the first entry; wherein the encrypted tuple list comprises a plurality of tuple list values obtained based on a randomized index value the randomized index value being obtained by applying a random permutation to the record index value; and wherein the plurality of tuple list values comprises a first tuple value obtained by encrypted the randomized index value with a key; and wherein the plurality of tuple list values further comprises a second tuple value obtained by: applying a first pseudorandom function to the randomized index value to create a first intermediate tuple value, wherein the first pseudorandom function takes a first key; applying a second pseudorandom function to the attribute value and a current count associated with the attribute value to create a second intermediate tuple value, wherein the second pseudorandom function takes a second key; and dividing the first intermediate tuple value by the second intermediate tuple value. | 8. An apparatus for searching in an encrypted database, comprising: a memory; and a processor operatively coupled to the memory and configured to: formulate a search as a conjunct of two or more atomic search queries; select one of the conjuncts as a primary atomic search query so as to generate search capabilities for a secondary atomic search query using the primary atomic search query and the secondary atomic search query; wherein the encrypted database comprises a first data structure associated with the primary atomic search query and a second data structure associated with the secondary atomic search query; wherein the first data structure and the second data structure are generated from a raw database comprising a plurality of records, and wherein each record of the plurality of records comprises a corresponding record index value and a plurality of attribute values; wherein the first data structure is generated from the raw database by: computing a first entry for each attribute value of the plurality of attribute values; wherein the first entry comprises an encrypted tuple list and a search tag, the search tag being obtained by applying a pseudorandom function to the attribute value of the first entry; wherein the encrypted tuple list comprises a plurality of tuple list values obtained based on a randomized index value the randomized index value being obtained by applying a random permutation to the record index value; and wherein the plurality of tuple list values comprises a first tuple value obtained by encrypted the randomized index value with a key; and wherein the plurality of tuple list values further comprises a second tuple value obtained by: applying a first pseudorandom function to the randomized index value to create a first intermediate tuple value, wherein the first pseudorandom function takes a first key; applying a second pseudorandom function to the attribute value and a current count associated with the attribute value to create a second intermediate tuple value, wherein the second pseudorandom function takes a second key; and dividing the first intermediate tuple value by the second intermediate tuple value. 11. The apparatus of claim 8 , wherein the generation of the search capabilities for the secondary atomic search query comprises a use of a cryptographic hash function. | 0.698214 |
24. An article of manufacture for detecting a spelling error in one or more documents, comprising a tangible machine readable recordable medium containing one or more programs which when executed implement the steps of: obtaining a maximum edit distance at which a word, w, is to be considered a possible misspelling of another word, w′; determining if at least one given word in said one or more documents satisfies a predefined misspelling criteria, wherein said predefined misspelling criteria comprises said at least one given word having a frequency below a predefined low threshold and said at least one given word being within the obtained maximum edit distance of one or more other words in said one or more documents having a frequency above a predefined high threshold; identifying a given word as a potentially misspelled word if said given word satisfies said predefined misspelling criteria; maintaining a lexicon such that said lexicon will include said given word if said given word does not satisfy said predefined misspelling criteria and will exclude said given word if said given word satisfies said predefined misspelling criteria. | 24. An article of manufacture for detecting a spelling error in one or more documents, comprising a tangible machine readable recordable medium containing one or more programs which when executed implement the steps of: obtaining a maximum edit distance at which a word, w, is to be considered a possible misspelling of another word, w′; determining if at least one given word in said one or more documents satisfies a predefined misspelling criteria, wherein said predefined misspelling criteria comprises said at least one given word having a frequency below a predefined low threshold and said at least one given word being within the obtained maximum edit distance of one or more other words in said one or more documents having a frequency above a predefined high threshold; identifying a given word as a potentially misspelled word if said given word satisfies said predefined misspelling criteria; maintaining a lexicon such that said lexicon will include said given word if said given word does not satisfy said predefined misspelling criteria and will exclude said given word if said given word satisfies said predefined misspelling criteria. 25. The article of manufacture of claim 24 , wherein said maximum edit distance is a function of a length of the at least one given word. | 0.574519 |
123. The machine system of claim 86 wherein the user monitoring subsystem is configured to store recent ones of the report records. | 123. The machine system of claim 86 wherein the user monitoring subsystem is configured to store recent ones of the report records. 124. The machine system of claim 123 wherein the user monitoring subsystem is configured to automatically sort the stored recent ones of the report records. | 0.984253 |
1. A method of optimizing a web page for a search engine, the method comprising: generating an event log comprising one or more events representing one or more initiatives affecting an organic search ranking of the web page for a search query performed in the search engine; generating at least one data graph of historical search rank data including the organic search ranking of the web page for the search query over time; identifying a feature or trend in the at least one data graph; automatically correlating, using a processor, the event data with the feature or trend identified in the at least one data graph to automatically identify the one or more events causing the feature or trend in the at least one data graph; determining, using the processor, a recommended modification to at least one parameter of a web document associated with the web page, the recommended modification to improve the organic search ranking of the web page, the determination made based on the correlation; and prompting, in a user interface, the recommended modification. | 1. A method of optimizing a web page for a search engine, the method comprising: generating an event log comprising one or more events representing one or more initiatives affecting an organic search ranking of the web page for a search query performed in the search engine; generating at least one data graph of historical search rank data including the organic search ranking of the web page for the search query over time; identifying a feature or trend in the at least one data graph; automatically correlating, using a processor, the event data with the feature or trend identified in the at least one data graph to automatically identify the one or more events causing the feature or trend in the at least one data graph; determining, using the processor, a recommended modification to at least one parameter of a web document associated with the web page, the recommended modification to improve the organic search ranking of the web page, the determination made based on the correlation; and prompting, in a user interface, the recommended modification. 9. The method of claim 1 , further comprising: compiling distribution data for the associated web document; and determining the recommended modification based on the distribution data. | 0.580545 |
13. The computer readable non-transitory memory of claim 9 wherein the assessment score further comprises a credit worthiness score which is determined comprising a profile criteria score, a lending history score, the base score and the endorsement score wherein each score has an associated weighting to determine the assessment score. | 13. The computer readable non-transitory memory of claim 9 wherein the assessment score further comprises a credit worthiness score which is determined comprising a profile criteria score, a lending history score, the base score and the endorsement score wherein each score has an associated weighting to determine the assessment score. 14. The computer readable non-transitory memory of claim 13 wherein the profile criteria score further comprises a score for verified identification and a retrieved credit bureau score for the borrowing party. | 0.941176 |
28. A computer-readable storage device having embedded therein a set of instructions which, when executed by one or more processors of the computer causes the computer to execute operations comprising: configuring storage to receive and store a query from a client machine, the query comprising a user-generated key word; responsive to the query from the client machine, using an auto-complete server to process the query to generate an auto-suggestion key word in response to detecting fewer than all of letters of the user-generated key word; and using a search engine coupled to the auto-complete server and configured to use a first search argument and a second search argument for searching at least one of the one or more files, using the user-generated key word and the auto-suggestion key word to find the at least one picture, wherein the auto-suggestion key word is used automatically and without response to a new search query, the search engine searches one of the one or more files using the user-generated key word as a search argument and, responsive to the at least one picture being found, transmits the at least one picture, and responsive to the at least one picture not being found, automatically searches, without response to a new search query from the client machine, the one of the one or more files using the auto-suggestion key word as a search argument. | 28. A computer-readable storage device having embedded therein a set of instructions which, when executed by one or more processors of the computer causes the computer to execute operations comprising: configuring storage to receive and store a query from a client machine, the query comprising a user-generated key word; responsive to the query from the client machine, using an auto-complete server to process the query to generate an auto-suggestion key word in response to detecting fewer than all of letters of the user-generated key word; and using a search engine coupled to the auto-complete server and configured to use a first search argument and a second search argument for searching at least one of the one or more files, using the user-generated key word and the auto-suggestion key word to find the at least one picture, wherein the auto-suggestion key word is used automatically and without response to a new search query, the search engine searches one of the one or more files using the user-generated key word as a search argument and, responsive to the at least one picture being found, transmits the at least one picture, and responsive to the at least one picture not being found, automatically searches, without response to a new search query from the client machine, the one of the one or more files using the auto-suggestion key word as a search argument. 46. The computer-readable storage device of claim 28 wherein the at least one picture is configured to be transmitted as a selectable picture that includes a link to a web page identifying aspects of an outlet store. | 0.555718 |
11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. | 11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. 14. The system of claim 11 , wherein the click tracker identifies traffic data comprising one or more of a browser type, a referring web site, a source internet protocol address and a destination internet protocol address. | 0.649371 |
11. The system of claim 10 , wherein the term assigned to the second leaf node is a first term and wherein the instructions further include instructions that, when executed, cause the first leaf node to: receive an updated term-sharded posting list portion for a second term from a third leaf node, the second term being assigned to the first leaf node; receive an updated term-sharded posting list portion for the second term from a fourth leaf node; merge the updated term-sharded posting list portion from the third leaf node with the updated term-sharded posting list portion from the fourth leaf node to generate a new term-sharded posting list for the second term; and and use the new term-sharded posting list for the second term in responding to queries. | 11. The system of claim 10 , wherein the term assigned to the second leaf node is a first term and wherein the instructions further include instructions that, when executed, cause the first leaf node to: receive an updated term-sharded posting list portion for a second term from a third leaf node, the second term being assigned to the first leaf node; receive an updated term-sharded posting list portion for the second term from a fourth leaf node; merge the updated term-sharded posting list portion from the third leaf node with the updated term-sharded posting list portion from the fourth leaf node to generate a new term-sharded posting list for the second term; and and use the new term-sharded posting list for the second term in responding to queries. 18. The system of claim 11 , wherein the instructions further include instructions that, when executed, cause the first leaf node to perform the merging when it is determined that a current version of the term-sharded posting list for the second term is stored in slower access memory. | 0.791136 |
1. A computer-based method of retrieving Web document information from a computer network, comprising: retrieving a Web document from a computer network using a first protocol included in a primary document address specification; obtaining data from the Web document; determining whether the primary document address specification has a corresponding secondary document address specification; and if the primary document address specification has a corresponding secondary document address specification, retrieving supplementary data from the computer network pertaining to the Web document using a second protocol included in the secondary document address specification. | 1. A computer-based method of retrieving Web document information from a computer network, comprising: retrieving a Web document from a computer network using a first protocol included in a primary document address specification; obtaining data from the Web document; determining whether the primary document address specification has a corresponding secondary document address specification; and if the primary document address specification has a corresponding secondary document address specification, retrieving supplementary data from the computer network pertaining to the Web document using a second protocol included in the secondary document address specification. 13. The method of claim 1, wherein the secondary document address specification is automatically built by replacing a secondary address prefix for a primary address prefix in the primary document address specification. | 0.773654 |
15. A search system comprising: a search engine, wherein the search engine receives a signal including a search query; a plurality of databases, wherein each database stores a set of ranked search results and a ranking scheme used to rank the set of search results, wherein each ranking scheme indicates a different methodology for ranking the set of search results and the ranking scheme is different for each database included in the plurality; and a server to analyze the search query to identify a plurality of properties of the search query, identify the a separate ranking scheme for ranking a set of search results stored in a plurality of databases resident in the server, wherein the set of search results and the ranking scheme is different for each database, determine a relevance factor of each scheme based a relevance of each ranking scheme to each property of the search query rank the set search results stored in each database of the plurality of databases using a ranking scheme identified for each respective database, identify, by the server, a plurality of search results that match one or more properties of the search query such that each search result is identified from a different stored set of ranked search results, sort the plurality of search results according to the relevance factor of a scheme associated with each respective search result included in the plurality of search results, and generate a search results list using the sorted plurality of search results. | 15. A search system comprising: a search engine, wherein the search engine receives a signal including a search query; a plurality of databases, wherein each database stores a set of ranked search results and a ranking scheme used to rank the set of search results, wherein each ranking scheme indicates a different methodology for ranking the set of search results and the ranking scheme is different for each database included in the plurality; and a server to analyze the search query to identify a plurality of properties of the search query, identify the a separate ranking scheme for ranking a set of search results stored in a plurality of databases resident in the server, wherein the set of search results and the ranking scheme is different for each database, determine a relevance factor of each scheme based a relevance of each ranking scheme to each property of the search query rank the set search results stored in each database of the plurality of databases using a ranking scheme identified for each respective database, identify, by the server, a plurality of search results that match one or more properties of the search query such that each search result is identified from a different stored set of ranked search results, sort the plurality of search results according to the relevance factor of a scheme associated with each respective search result included in the plurality of search results, and generate a search results list using the sorted plurality of search results. 18. The search system of claim 15 , wherein the server divides each of the search results from each database into a plurality of zones, combines each of the search results from each database in each zone, and combines the search results from each zone. | 0.617857 |
1. A method for providing due diligence of software using a license description syntax, wherein the license description syntax includes a plurality of attributes for describing software licenses, the method comprising: creating a license database that includes a plurality of entries, wherein each of the plurality of entries in the license database uniquely describes permissions and obligations associated with one version of an authoritative text for a respective software license; associating each of the plurality of entries in the license database with one or more of the plurality of attributes of the license description syntax, wherein the one or more attributes associated with at least one of the plurality of entries is arranged to uniquely describe said permissions and obligations of said version of authoritative text; combining the one or more of the plurality of entries by Boolean operators to form a complex entry for describing an applicable software license, wherein the complex entry comprises the one or more attributes of one or more of the plurality of entries and the relationships among the entries indicated b the Boolean operators; analyzing the software under due diligence to identify one or more software licenses as being applicable to said software, said analyzing comprising comparing a fingerprint of the software under due diligence with other fingerprints of other known software having known applicable software licenses to determine a match between the software under due diligence and the other known software; and identifying, upon determining a match, one or more entries in said license database that describe said known applicable software licenses. | 1. A method for providing due diligence of software using a license description syntax, wherein the license description syntax includes a plurality of attributes for describing software licenses, the method comprising: creating a license database that includes a plurality of entries, wherein each of the plurality of entries in the license database uniquely describes permissions and obligations associated with one version of an authoritative text for a respective software license; associating each of the plurality of entries in the license database with one or more of the plurality of attributes of the license description syntax, wherein the one or more attributes associated with at least one of the plurality of entries is arranged to uniquely describe said permissions and obligations of said version of authoritative text; combining the one or more of the plurality of entries by Boolean operators to form a complex entry for describing an applicable software license, wherein the complex entry comprises the one or more attributes of one or more of the plurality of entries and the relationships among the entries indicated b the Boolean operators; analyzing the software under due diligence to identify one or more software licenses as being applicable to said software, said analyzing comprising comparing a fingerprint of the software under due diligence with other fingerprints of other known software having known applicable software licenses to determine a match between the software under due diligence and the other known software; and identifying, upon determining a match, one or more entries in said license database that describe said known applicable software licenses. 12. The method of claim 1 , wherein the complex license operators include an equivalents operator for representing alternative expressions for an entry in the license database, wherein the alternative expressions are defined in terms of other entries in the license database. | 0.623851 |
8. A system of determining a layout of a structural document, the system comprising: a first computing device; and a computer-readable storage medium in communication with the first computing device, the computer-readable storage medium comprising one or more programming instructions that, when executed, cause the first computing device to: receive a plurality of images from a second computing device, determine a design associated with a structural document, the structural document comprising one or more facets, each facet representing one or more exterior surfaces of the structural document, determine a number of facets associated with the structural document based on the determined design, determine an image area associated with the structural document based on the received plurality of images and the number of facets; determine an image aspect ratio associated with each of the plurality of received images, determine a layout associated with the structural document based on the determined image area by: determining one or more areas of each facet in the number of facets, for each area of each facet in the number of facets: determine an area aspect ratio associated with each of the one or more areas, a received image to the area, and determining a fit ratio comprising a ratio of the determined aspect ratio associated with the area and the determined aspect ratio associated with the image assigned to the area, evaluate the layout by: for each facet in the number of facets, determine an average fit ratio of aspect ratios associated with the facet, and determine whether the average fit ratio of aspect ratios exceeds a threshold value, when the average fit ratio of aspect ratios exceeds a threshold value for one or more of the facets in the number of facets, determine a new layout associated with the structural document and evaluating the new layout, and when the average fit ratio of aspect ratios for all facets associated with the evaluated layout does not exceed the threshold value, cause a graphical representation of the structural document to be displayed at the second computing device, wherein each received image is displayed on its assigned area on the graphical representation. | 8. A system of determining a layout of a structural document, the system comprising: a first computing device; and a computer-readable storage medium in communication with the first computing device, the computer-readable storage medium comprising one or more programming instructions that, when executed, cause the first computing device to: receive a plurality of images from a second computing device, determine a design associated with a structural document, the structural document comprising one or more facets, each facet representing one or more exterior surfaces of the structural document, determine a number of facets associated with the structural document based on the determined design, determine an image area associated with the structural document based on the received plurality of images and the number of facets; determine an image aspect ratio associated with each of the plurality of received images, determine a layout associated with the structural document based on the determined image area by: determining one or more areas of each facet in the number of facets, for each area of each facet in the number of facets: determine an area aspect ratio associated with each of the one or more areas, a received image to the area, and determining a fit ratio comprising a ratio of the determined aspect ratio associated with the area and the determined aspect ratio associated with the image assigned to the area, evaluate the layout by: for each facet in the number of facets, determine an average fit ratio of aspect ratios associated with the facet, and determine whether the average fit ratio of aspect ratios exceeds a threshold value, when the average fit ratio of aspect ratios exceeds a threshold value for one or more of the facets in the number of facets, determine a new layout associated with the structural document and evaluating the new layout, and when the average fit ratio of aspect ratios for all facets associated with the evaluated layout does not exceed the threshold value, cause a graphical representation of the structural document to be displayed at the second computing device, wherein each received image is displayed on its assigned area on the graphical representation. 11. The system of claim 8 , wherein the one or more programming instructions that, when executed, cause the computing device to determine the layout associated with the structural document based on the determined image area further comprises one or more programming instructions that, when executed, cause the computing device to: generate an image list, wherein the image list comprises the received images arranged in an order based on associated aspect ratios, generate an area list, wherein the area list comprises the areas arranged in an order based on associated aspect ratios, assign a first image in the image list to a first area in the area list, assign a next image in the image list to a next area in the area list, and repeat the assigning a next image until all of the images in the image list are assigned to an area in the area list. | 0.530384 |
28. The method of claim 24 , further comprising effecting a disposition of the edited multimedia in dependence upon the script. | 28. The method of claim 24 , further comprising effecting a disposition of the edited multimedia in dependence upon the script. 31. The method of claim 28 , wherein said disposition comprises associating said manipulated multimedia item with an instant message. | 0.949013 |
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