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8,762,385 | 3 | 4 | 3. The method for implementing email recipient templates as in claim 2 , further comprising storing an inbound record for each to/cc/bcc combination used by each email user in incoming email messages. | 3. The method for implementing email recipient templates as in claim 2 , further comprising storing an inbound record for each to/cc/bcc combination used by each email user in incoming email messages. 4. The method for implementing email recipient templates as in claim 3 , further comprising generating a unique template for each of the outbound and inbound records. | 0.950975 |
9,959,341 | 15 | 19 | 15. At least one computer-readable medium having encoded thereon instructions which, when executed by at least one processor, cause the at least one processor to perform a method comprising acts of: processing an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a valency frame having a plurality of valency frame components; the plurality of valency frame components correspond, respectively, to a plurality of semantic entities identified from the at least one input text; and the plurality of semantic entities occur in a common context within the at least one input text; and using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data. | 15. At least one computer-readable medium having encoded thereon instructions which, when executed by at least one processor, cause the at least one processor to perform a method comprising acts of: processing an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a valency frame having a plurality of valency frame components; the plurality of valency frame components correspond, respectively, to a plurality of semantic entities identified from the at least one input text; and the plurality of semantic entities occur in a common context within the at least one input text; and using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data. 19. The at least one computer-readable medium of claim 15 , wherein the at least one semantic pattern is in a lexicon of semantic patterns, and wherein the method further comprises an act of: processing the input text to identify, from the lexicon of semantic patterns, one or more semantic patterns that match the input text. | 0.524781 |
9,323,456 | 3 | 6 | 3. A multi-character continuous handwriting input method, comprising the following steps: writing a character on a touch unit; after writing an i th character, writing an (i+1) th character on the i th character in an overlapping manner; when a user is writing, determining whether the current stroke belongs to the i th character or the (i+1) th character; when it is determined that the user starts writing the (i+1) th character in an overlapping manner, dimming a display color of strokes of the i th character automatically, so that the user sees a clear track of a newly written character on a display screen; and continuously writing multiple characters without pauses according to the above manner, wherein when an (i+2) th character is written, the i th character disappears automatically from the display screen, and the color of the (i+1) th character is dimmed automatically, or colors of the (i+1) th character and the (i+2) th character are made to be different. | 3. A multi-character continuous handwriting input method, comprising the following steps: writing a character on a touch unit; after writing an i th character, writing an (i+1) th character on the i th character in an overlapping manner; when a user is writing, determining whether the current stroke belongs to the i th character or the (i+1) th character; when it is determined that the user starts writing the (i+1) th character in an overlapping manner, dimming a display color of strokes of the i th character automatically, so that the user sees a clear track of a newly written character on a display screen; and continuously writing multiple characters without pauses according to the above manner, wherein when an (i+2) th character is written, the i th character disappears automatically from the display screen, and the color of the (i+1) th character is dimmed automatically, or colors of the (i+1) th character and the (i+2) th character are made to be different. 6. The multi-character continuous handwriting input method as in claim 3 , wherein the multi-character continuous handwriting input method is a left-to-right handwriting input method that inputs characters from the left-hand side to the right-hand side. | 0.94942 |
9,643,722 | 1 | 2 | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. 2. The system of claim 1 wherein the aerial drone device includes: a storage compartment configured for storing a net, paint, pepper spray or a tracking device; and ii. a shielding component configured for protecting the aerial drone device, wherein the shielding component includes one or more extendible wings. | 0.6 |
8,302,010 | 1 | 8 | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises reordering the transcript text by moving a selected span of the transcript text from a first position within the transcript text to a second position within the transcript text, wherein the association of the tinting information with each of the plurality of words within the transcript is preserved during the editing, and wherein the editing of the augmented transcript does not involve playback of the time-based media; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a reordered temporal sequence that corresponds to the reordered transcript text of the edited augmented transcript. | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises reordering the transcript text by moving a selected span of the transcript text from a first position within the transcript text to a second position within the transcript text, wherein the association of the tinting information with each of the plurality of words within the transcript is preserved during the editing, and wherein the editing of the augmented transcript does not involve playback of the time-based media; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a reordered temporal sequence that corresponds to the reordered transcript text of the edited augmented transcript. 8. The method of claim 1 , wherein generating the edited version of the time-based media program includes automatic linking by the media editing system to time-based media corresponding to the edited time-based media program. | 0.816775 |
6,055,515 | 1 | 9 | 1. An integrated computer browsing system, comprising: a computer controlled user interface display, processing means for presenting data from a complex lattice data structure in a tree data structure, browsing means for navigating said complex lattice data structure through said tree data structure by means of multi-navigation paths, and display processor means for facilitating navigation without expanding said tree by providing navigation information as displayed categories of information located beyond currently displayed information. | 1. An integrated computer browsing system, comprising: a computer controlled user interface display, processing means for presenting data from a complex lattice data structure in a tree data structure, browsing means for navigating said complex lattice data structure through said tree data structure by means of multi-navigation paths, and display processor means for facilitating navigation without expanding said tree by providing navigation information as displayed categories of information located beyond currently displayed information. 9. The system recited in claim 1 further comprising: means for building, maintaining, and using said multi-inheritance taxonomy, means for providing multiple parents in said taxonomy, and means for storing the nodes of each of said multiple parents wherein each node is stored at a single location, each of said parents being displayed in said taxonomy a plurality of times. | 0.785796 |
9,910,848 | 1 | 10 | 1. A method, in a data processing system having a processor and a memory storing instructions for implementing a natural language processing engine, a store of semantic types, and a store of units, conversions among units, and variants of unit names, for generating semantically equivalent variants of a natural language term, wherein the data processing system configured with the natural language processing engine comprises a question answering system, the method comprising: receiving, by the natural language processing engine, an input term for variant analysis, wherein the input term is an answer to a question forming a question and answer pair for an answer key of the question answering system; identifying, by the natural language processing engine executing on the data processing system, a semantic type of the input term based on the store of semantic types; extracting, by the natural language processing engine, a quantity and a unit from the input term based on the store of units, conversions among units, and variants of unit names; populating, by the natural language processing engine, type-specific templates at a level of specificity based on the input term based on the identified semantic type of the input term and the extracted quantity and unit to form a set of semantically equivalent variants of the input term; generating, by the natural language processing engine, a question and answer pair using the question and each semantically equivalent variant within the set of semantically equivalent variants of the input term to form a supplemented answer key; training, by the natural language processing engine, a question answering machine learning model for the question answering system using the supplemented answer key; and configuring the question answering system to operate in accordance with the question answering machine learning model. | 1. A method, in a data processing system having a processor and a memory storing instructions for implementing a natural language processing engine, a store of semantic types, and a store of units, conversions among units, and variants of unit names, for generating semantically equivalent variants of a natural language term, wherein the data processing system configured with the natural language processing engine comprises a question answering system, the method comprising: receiving, by the natural language processing engine, an input term for variant analysis, wherein the input term is an answer to a question forming a question and answer pair for an answer key of the question answering system; identifying, by the natural language processing engine executing on the data processing system, a semantic type of the input term based on the store of semantic types; extracting, by the natural language processing engine, a quantity and a unit from the input term based on the store of units, conversions among units, and variants of unit names; populating, by the natural language processing engine, type-specific templates at a level of specificity based on the input term based on the identified semantic type of the input term and the extracted quantity and unit to form a set of semantically equivalent variants of the input term; generating, by the natural language processing engine, a question and answer pair using the question and each semantically equivalent variant within the set of semantically equivalent variants of the input term to form a supplemented answer key; training, by the natural language processing engine, a question answering machine learning model for the question answering system using the supplemented answer key; and configuring the question answering system to operate in accordance with the question answering machine learning model. 10. The method of claim 1 , further comprising: generating, by the natural language processing engine, a user interface presenting the set of semantically equivalent variants of the input term; and receiving, by the natural language processing engine, user input modifying the set of semantically equivalent variants of the input term via the user interface. | 0.501393 |
7,685,155 | 1 | 3 | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. 3. The method of claim 1 , wherein the schema is an XML schema. | 0.888693 |
10,026,394 | 1 | 2 | 1. A system comprising: one or more processors; and one or more computer-readable media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: receiving a first audio signal that represents, at least in part, first speech; analyzing the first audio signal to generate first speech-recognition results; identifying a first intent and a second intent associated with the first speech based at least in part on the first speech-recognition results, wherein the first intent and the second intent are associated with a first domain; identifying a third intent associated with the first speech based at least in part on the first speech-recognition results, wherein the third intent is associated with a second domain; sending a second audio signal that represents a first question associated with the first domain and the second domain; receiving a third audio signal that represents, at least in part, second speech; analyzing the third audio signal to generate second speech-recognition results; selecting the first domain based at least in part on the second speech-recognition results; sending a fourth audio signal that represents a second question associated with at least the first intent and the second intent; receiving a fifth audio signal that represents, at least in part, third speech; analyzing the fifth audio signal to generate third speech-recognition results; and selecting the first intent based at least in part on the third speech-recognition results. | 1. A system comprising: one or more processors; and one or more computer-readable media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: receiving a first audio signal that represents, at least in part, first speech; analyzing the first audio signal to generate first speech-recognition results; identifying a first intent and a second intent associated with the first speech based at least in part on the first speech-recognition results, wherein the first intent and the second intent are associated with a first domain; identifying a third intent associated with the first speech based at least in part on the first speech-recognition results, wherein the third intent is associated with a second domain; sending a second audio signal that represents a first question associated with the first domain and the second domain; receiving a third audio signal that represents, at least in part, second speech; analyzing the third audio signal to generate second speech-recognition results; selecting the first domain based at least in part on the second speech-recognition results; sending a fourth audio signal that represents a second question associated with at least the first intent and the second intent; receiving a fifth audio signal that represents, at least in part, third speech; analyzing the fifth audio signal to generate third speech-recognition results; and selecting the first intent based at least in part on the third speech-recognition results. 2. A system as recited in claim 1 , the acts further comprising: identifying a value of a field of the first intent based at least in part on the third speech-recognition results; and associating the value with the field of the first intent. | 0.821217 |
9,666,096 | 1 | 15 | 1. A spelling totem, comprising: an elongated, generally rectangular box-shaped member having a top end, a bottom end, a first side surface, a second side surface, a third side surface and a fourth side surface; a first letter language family that is disposed along the first side surface; a second letter language family that is disposed along the second side surface; a third letter language family that is disposed along the third side surface; and a fourth letter language family that is disposed along the fourth side surface, wherein the rectangular member includes a plurality of horizontal ridges that extend across each of the first, second, third and fourth side surfaces, said ridges functioning to create the appearance of a series of vertically aligned building blocks, and each of the first, second, third and fourth letter language families include a different single letter from an alphabet, and a plurality of letter implementations. | 1. A spelling totem, comprising: an elongated, generally rectangular box-shaped member having a top end, a bottom end, a first side surface, a second side surface, a third side surface and a fourth side surface; a first letter language family that is disposed along the first side surface; a second letter language family that is disposed along the second side surface; a third letter language family that is disposed along the third side surface; and a fourth letter language family that is disposed along the fourth side surface, wherein the rectangular member includes a plurality of horizontal ridges that extend across each of the first, second, third and fourth side surfaces, said ridges functioning to create the appearance of a series of vertically aligned building blocks, and each of the first, second, third and fourth letter language families include a different single letter from an alphabet, and a plurality of letter implementations. 15. The totem of claim 1 , wherein the alphabet consists of the modern English alphabet, and includes the letters A through Z. | 0.87037 |
7,734,471 | 14 | 15 | 14. An online learning dialog system comprising: means for receiving voice input; means for modeling the voice input based on a probability distribution associated with uncertainty regarding a plurality of parameters of the means for modeling the voice input, wherein the probability distribution is defined by an influence diagram that is configured to apply the Thompson strategy; means for selecting an action based, at upon in part, upon the probability distribution received from the means for modeling the voice input; and means for modifying the plurality of parameters of the means for modeling the voice input based upon feedback associated with the selected action, wherein the feedback comprises a lack of verbal response from a user in a threshold period of time. | 14. An online learning dialog system comprising: means for receiving voice input; means for modeling the voice input based on a probability distribution associated with uncertainty regarding a plurality of parameters of the means for modeling the voice input, wherein the probability distribution is defined by an influence diagram that is configured to apply the Thompson strategy; means for selecting an action based, at upon in part, upon the probability distribution received from the means for modeling the voice input; and means for modifying the plurality of parameters of the means for modeling the voice input based upon feedback associated with the selected action, wherein the feedback comprises a lack of verbal response from a user in a threshold period of time. 15. The system of claim 14 , wherein the means for selecting an action employs a heuristic technique to maximize long term expected utility. | 0.935065 |
7,499,910 | 1 | 18 | 1. A computer-readable program code embedded in a memory, wherein when a computer system executes the computer-readable program code embedded in the memory to perform a method for supporting query caching, the method comprising: determining a list of candidate queries from a plurality of queries that are stored in a cache in response to receiving a new query, wherein the list comprises a subset of the plurality of queries, wherein the subset is less than all of the plurality of queries, and wherein the determining comprises for each item in a select list of the new query, obtaining a set of cached queries that include the each item in the select list, for the each item in the select list of the new query without an exact match in the select list of at least one cached query, obtaining a set of cached queries using aggregate rewrite, and forming the list of candidate queries by intersecting the set of cached queries for the each item in the select list of the new query and the set of cached queries for the each item in the select list of the new query without an exact match in the select list of the at least one cached query; evaluating each of the candidate queries in the list to determine one candidate query that is a cache hit, the cache hit indicating a stored result of the one candidate query which answers the new query, wherein the evaluating is performed using a set of rules that allows for inexact matches between one or more aggregates included in the new query and one or more aggregates included in the candidate queries in the list; generating a result for the new query using the stored result for the one candidate query; and storing the result of the new query. | 1. A computer-readable program code embedded in a memory, wherein when a computer system executes the computer-readable program code embedded in the memory to perform a method for supporting query caching, the method comprising: determining a list of candidate queries from a plurality of queries that are stored in a cache in response to receiving a new query, wherein the list comprises a subset of the plurality of queries, wherein the subset is less than all of the plurality of queries, and wherein the determining comprises for each item in a select list of the new query, obtaining a set of cached queries that include the each item in the select list, for the each item in the select list of the new query without an exact match in the select list of at least one cached query, obtaining a set of cached queries using aggregate rewrite, and forming the list of candidate queries by intersecting the set of cached queries for the each item in the select list of the new query and the set of cached queries for the each item in the select list of the new query without an exact match in the select list of the at least one cached query; evaluating each of the candidate queries in the list to determine one candidate query that is a cache hit, the cache hit indicating a stored result of the one candidate query which answers the new query, wherein the evaluating is performed using a set of rules that allows for inexact matches between one or more aggregates included in the new query and one or more aggregates included in the candidate queries in the list; generating a result for the new query using the stored result for the one candidate query; and storing the result of the new query. 18. The computer-readable program code embedded in the memory of claim 1 , wherein obtaining the set of cached queries for the select list using aggregate rewrite further comprises: obtaining a set of aggregates for that select list in the new query without an exact match in the select list of the at least one cached query; and performing a union on the set of cached queries for all aggregates in the set of aggregates. | 0.501182 |
10,013,397 | 1 | 12 | 1. A computer-implemented method comprising: detecting a request on a client device to embed a preview region including content item previews corresponding to content items included in a folder within a document displayed on the client device, the document having visible document content, wherein the content item previews are synchronized with the content items included in the folder in a content management system, each content item preview including a portion of visible content of a corresponding content item displayed within the content item preview; displaying, within the preview region, a subset of content item previews; in response to receiving a vertical scrolling input, scrolling the document content, including the preview region, in a vertical direction; and in response to receiving a horizontal scrolling input, irrespective of a location of the received horizontal scrolling input: scrolling out of the preview region a number of the content item previews; and scrolling into the preview region additional content item previews without scrolling the document. | 1. A computer-implemented method comprising: detecting a request on a client device to embed a preview region including content item previews corresponding to content items included in a folder within a document displayed on the client device, the document having visible document content, wherein the content item previews are synchronized with the content items included in the folder in a content management system, each content item preview including a portion of visible content of a corresponding content item displayed within the content item preview; displaying, within the preview region, a subset of content item previews; in response to receiving a vertical scrolling input, scrolling the document content, including the preview region, in a vertical direction; and in response to receiving a horizontal scrolling input, irrespective of a location of the received horizontal scrolling input: scrolling out of the preview region a number of the content item previews; and scrolling into the preview region additional content item previews without scrolling the document. 12. The method of claim 1 , further comprising receiving a request to move a location of the preview region within the document to a new location and, in response, embedding the preview region at the new location. | 0.829053 |
8,374,846 | 1 | 13 | 1. A text input method, comprising: predicting candidate words for text input in accordance with a text context; causing a first set of predicted candidate words to be displayed in a spatial arrangement which reflects the selectable directions of a navigational input device, the first set of predicted candidate words comprising at least four candidate words arranged in four different directions reflecting respective selectable directions of the navigational input device, the navigational input device being one of a rocker, a D-Pad or cursor keys; receiving user input in response to actuation, of the navigational input device; and directly selecting a displayed candidate word by toggling the navigational input device in one of the four different directions reflecting the respective selectable directions of the navigational input device. | 1. A text input method, comprising: predicting candidate words for text input in accordance with a text context; causing a first set of predicted candidate words to be displayed in a spatial arrangement which reflects the selectable directions of a navigational input device, the first set of predicted candidate words comprising at least four candidate words arranged in four different directions reflecting respective selectable directions of the navigational input device, the navigational input device being one of a rocker, a D-Pad or cursor keys; receiving user input in response to actuation, of the navigational input device; and directly selecting a displayed candidate word by toggling the navigational input device in one of the four different directions reflecting the respective selectable directions of the navigational input device. 13. The method of claim 1 , further comprising: receiving user input from input keys that are assigned to alphabetic characters; updating the prediction of candidate words based on the received user input by limiting the candidate words to candidate words including the alphabetic characters associated with the actuated input keys. | 0.501502 |
9,251,246 | 1 | 5 | 1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising: receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects is a numerical value that ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving, by the processor, a data stream of non-dimensional data objects; applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects and a probability that one of the non-dimensional data objects has been associated with a correct dimensional label; parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects and a probability that a non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. | 1. A processor-implemented method of defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the processor-implemented method comprising: receiving, by a processor, a data stream of non-contextual data objects, wherein each of the non-contextual data objects is a numerical value that ambiguously relates to multiple subject-matters; associating, by the processor, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving, by the processor, a data stream of non-dimensional data objects; applying, by the processor, a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing, by the processor, the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects and a probability that one of the non-dimensional data objects has been associated with a correct dimensional label; parsing, by the processor, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects and a probability that a non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating, by the processor, a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating, by the processor, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting, by the processor, multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining, by the processor, multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. 5. The processor-implemented method of claim 1 , further comprising: graphically representing, by the processor, said at least one dimension object and said at least one context object on a wall of said particular context-based conformed dimensional data gravity well. | 0.929806 |
8,429,183 | 8 | 9 | 8. The search engine server of claim 5 , wherein the processing circuitry, memory, and network circuitry are further operable to rank the websites having international language support based upon a recorded popularity calculation associated with the search results. | 8. The search engine server of claim 5 , wherein the processing circuitry, memory, and network circuitry are further operable to rank the websites having international language support based upon a recorded popularity calculation associated with the search results. 9. The search engine server of claim 8 , wherein the processing circuitry, memory, and network circuitry are further operable to deliver a search results page comprising links for the few of the ranked websites having international language support provided in the language used in the international search string. | 0.85436 |
8,702,433 | 1 | 7 | 1. An article of manufacture comprising: non-transitory computer readable memory storing program code, that when executed by a computing system is configured to cause the computing system to perform operations comprising: provide for display on a terminal to a user information regarding a real or simulated person; provide via the terminal an instruction related to having the user verbally identify one or more needs of the person based on the information; store an indication in computer readable memory as to whether the user correctly identified at least a first need; provide an instruction related to having the user verbally identify at least one item that appropriately corresponds to the first need; store an indication in computer readable memory as to whether the user correctly identified at least a first item, wherein the first item is a product and/or service, that appropriately corresponds to the first need; provide an instruction related to having the user verbally explain why the first item corresponds to the first need; store an indication in computer readable memory as to whether the user correctly explained why the first item corresponds to the first need; and calculate a score based at least in part on one or more of the stored indications, including at least the indication as to whether the user correctly explained why the first item corresponds to the first need; and report the score electronically. | 1. An article of manufacture comprising: non-transitory computer readable memory storing program code, that when executed by a computing system is configured to cause the computing system to perform operations comprising: provide for display on a terminal to a user information regarding a real or simulated person; provide via the terminal an instruction related to having the user verbally identify one or more needs of the person based on the information; store an indication in computer readable memory as to whether the user correctly identified at least a first need; provide an instruction related to having the user verbally identify at least one item that appropriately corresponds to the first need; store an indication in computer readable memory as to whether the user correctly identified at least a first item, wherein the first item is a product and/or service, that appropriately corresponds to the first need; provide an instruction related to having the user verbally explain why the first item corresponds to the first need; store an indication in computer readable memory as to whether the user correctly explained why the first item corresponds to the first need; and calculate a score based at least in part on one or more of the stored indications, including at least the indication as to whether the user correctly explained why the first item corresponds to the first need; and report the score electronically. 7. The system as defined in claim 1 , wherein the program code is configured to generate a report, the report indicating whether the user: identified the first need; identified the first item; and whether the user correctly explained why the first item corresponds to the first need. | 0.817655 |
7,647,304 | 9 | 10 | 9. The at least one one or more device-readable computer storage media as recited in claim 8 , wherein the system filter is configured to filter items based on a context. | 9. The at least one one or more device-readable computer storage media as recited in claim 8 , wherein the system filter is configured to filter items based on a context. 10. The at least one device-readable computer storage media as recited in claim 9 , wherein the context includes at least one of identity of a user, time of day, an application the user is working within, or an organizational discipline of the user. | 0.901891 |
7,904,467 | 7 | 8 | 7. A context aware, shortcut enabled computer program product of presenting information through a user interface on a client device, the computer program product comprising: a recording medium; means, recorded on the recording medium, for selecting a context, wherein a context is one or more situational parameters that dictate the semantics of a shortcut, wherein means, recorded on the recording medium, for selecting a context includes means, recorded on the recording medium, for selecting a default context and means, recorded on the recording medium, for selecting a display, form in dependence upon the shortcut value, wherein means, recorded on the recording medium, for displaying selected records through the user interface on the client device further comprises means, recorded on the recording medium, for downloading the selected records to the client device for display in the display, form; means, recorded on the recording medium, for receiving a shortcut entered through the user interface, the shortcut having a associated with it a shortcut field name set comprising one or more shortcut field names, wherein a shortcut is an abbreviated form of user input; means, recorded on the recording medium, for inferring from a context definition table, in dependence upon the context, a context table name and a context field name; means, recorded on the recording medium, for selecting information records from an information database in dependence upon the context, the context table name, the shortcut fields names, and the context field name; and means, recorded on the recording medium, for displaying selected records through the user interface on the client device. | 7. A context aware, shortcut enabled computer program product of presenting information through a user interface on a client device, the computer program product comprising: a recording medium; means, recorded on the recording medium, for selecting a context, wherein a context is one or more situational parameters that dictate the semantics of a shortcut, wherein means, recorded on the recording medium, for selecting a context includes means, recorded on the recording medium, for selecting a default context and means, recorded on the recording medium, for selecting a display, form in dependence upon the shortcut value, wherein means, recorded on the recording medium, for displaying selected records through the user interface on the client device further comprises means, recorded on the recording medium, for downloading the selected records to the client device for display in the display, form; means, recorded on the recording medium, for receiving a shortcut entered through the user interface, the shortcut having a associated with it a shortcut field name set comprising one or more shortcut field names, wherein a shortcut is an abbreviated form of user input; means, recorded on the recording medium, for inferring from a context definition table, in dependence upon the context, a context table name and a context field name; means, recorded on the recording medium, for selecting information records from an information database in dependence upon the context, the context table name, the shortcut fields names, and the context field name; and means, recorded on the recording medium, for displaying selected records through the user interface on the client device. 8. The computer program product of claim 7 wherein means, recorded on the recording medium, for selecting records further comprises means, recorded on the recording medium, for creating a query, wherein the query includes: the context table name as a table for the query; the shortcut fields names as field names for the query; and the context and the context field name in a condition for the query. | 0.64476 |
8,027,867 | 35 | 37 | 35. The method of claim 34 further comprising the step of issuing a certification of approval from a host entity. | 35. The method of claim 34 further comprising the step of issuing a certification of approval from a host entity. 37. The method of claim 35 further comprising the step of licensing the author with the right to post the certification with the literary work. | 0.967603 |
8,843,427 | 4 | 6 | 4. The computer-implemented method of claim 3 , further comprising: receiving a second training data set; and determining that the second training data set has one or more characteristics that are similar to the one or more characteristics of the training data set. | 4. The computer-implemented method of claim 3 , further comprising: receiving a second training data set; and determining that the second training data set has one or more characteristics that are similar to the one or more characteristics of the training data set. 6. The computer-implemented method of claim 4 , further comprising applying the filter or combination of filters associated with the most accurate predictive model to the second training data set based on determining that the second training data set has one or more characteristics that are similar to the one or more characteristics of the training data set. | 0.882889 |
9,973,517 | 10 | 14 | 10. A mobile computing device comprising: a hardware processor configured with processor-executable instructions to: monitor an activity of a software process; collect behavior information from the monitored activity; use the collected behavior information to generate a vector information structure, wherein: the generated vector information structure includes a plurality of numerical values, at least one numerical value in the plurality of numerical values identifies a number of occurrences of an action of the software process, at least one numerical value in the plurality of numerical values indicates a category for the software process based on an answer to a category query, and the plurality of numerical values collectively characterize the monitored activity; apply the generated vector information structure to a machine learning classifier model; and use a result generated by applying the generated vector information structure to the machine learning classifier model to determine whether the software process is non-benign. | 10. A mobile computing device comprising: a hardware processor configured with processor-executable instructions to: monitor an activity of a software process; collect behavior information from the monitored activity; use the collected behavior information to generate a vector information structure, wherein: the generated vector information structure includes a plurality of numerical values, at least one numerical value in the plurality of numerical values identifies a number of occurrences of an action of the software process, at least one numerical value in the plurality of numerical values indicates a category for the software process based on an answer to a category query, and the plurality of numerical values collectively characterize the monitored activity; apply the generated vector information structure to a machine learning classifier model; and use a result generated by applying the generated vector information structure to the machine learning classifier model to determine whether the software process is non-benign. 14. The mobile computing device of claim 10 , wherein the processor is configured with processor-executable instructions to use the collected behavior information to generate the vector information structure by: determining whether the monitored activity has a high probability of identifying malware; generating the vector information structure in response to determining that the monitored activity has the high probability of identifying malware; and monitoring a different type of activity in response to determining that the monitored activity does not have the high probability of identifying malware. | 0.608387 |
5,543,818 | 10 | 11 | 10. The system of claim 9, wherein the first set of the keys consists of at least one cursor movement key and the second set of the keys consists of B selection keys, and wherein the processor is programmed with software for highlighting the selected one of the groups in response to actuation of the at least one cursor movement key, and selecting said character representation within said selected one of the groups in response to actuation of one of the selection keys. | 10. The system of claim 9, wherein the first set of the keys consists of at least one cursor movement key and the second set of the keys consists of B selection keys, and wherein the processor is programmed with software for highlighting the selected one of the groups in response to actuation of the at least one cursor movement key, and selecting said character representation within said selected one of the groups in response to actuation of one of the selection keys. 11. The system of claim 10, wherein B=4. | 0.980507 |
9,308,445 | 1 | 6 | 1. A game delivery system for delivering a plurality of games in a training program configured to systematically drive neurological changes to overcome cognitive deficits associated with a neurological disorder, the game delivery system comprising: a computerized game manager configured to assess a game participant and, in response to the assessment, calibrate a training program comprising games for the game participant; the computerized game manager also being configured to administer the games, manipulate a plurality of game stimuli, and receive input from a game piece; and a participant portal that provides remote access to and delivers the games to game participants; wherein the game manager is configured to administer games of the training program to the game participant by: presenting a plurality of target and/or distractor stimuli; prompting the game participant to respond to the target and/or distractor stimuli; receiving the game participant's input through the game piece; and repeating the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range; wherein the game manager is further configured to administer an assessment, using at least one of the plurality of games, by administering a brief version of the game using mid-level game difficulty parameters. | 1. A game delivery system for delivering a plurality of games in a training program configured to systematically drive neurological changes to overcome cognitive deficits associated with a neurological disorder, the game delivery system comprising: a computerized game manager configured to assess a game participant and, in response to the assessment, calibrate a training program comprising games for the game participant; the computerized game manager also being configured to administer the games, manipulate a plurality of game stimuli, and receive input from a game piece; and a participant portal that provides remote access to and delivers the games to game participants; wherein the game manager is configured to administer games of the training program to the game participant by: presenting a plurality of target and/or distractor stimuli; prompting the game participant to respond to the target and/or distractor stimuli; receiving the game participant's input through the game piece; and repeating the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range; wherein the game manager is further configured to administer an assessment, using at least one of the plurality of games, by administering a brief version of the game using mid-level game difficulty parameters. 6. The game delivery system of claim 1 , where the training program includes one or more social cognition games. | 0.885246 |
7,917,489 | 3 | 4 | 3. The method of claim 1 , wherein said name entity is selected based on the presence of an index entry in a profile information database. | 3. The method of claim 1 , wherein said name entity is selected based on the presence of an index entry in a profile information database. 4. The method of claim 3 , wherein said name entity information includes profile information derived from the profile information database. | 0.953136 |
7,640,498 | 11 | 15 | 11. A server for enabling a document to be remotely displayed, comprising: a memory for storing data and a plurality of instructions; a processor for enabling actions, including: receiving a request for a document from a remote platform, a type of remote platform including a type of an operating system and a type of a native browser that are employed to display the document, the received document being a markup language document; determining the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, said determining the type of the remote platform comprising determining the type of the operating system and determining the type of the native browser, and the selective association being based on the determined type of the operating system and the determined type of the native browser; providing the document and the size ratio between the plurality of font sizes to the remote platform for display, the provided document being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and enabling the plurality of font sizes to be changed with at least one control of the native browser operating on the remote platform, a size change to the font sizes being determined by the operation of the native browser, the size ratio between the plurality of font sizes being maintained for a change to a size of at least one font displayed in the document at the remote platform. | 11. A server for enabling a document to be remotely displayed, comprising: a memory for storing data and a plurality of instructions; a processor for enabling actions, including: receiving a request for a document from a remote platform, a type of remote platform including a type of an operating system and a type of a native browser that are employed to display the document, the received document being a markup language document; determining the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, said determining the type of the remote platform comprising determining the type of the operating system and determining the type of the native browser, and the selective association being based on the determined type of the operating system and the determined type of the native browser; providing the document and the size ratio between the plurality of font sizes to the remote platform for display, the provided document being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and enabling the plurality of font sizes to be changed with at least one control of the native browser operating on the remote platform, a size change to the font sizes being determined by the operation of the native browser, the size ratio between the plurality of font sizes being maintained for a change to a size of at least one font displayed in the document at the remote platform. 15. The server of claim 11 , wherein the actions further comprise determining a version of the operating system for the remote platform. | 0.885329 |
9,135,344 | 1 | 2 | 1. A method for providing search results based on user interaction with content, the method comprising: (a) receiving, by a server of a linking system, identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server 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; (b) identifying, by the server of a linking system, 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, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; (c) storing, by the server of a linking system, a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click; (d) determining, by the server of the linking system, 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 (e) communicating, by the server of the linking system, responsive to the server of the linking system receiving a request to search content based on a keyword, 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. | 1. A method for providing search results based on user interaction with content, the method comprising: (a) receiving, by a server of a linking system, identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server 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; (b) identifying, by the server of a linking system, 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, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; (c) storing, by the server of a linking system, a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click; (d) determining, by the server of the linking system, 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 (e) communicating, by the server of the linking system, responsive to the server of the linking system receiving a request to search content based on a keyword, 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. 2. The method of claim 1 , wherein step (a) further comprises decoding, by the server, each of the encoded URL links. | 0.802365 |
10,074,361 | 8 | 9 | 8. The apparatus of claim 7 , wherein, for the extraction of the select frames, the processor is further configured to extract the select frames according to m*K+i and from an N number of all of the frames of the first speech, wherein i is any integer according to 1≤i≤K, and K is any integer according to 2≤K≤N, while m is made to be one or more integers according to i≤m*K+i≤N, to extract respective m*K+i-th frames of the first speech. | 8. The apparatus of claim 7 , wherein, for the extraction of the select frames, the processor is further configured to extract the select frames according to m*K+i and from an N number of all of the frames of the first speech, wherein i is any integer according to 1≤i≤K, and K is any integer according to 2≤K≤N, while m is made to be one or more integers according to i≤m*K+i≤N, to extract respective m*K+i-th frames of the first speech. 9. The apparatus of claim 8 , wherein, with K and i being maintained, the second speech is generated by extracting the respective m*K+i-th frames of the first speech, as m is incremented between 0 and K−1. | 0.916531 |
8,606,733 | 17 | 21 | 17. A color palette system comprising: a taxonomy stored in memory comprising a set of achromatic entity categories and a set of natural language terms associated with each of the achromatic entity categories; a dataset of color palettes stored in memory, each color palette consisting of a sequence of from two to one hundred swatches, each of the swatches in the color palette being of a different color, each color palette in the dataset of color palettes differing from each of the other color palettes in the dataset with respect to at least one of its swatches, at least a subset of the color palettes being annotated with labels that each include at least one natural language term from the taxonomy; a classifier stored in memory which assigns achromatic entity categories to color palettes, the classifier having been trained on color-related features extracted from labeled color palettes of the subset of the color palettes and achromatic entities assigned based on the natural language terms in their labels; instructions stored in memory for inputting color-related features extracted from a color palette into the classifier and for associating at least one of the achromatic entity categories assigned by the classifier to said color palette; an ordering component, stored in memory and executed by the processor which outputs an order of a set of palettes which are displayed along a dimension defined by a pair of opposing entity classes; and a processor in communication with the memory which executes the instructions. | 17. A color palette system comprising: a taxonomy stored in memory comprising a set of achromatic entity categories and a set of natural language terms associated with each of the achromatic entity categories; a dataset of color palettes stored in memory, each color palette consisting of a sequence of from two to one hundred swatches, each of the swatches in the color palette being of a different color, each color palette in the dataset of color palettes differing from each of the other color palettes in the dataset with respect to at least one of its swatches, at least a subset of the color palettes being annotated with labels that each include at least one natural language term from the taxonomy; a classifier stored in memory which assigns achromatic entity categories to color palettes, the classifier having been trained on color-related features extracted from labeled color palettes of the subset of the color palettes and achromatic entities assigned based on the natural language terms in their labels; instructions stored in memory for inputting color-related features extracted from a color palette into the classifier and for associating at least one of the achromatic entity categories assigned by the classifier to said color palette; an ordering component, stored in memory and executed by the processor which outputs an order of a set of palettes which are displayed along a dimension defined by a pair of opposing entity classes; and a processor in communication with the memory which executes the instructions. 21. The system of claim 17 , further comprising: a web browser for mining a collection of color palettes which have been previously labeled with comments of reviewers to form the dataset of labeled color palettes. | 0.615523 |
4,151,659 | 1 | 12 | 1. A portable machine for teaching students to read comprising: keyboard means having manually actuable switches at least some of which individually correspond to separate grammatical characteristics, display means for providing a visual display of words by generating images of words internally transmitted thereto in electronically encoded form, indicators of correctness and incorrectness, word set defining means for storing a multiplicity of words in electronically encoded form, and for assembling said words in sets wherein said sets are separately selected in response to separate actuation of said switch means corresponding to grammatical characteristics, random selection means connected to said word set defining means for selecting words at random from among words in a selected set and for transmitting words so selected to said display means for generation of an image containing at least one such word for visual observation, means for internally associating a particular one of said manually actuable switches with each of said displayed words, comparison means for sensing actuation of a manually selected switch and for ascertaining whether said selected switch is the switch internally associated with said image, and for providing an output indicative of the comparison results to said indicators of correctness and incorrectness. | 1. A portable machine for teaching students to read comprising: keyboard means having manually actuable switches at least some of which individually correspond to separate grammatical characteristics, display means for providing a visual display of words by generating images of words internally transmitted thereto in electronically encoded form, indicators of correctness and incorrectness, word set defining means for storing a multiplicity of words in electronically encoded form, and for assembling said words in sets wherein said sets are separately selected in response to separate actuation of said switch means corresponding to grammatical characteristics, random selection means connected to said word set defining means for selecting words at random from among words in a selected set and for transmitting words so selected to said display means for generation of an image containing at least one such word for visual observation, means for internally associating a particular one of said manually actuable switches with each of said displayed words, comparison means for sensing actuation of a manually selected switch and for ascertaining whether said selected switch is the switch internally associated with said image, and for providing an output indicative of the comparison results to said indicators of correctness and incorrectness. 12. Apparatus according to claim 1 further characterized in that at least one set of words is assembled having a considerable number or words beginning with a particular consonant. | 0.87984 |
8,713,119 | 1 | 47 | 1. A method for processing voice commands, performed at a portable electronic device with one or more processors and memory storing instructions for execution by the one or more processors, the method comprising: in response to user input, recording at least a portion of a voice command on the portable electronic device; when recording the portion of the voice command on the portable electronic device, storing contextual information of the portable electronic device; after recording the portion of the voice command at the portable electronic device, uploading the portion of the voice command and the stored contextual information from the portable electronic device to remote computing equipment; receiving, from the remote computing equipment, results associated with processing the portion of the voice command and the stored contextual information; and presenting the results. | 1. A method for processing voice commands, performed at a portable electronic device with one or more processors and memory storing instructions for execution by the one or more processors, the method comprising: in response to user input, recording at least a portion of a voice command on the portable electronic device; when recording the portion of the voice command on the portable electronic device, storing contextual information of the portable electronic device; after recording the portion of the voice command at the portable electronic device, uploading the portion of the voice command and the stored contextual information from the portable electronic device to remote computing equipment; receiving, from the remote computing equipment, results associated with processing the portion of the voice command and the stored contextual information; and presenting the results. 47. The method of claim 1 , wherein the contextual information is one or both of a current date and a current time. | 0.88921 |
10,026,107 | 6 | 7 | 6. The computer-implemented method of claim 5 , wherein the fingerprint information further identifies time information associated with at least the first action and the one or more subsequent actions. | 6. The computer-implemented method of claim 5 , wherein the fingerprint information further identifies time information associated with at least the first action and the one or more subsequent actions. 7. The computer-implemented method of claim 6 , wherein the time information comprises an amount of time spent by the user on the particular network page of the electronic marketplace website after performing at least the first action and one or more subsequent actions. | 0.901026 |
8,965,763 | 9 | 14 | 9. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: determining a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level. | 9. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: determining a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level. 14. The article of manufacture of claim 9 , wherein a first feature vector characterizes the reference transcription, wherein a second feature vector characterizes the secondary transcription, and wherein updating the weight vector comprises adding the first feature vector to the weight vector and subtracting the second feature vector from the weight vector. | 0.769526 |
9,244,985 | 10 | 18 | 10. A method performed by one or more processing devices, comprising: receiving, by one or more processing devices, data to generate a user interface on a computer display device; and using the data to generate, by one or more processing devices, the user interface on the computer display device; wherein the user interface comprises: a search field to receive a search query for use in searching Web content and a corpus of a social networking service, a results display area to display search results received in response to a search initiated through the search field, and individual display areas corresponding to each of one or more members of the social networking service that have an association with content corresponding to the search results, the display areas for display on a same page as, but separate from, the results display area, each of the display areas for enabling access to information about a corresponding member of the social networking service who is represented by a the corresponding display area and about content associated with the member of the social networking service, wherein the individual display areas are generated based on a number of interactions of the one or more members with the content corresponding to the search results. | 10. A method performed by one or more processing devices, comprising: receiving, by one or more processing devices, data to generate a user interface on a computer display device; and using the data to generate, by one or more processing devices, the user interface on the computer display device; wherein the user interface comprises: a search field to receive a search query for use in searching Web content and a corpus of a social networking service, a results display area to display search results received in response to a search initiated through the search field, and individual display areas corresponding to each of one or more members of the social networking service that have an association with content corresponding to the search results, the display areas for display on a same page as, but separate from, the results display area, each of the display areas for enabling access to information about a corresponding member of the social networking service who is represented by a the corresponding display area and about content associated with the member of the social networking service, wherein the individual display areas are generated based on a number of interactions of the one or more members with the content corresponding to the search results. 18. The method of claim 10 , wherein one or more of the display areas provide one or more options for enabling social interaction, over the social networking service, with subjects of the display areas. | 0.831667 |
10,019,641 | 1 | 2 | 1. A method, performed on a mobile computing device, for reducing a number of user corrections entered to obtain a correct account number for a financial transaction card, the method comprising: obtaining, at the mobile computing device, multiple versions of text recognition results, wherein each version of the text recognition results is associated with a total confidence score; displaying, by the mobile computing device, a visual representation of a best guess comprising a version of the text recognition results that is associated with a highest total confidence score; receiving, by the mobile computing device, a user selection, as a selected character from at least one of a plurality of characters to verify from the best guess selected based on individual confidence scores, wherein the multiple versions of the text recognition results are updated by performing one or more of: eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match the selected character; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not satisfy the Luhn algorithm; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match any of multiple known issuer identification numbers; updating the total confidence score for the multiple versions of text recognition results; or any combination thereof; and updating, by the mobile computing device, the visual representation to display a new best guess from the remaining versions of the text recognition results, wherein the new best guess comprises at least: a first difference from the best guess that is a change of a first character in the best guess to the selected character, and a second difference from the best guess that is a change of a second character in the best guess other than to the selected character. | 1. A method, performed on a mobile computing device, for reducing a number of user corrections entered to obtain a correct account number for a financial transaction card, the method comprising: obtaining, at the mobile computing device, multiple versions of text recognition results, wherein each version of the text recognition results is associated with a total confidence score; displaying, by the mobile computing device, a visual representation of a best guess comprising a version of the text recognition results that is associated with a highest total confidence score; receiving, by the mobile computing device, a user selection, as a selected character from at least one of a plurality of characters to verify from the best guess selected based on individual confidence scores, wherein the multiple versions of the text recognition results are updated by performing one or more of: eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match the selected character; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not satisfy the Luhn algorithm; eliminating, from the multiple versions of text recognition results, one or more of the multiple versions of text recognition results that do not match any of multiple known issuer identification numbers; updating the total confidence score for the multiple versions of text recognition results; or any combination thereof; and updating, by the mobile computing device, the visual representation to display a new best guess from the remaining versions of the text recognition results, wherein the new best guess comprises at least: a first difference from the best guess that is a change of a first character in the best guess to the selected character, and a second difference from the best guess that is a change of a second character in the best guess other than to the selected character. 2. The method of claim 1 further comprising: verifying that the new best guess includes the correct account number by: sending a proposed account number associated with the new best guess to a financial institution; and receiving, from the financial institution, a confirmation that the proposed account number associated with the new best guess indicates valid account data. | 0.50133 |
7,853,987 | 2 | 4 | 2. The method of claim 1 wherein the processing of the context based access control policies specified in a formal descriptive language comprises processing the context based access control policies in the form of events. | 2. The method of claim 1 wherein the processing of the context based access control policies specified in a formal descriptive language comprises processing the context based access control policies in the form of events. 4. The method of claim 2 wherein the processing of the context based access control policies in the form of events comprises processing the context based access control policies in the form of events specified in terms of a user s, a type of user s, a restricted area o of a secured facility, a type of restricted area o, and an access point d permitting entrance to or exit from the restricted area o. | 0.80099 |
8,479,007 | 10 | 13 | 10. A method according to claim 1 wherein the encoded portion of the document is a machine-readable symbol that is printed in a size and format suitable for acquisition by a conventional imaging device to permit acquisition and transmission of the encoded portion of the document to an authentication center. | 10. A method according to claim 1 wherein the encoded portion of the document is a machine-readable symbol that is printed in a size and format suitable for acquisition by a conventional imaging device to permit acquisition and transmission of the encoded portion of the document to an authentication center. 13. A method according to claim 10 wherein the encoded portion of the document is printed, as a two-dimensional symbolic barcode. | 0.962281 |
8,307,372 | 6 | 7 | 6. The method of claim 5 , wherein the element is defined in a where clause. | 6. The method of claim 5 , wherein the element is defined in a where clause. 7. The method of claim 6 , wherein the where clause explicitly references the variable. | 0.981707 |
10,069,971 | 16 | 18 | 16. A system comprising: one or more processors; and one or more non-transitory computer-readable media having computer executable instructions that, when executed, cause the one or more processors to: determine one or more audio signals of a conversation between a first participant and a second participant; track attributes of the one or more audio signals, one or more attributes of the attributes quantifying one or more aspects of the conversation based at least in part on one or more words used by the first participant and the second participant; determine a visual conversation feedback output representing the conversation based at least in part on the one or more attributes; determine that the visual conversation feedback output includes a facial expression, the facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes of the one or more audio signals, and the facial expression representing an estimation of a state of mind of the first participant during a first time period; determine that the visual conversation feedback output further includes a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the second participant; determine that the visual conversation feedback output further includes a second time series graph indicating a score for the second participant, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; cause visual output of the visual conversation feedback output for view by at least the second participant, the visual conversation feedback output including the facial expression being updated in real-time or near real-time based at least in part on a change of the estimation of the state of mind of the first participant; generate a communication suggestion for the second participant based at least in part on the estimation of the state of mind of the first participant; and cause the visual output to include the communication suggestion for view by the second participant. | 16. A system comprising: one or more processors; and one or more non-transitory computer-readable media having computer executable instructions that, when executed, cause the one or more processors to: determine one or more audio signals of a conversation between a first participant and a second participant; track attributes of the one or more audio signals, one or more attributes of the attributes quantifying one or more aspects of the conversation based at least in part on one or more words used by the first participant and the second participant; determine a visual conversation feedback output representing the conversation based at least in part on the one or more attributes; determine that the visual conversation feedback output includes a facial expression, the facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes of the one or more audio signals, and the facial expression representing an estimation of a state of mind of the first participant during a first time period; determine that the visual conversation feedback output further includes a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the second participant; determine that the visual conversation feedback output further includes a second time series graph indicating a score for the second participant, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; cause visual output of the visual conversation feedback output for view by at least the second participant, the visual conversation feedback output including the facial expression being updated in real-time or near real-time based at least in part on a change of the estimation of the state of mind of the first participant; generate a communication suggestion for the second participant based at least in part on the estimation of the state of mind of the first participant; and cause the visual output to include the communication suggestion for view by the second participant. 18. The system as recited in claim 16 , wherein the one or more non-transitory computer-readable media having computer executable instructions further cause the one or more processors to determine that at least a portion of the conversation includes an exchange of text-based messages. | 0.819392 |
7,707,037 | 1 | 8 | 1. A method of monitoring a location having a plurality of audio sensors and video sensors, comprising: receiving auditory data from at least one of the plurality of audio sensors; comparing at least a first portion of the auditory data to a lexicon comprising a plurality of keywords to determine if there is a match to a first keyword from the lexicon; triggering a policy based on the keyword match; associating at least one video sensor with at least one audio sensor; selecting the at least one video sensor if a match is found; receiving video data from the at least one video sensor; and archiving the auditory data and the video data, wherein archiving the auditory data includes associating the auditory data with data indicating the triggered policy. | 1. A method of monitoring a location having a plurality of audio sensors and video sensors, comprising: receiving auditory data from at least one of the plurality of audio sensors; comparing at least a first portion of the auditory data to a lexicon comprising a plurality of keywords to determine if there is a match to a first keyword from the lexicon; triggering a policy based on the keyword match; associating at least one video sensor with at least one audio sensor; selecting the at least one video sensor if a match is found; receiving video data from the at least one video sensor; and archiving the auditory data and the video data, wherein archiving the auditory data includes associating the auditory data with data indicating the triggered policy. 8. The method as recited in claim 1 , further comprising comparing the first portion of the auditory data to the lexicon to determine if there is a match to a second keyword from the lexicon. | 0.746011 |
9,269,057 | 25 | 28 | 25. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class. | 25. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class. 28. The computer program product of claim 25 , wherein the operations further comprise blocking examples associated with the second class from being distributed to a worker receiving only examples associated with the first class. | 0.666181 |
7,571,160 | 1 | 8 | 1. A method for an implementation of XML Query language, comprising the steps of: receiving an XQuery request; creating a token stream representation of one or more XML documents that are required to process said XQuery request, wherein the step of creating the token stream further comprises accessing an XML document, parsing a schema associated with the XML document, using the contents of the schema associated with the XML document to create a tokenized representation of the entire XML document, as a sequence of tokens describing the XML document, and including within the sequence of tokens a namespace declaration for the XML document, name tokens indicating a fully qualified name for each element, and name tokens specifying a type of the element as defined in the schema, and populating the tokens with one of data from the XML schema or data from the XML document; transforming said XQuery request into a second query that can work on said token stream representation; and executing said second query on said token stream representation, wherein said transforming step further comprises converting said XQuery request into a sequence of elementary operators, and applying the sequence of elementary operators against the tokenized representation of the XML document, with each operator applying a transformation of the operator input and feeding the operator output to the next operator, and wherein instead of completely consuming input before performing the transformation, each operator consumes a minimal amount of input and immediately begins to produce results, that is directly available to the next operator. | 1. A method for an implementation of XML Query language, comprising the steps of: receiving an XQuery request; creating a token stream representation of one or more XML documents that are required to process said XQuery request, wherein the step of creating the token stream further comprises accessing an XML document, parsing a schema associated with the XML document, using the contents of the schema associated with the XML document to create a tokenized representation of the entire XML document, as a sequence of tokens describing the XML document, and including within the sequence of tokens a namespace declaration for the XML document, name tokens indicating a fully qualified name for each element, and name tokens specifying a type of the element as defined in the schema, and populating the tokens with one of data from the XML schema or data from the XML document; transforming said XQuery request into a second query that can work on said token stream representation; and executing said second query on said token stream representation, wherein said transforming step further comprises converting said XQuery request into a sequence of elementary operators, and applying the sequence of elementary operators against the tokenized representation of the XML document, with each operator applying a transformation of the operator input and feeding the operator output to the next operator, and wherein instead of completely consuming input before performing the transformation, each operator consumes a minimal amount of input and immediately begins to produce results, that is directly available to the next operator. 8. The method according to claim 1 , further comprising: executing said XQuery request in a context, wherein said context is comprised of resources required for said XQuery request execution. | 0.813477 |
9,171,180 | 8 | 10 | 8. The system of claim 1 , the database system software further operable to cause: initiating a digital conversation between at least the at least one user and a second user, wherein the digital conversation provides access to data items of the requested rights-managed file to the at least one user via a user interface displayable on a display device. | 8. The system of claim 1 , the database system software further operable to cause: initiating a digital conversation between at least the at least one user and a second user, wherein the digital conversation provides access to data items of the requested rights-managed file to the at least one user via a user interface displayable on a display device. 10. The system of claim 8 , wherein the digital conversation is a public conversation accessible to other users within the enterprise level information networking system. | 0.948609 |
8,397,223 | 18 | 19 | 18. The computer-implemented method of claim 15 , further comprising interpreting the modified input files at runtime. | 18. The computer-implemented method of claim 15 , further comprising interpreting the modified input files at runtime. 19. The computer-implemented method of claim 18 , further comprising binding the web application source code with the interpreted modified input files at runtime. | 0.931181 |
9,251,238 | 13 | 15 | 13. A non-transitory computer-readable storage medium having stored thereon computer executable program code, which, when executed by a computer, causes the computer to perform a method of: receiving a Simple Protocol And Resource Description Framework Query Language (SPARQL) query; generating a native query from the SPARQL query using a mapping file comprising metadata that describes a multidimensional database; mapping a first Resource Description Framework (RDF) class specified in the SPARQL query with a first column in the multidimensional database; mapping a first property corresponding to the first RDF class specified in the SPARQL query with first values corresponding to the first column in the multidimensional database; executing the native query on the multidimensional database; receiving a native result comprising data stored in the multidimensional database resulting from execution of the native query against the multidimensional database; and generating a SPARQL result from the native result using the mapping file, the SPARQL result representing a response to the SPARQL query. | 13. A non-transitory computer-readable storage medium having stored thereon computer executable program code, which, when executed by a computer, causes the computer to perform a method of: receiving a Simple Protocol And Resource Description Framework Query Language (SPARQL) query; generating a native query from the SPARQL query using a mapping file comprising metadata that describes a multidimensional database; mapping a first Resource Description Framework (RDF) class specified in the SPARQL query with a first column in the multidimensional database; mapping a first property corresponding to the first RDF class specified in the SPARQL query with first values corresponding to the first column in the multidimensional database; executing the native query on the multidimensional database; receiving a native result comprising data stored in the multidimensional database resulting from execution of the native query against the multidimensional database; and generating a SPARQL result from the native result using the mapping file, the SPARQL result representing a response to the SPARQL query. 15. The non-transitory computer-readable storage medium of claim 13 , wherein the multidimensional database is organized in a star schema. | 0.757895 |
8,719,295 | 13 | 14 | 13. The apparatus of claim 12 , wherein the optimal temporal hierarchy is used to materialize pre-computed results that are used to accelerate a response time to a query workload in the presence of newly inserted database records. | 13. The apparatus of claim 12 , wherein the optimal temporal hierarchy is used to materialize pre-computed results that are used to accelerate a response time to a query workload in the presence of newly inserted database records. 14. The apparatus of claim 13 , wherein the newly inserted database records are inserted at any time individually or at fixed time intervals in batches. | 0.935374 |
7,996,437 | 1 | 2 | 1. A program stored on a computer-readable medium, which refers to a first data schema and a second data schema that describe data structures to correlate a data item name constituting the first data schema with a data item name constituting the second data schema, the program being implemented on and controlling a computer to execute the procedures of: extracting the data item name constituting the first data schema; extracting the data item name constituting the second data schema; extracting element concepts included in the extracted data item names of the first data schema and the second data schema; setting a distinctive relation and a time-sequential order relation between the data item names based on the extracted element concepts; reading the data item names of the first data schema and the second data schema and setting a correlation between the two read data item names based on the distinctive relation to satisfy a constraint imposed by the time-sequential order relation between the data item names; and accumulating the correlation of the data item names; reading two data item names of one of the first data schema and the second data schema; extracting a set of common character strings from among character strings constituting the two data item names as a first element concept when character strings of the two data item names are compared with each other and are judged to include synonymous character strings; and extracting a set of character strings excluding common character strings from the character strings constituting the two data item names as a second element concept when the character strings of the two data item names are compared with each other and are judged to include synonymous character strings; judging a time-sequential order relation for the two item names corresponding to the second element concept; and setting that the set of character strings constituting the second element concept has a distinctive relation when no time-sequential order relation is included in the second element concept. | 1. A program stored on a computer-readable medium, which refers to a first data schema and a second data schema that describe data structures to correlate a data item name constituting the first data schema with a data item name constituting the second data schema, the program being implemented on and controlling a computer to execute the procedures of: extracting the data item name constituting the first data schema; extracting the data item name constituting the second data schema; extracting element concepts included in the extracted data item names of the first data schema and the second data schema; setting a distinctive relation and a time-sequential order relation between the data item names based on the extracted element concepts; reading the data item names of the first data schema and the second data schema and setting a correlation between the two read data item names based on the distinctive relation to satisfy a constraint imposed by the time-sequential order relation between the data item names; and accumulating the correlation of the data item names; reading two data item names of one of the first data schema and the second data schema; extracting a set of common character strings from among character strings constituting the two data item names as a first element concept when character strings of the two data item names are compared with each other and are judged to include synonymous character strings; and extracting a set of character strings excluding common character strings from the character strings constituting the two data item names as a second element concept when the character strings of the two data item names are compared with each other and are judged to include synonymous character strings; judging a time-sequential order relation for the two item names corresponding to the second element concept; and setting that the set of character strings constituting the second element concept has a distinctive relation when no time-sequential order relation is included in the second element concept. 2. The program according to claim 1 , wherein the correlation procedure sets that the two data items correspond to each other when the character strings of the two read data item names are compared with each other and are judged to include the synonymous character stings but not to have a distinctive relation. | 0.501603 |
8,776,094 | 1 | 3 | 1. A computer-implemented method comprising: receiving a request for information associated with one or more available operating system interfaces; obtaining the information associated with the one or more available operating system interfaces, the operating system interfaces being described using an abstract type system, wherein the abstract type system is configured to enable interface descriptions that are independent from specific programming languages, and wherein at least one description of an operating system interface includes calling parameter type descriptions; programmatically determining one or more abstract types associated with the one or more available operating system interfaces using at least one binary contract, wherein determining the one or more abstract types comprises determining behavior associated with the one or more abstract types, wherein the binary contract is configured to include machine-level definitions; and mapping individual determined abstract types to individual respective types associated with at least one specific programming language. | 1. A computer-implemented method comprising: receiving a request for information associated with one or more available operating system interfaces; obtaining the information associated with the one or more available operating system interfaces, the operating system interfaces being described using an abstract type system, wherein the abstract type system is configured to enable interface descriptions that are independent from specific programming languages, and wherein at least one description of an operating system interface includes calling parameter type descriptions; programmatically determining one or more abstract types associated with the one or more available operating system interfaces using at least one binary contract, wherein determining the one or more abstract types comprises determining behavior associated with the one or more abstract types, wherein the binary contract is configured to include machine-level definitions; and mapping individual determined abstract types to individual respective types associated with at least one specific programming language. 3. The computer-implemented method of claim 1 , the information comprising version information associated with at least one interface, data types of individual parameters associated with the at least one interface, and a calling order of the individual parameters associated with the at least one interface. | 0.618159 |
7,703,003 | 31 | 34 | 31. A computer-implemented method, comprising: maintaining a service store comprising a plurality of service objects each corresponding to a different service, wherein each service object has a hierarchical structure specifying a plurality of activities and one or more service elements for each activity, wherein each activity is a procedure to be carried out in providing the corresponding service, wherein each service object includes activity data identifying the service object's respective plurality of activities and specifying the one or more service elements for each activity, wherein each service element represents a component of the corresponding activity and specifies a representation for inclusion in a document to be used in performing the service; wherein a particular service element of an activity of a service object stored in the service store comprises at least one of: a description of the activity, an input for the activity, an output or deliverable from the activity, an assumption for the activity, information regarding responsibility for the activity, a subsidiary activity of the activity, or a sub-work plan of the activity; maintaining a document template store comprising one or more document templates, wherein each document template specifies an organization of a type of document to be used in performing a service; and identifying, for a given service selected by a user, and for a given document template selected by the user, one or more service elements of one or more activities of a service object corresponding to the given service, wherein representations of the one or more service elements are to be included in a document organized in accordance with the given document template; and generating a document including representations of the one or more service elements, wherein the document is organized in accordance with the given document template, wherein the representations of the one or more service elements are included in the document without the user having to identify each representation separately. | 31. A computer-implemented method, comprising: maintaining a service store comprising a plurality of service objects each corresponding to a different service, wherein each service object has a hierarchical structure specifying a plurality of activities and one or more service elements for each activity, wherein each activity is a procedure to be carried out in providing the corresponding service, wherein each service object includes activity data identifying the service object's respective plurality of activities and specifying the one or more service elements for each activity, wherein each service element represents a component of the corresponding activity and specifies a representation for inclusion in a document to be used in performing the service; wherein a particular service element of an activity of a service object stored in the service store comprises at least one of: a description of the activity, an input for the activity, an output or deliverable from the activity, an assumption for the activity, information regarding responsibility for the activity, a subsidiary activity of the activity, or a sub-work plan of the activity; maintaining a document template store comprising one or more document templates, wherein each document template specifies an organization of a type of document to be used in performing a service; and identifying, for a given service selected by a user, and for a given document template selected by the user, one or more service elements of one or more activities of a service object corresponding to the given service, wherein representations of the one or more service elements are to be included in a document organized in accordance with the given document template; and generating a document including representations of the one or more service elements, wherein the document is organized in accordance with the given document template, wherein the representations of the one or more service elements are included in the document without the user having to identify each representation separately. 34. The method as recited in claim 31 , wherein the representation of at least one service element of the one or more service elements is stored as a text file. | 0.894598 |
8,587,540 | 1 | 5 | 1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: concurrently displaying on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detecting a first input on the touch-sensitive surface; in response to detecting the first input, entering a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detecting a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjusting the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintaining the first set of characters in the left side of the split keyboard, and maintaining the second set of characters in the right side of the split keyboard; detecting a third input; and, in response to detecting the third input, exiting the reconfiguration mode for the integrated input area. | 1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: concurrently displaying on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detecting a first input on the touch-sensitive surface; in response to detecting the first input, entering a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detecting a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjusting the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintaining the first set of characters in the left side of the split keyboard, and maintaining the second set of characters in the right side of the split keyboard; detecting a third input; and, in response to detecting the third input, exiting the reconfiguration mode for the integrated input area. 5. The device of claim 1 , wherein the second input includes a horizontal movement of a left thumb away from a left vertical side of the display; and the one or more programs include instructions for: in response to detecting the horizontal movement of the left thumb away from the left vertical side of the display, increasing the size of the left side of the split keyboard. | 0.576577 |
8,639,509 | 4 | 5 | 4. The method of claim 1 , wherein the statistical model includes a maximum entropy model. | 4. The method of claim 1 , wherein the statistical model includes a maximum entropy model. 5. The method of claim 4 , further comprising: assigning a Part-Of-Speech (POS) tag to each word in the interpreted text string, wherein the syntactical parse tree represents the assignment of the POS tags. | 0.966373 |
9,613,136 | 20 | 21 | 20. The system of claim 19 , wherein the assessment tracking engine is further configured to derive interaction metrics associated with the stored interaction data. | 20. The system of claim 19 , wherein the assessment tracking engine is further configured to derive interaction metrics associated with the stored interaction data. 21. The system of claim 20 , wherein the interaction metrics include at least one of the following: number of assessments, assessment trends, and validation statistics. | 0.959104 |
7,664,323 | 1 | 2 | 1. A system that facilitates data recognition comprising: a processor coupled to a memory, the processor executing: a hash component that receives an input with at least one representation of an unknown character glyph and attempts to determine meta data associated with the glyph via at least one hash table; a hash table component that receives training data, wherein the training data comprises documents, fonts, and glyph information, including glyph appearance frequency; the hash table component formulates the hash table á posteriori based on the training data and via hashing a glyph meta data derived from the training data, wherein the hash table is utilized to identify a print character where the character glyph is identical over an independent presentation, the hash table is updated based on a threshold value; and an auxiliary character recognition component that is utilized as a secondary form of character recognition to supplement the hash component in determining the glyph meta data, the auxiliary character recognition component is utilized as an alternative to utilizing the hash component if the hash component fails to identify the glyph meta data. | 1. A system that facilitates data recognition comprising: a processor coupled to a memory, the processor executing: a hash component that receives an input with at least one representation of an unknown character glyph and attempts to determine meta data associated with the glyph via at least one hash table; a hash table component that receives training data, wherein the training data comprises documents, fonts, and glyph information, including glyph appearance frequency; the hash table component formulates the hash table á posteriori based on the training data and via hashing a glyph meta data derived from the training data, wherein the hash table is utilized to identify a print character where the character glyph is identical over an independent presentation, the hash table is updated based on a threshold value; and an auxiliary character recognition component that is utilized as a secondary form of character recognition to supplement the hash component in determining the glyph meta data, the auxiliary character recognition component is utilized as an alternative to utilizing the hash component if the hash component fails to identify the glyph meta data. 2. The system of claim 1 , the unknown glyph representation comprising uncompressed, compressed, and encoded representations. | 0.860491 |
9,792,534 | 2 | 3 | 2. The method as described in claim 1 , further comprising converting the word vector into a caption for the target image as a post-processing operation. | 2. The method as described in claim 1 , further comprising converting the word vector into a caption for the target image as a post-processing operation. 3. The method as described in claim 2 , wherein converting the word vector into a caption for the target image comprises selecting a dictionary and mapping the word vector to words in the semantic word vector space based on the selected dictionary. | 0.900879 |
9,098,584 | 3 | 4 | 3. The method of claim 2 , wherein the identifying comprises: identifying the individual subject by performing the facial recognition to compare the at least first facial image to a database of stored images linked to corresponding people, the individual subject being one of the corresponding people; and identifying the general web content by carrying out a term-based general web search on the individual subject's name. | 3. The method of claim 2 , wherein the identifying comprises: identifying the individual subject by performing the facial recognition to compare the at least first facial image to a database of stored images linked to corresponding people, the individual subject being one of the corresponding people; and identifying the general web content by carrying out a term-based general web search on the individual subject's name. 4. The method of claim 3 , wherein the database of stored images is under control of the search entity. | 0.980559 |
8,271,256 | 1 | 2 | 1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics. | 1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics. 2. The method of claim 1 , wherein key independent parameters comprise at least one of: a flatband voltage, for both n-type and p-type devices; a channel doping concentration at depletion edge of zero body bias, for both n-type and p-type devices; an electrical oxide thickness; a zero biased lightly doped drain resistance per unit width, for both n-type and p-type devices; a channel length offset correction due to production techniques; and a channel width offset production due to production techniques. | 0.63766 |
7,665,063 | 17 | 18 | 17. The method of claim 15 , further comprising parsing said procedures for automated generation of dependency networks and associated hash tables. | 17. The method of claim 15 , further comprising parsing said procedures for automated generation of dependency networks and associated hash tables. 18. The method of claim 17 , further comprising utilizing an ATN (Augmented Transition Network) based parser to perform said parsing step. | 0.953315 |
8,775,400 | 1 | 2 | 1. A method of presenting facts extracted from a social network on a device having a processor and a fact store, respective facts associated with at least one topic, the method comprising: executing on the processor instructions configured to: upon receiving from a user within the social network a message conveying a personal opinion of the user: identify in the message a reference identifying a topic associated with the personal opinion, translate the personal opinion in the message into at least one fact associated with the topic identified by the reference and not explicitly stated in the message, and store the fact in the fact store associated with the topic; and upon receiving from a user a query related to a topic: select from the fact store at least one fact associated with the topic, and present the at least one fact to the user. | 1. A method of presenting facts extracted from a social network on a device having a processor and a fact store, respective facts associated with at least one topic, the method comprising: executing on the processor instructions configured to: upon receiving from a user within the social network a message conveying a personal opinion of the user: identify in the message a reference identifying a topic associated with the personal opinion, translate the personal opinion in the message into at least one fact associated with the topic identified by the reference and not explicitly stated in the message, and store the fact in the fact store associated with the topic; and upon receiving from a user a query related to a topic: select from the fact store at least one fact associated with the topic, and present the at least one fact to the user. 2. The method of claim 1 : identifying the at least one fact comprising: identifying a time associated with the fact; storing the fact in the fact store comprising: storing the fact in the fact store associated with the topic and associated with the time; and selecting the at least one fact from the fact store comprising: selecting from the fact store at least one fact associated with the topic and associated with a time associated with the query. | 0.53791 |
9,626,699 | 1 | 8 | 1. A system comprising one or more processors and a non-transitory storage medium comprising program logic for execution by the one or more processors, the program logic comprising: a native advertisement placement engine that: obtains a Document Object Model of an HTML document; identifies Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifies, with the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model; constructs a suffix tree of a string of tags comprising all tags in the Document Object Model; performs a traversal of the suffix tree, beginning with a root node, and computes, for each node that is non-root and non-leaf, a number of leaf nodes of the each node; analyzes the Document Object Model by performing a recursion of the suffix tree; filtering determined candidate containers based on at least one of (1) candidate container size, (2) size of a meta-container associated with multiple candidate containers, (3) number of element types included within a candidate container, (4) anticipated display location of native advertisements associated with candidate containers, and (5) topology of the Document Object Model; and based at least in part on the analysis associated with the Document Object Model, and utilizing at least some of the identified elements, determines, within the Document Object Model, one or more native advertisement placement candidate containers. | 1. A system comprising one or more processors and a non-transitory storage medium comprising program logic for execution by the one or more processors, the program logic comprising: a native advertisement placement engine that: obtains a Document Object Model of an HTML document; identifies Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifies, with the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model; constructs a suffix tree of a string of tags comprising all tags in the Document Object Model; performs a traversal of the suffix tree, beginning with a root node, and computes, for each node that is non-root and non-leaf, a number of leaf nodes of the each node; analyzes the Document Object Model by performing a recursion of the suffix tree; filtering determined candidate containers based on at least one of (1) candidate container size, (2) size of a meta-container associated with multiple candidate containers, (3) number of element types included within a candidate container, (4) anticipated display location of native advertisements associated with candidate containers, and (5) topology of the Document Object Model; and based at least in part on the analysis associated with the Document Object Model, and utilizing at least some of the identified elements, determines, within the Document Object Model, one or more native advertisement placement candidate containers. 8. The system of claim 1 , wherein the identified candidate containers relate to content with which native advertisements may be associated. | 0.713115 |
8,515,025 | 10 | 17 | 10. A teleconference system comprising: a plurality of client terminals for respective ones of a plurality of participants; and a server that is in communication with the plurality of client terminals, the server configured to: receive (i) a first utterance from one of the plurality of client terminals, the first utterance including a plurality of words, the plurality of words including an identifier of one of the plurality of participants and at least one additional word, and (ii) an initial background noise that is local to the one of the plurality of participants; recognize the plurality of words; parse the identifier from the at least one additional word; associate (i) the identifier to a voiceprint of the one of the plurality of participants, the voiceprint including a set of vocal characteristics that can be used to identify speech as originating from the one of the plurality of participants, and (ii) the initial background noise to the identifier and the voiceprint; receive a second utterance and a second background noise from the one of the plurality of participants; compare (i) the second utterance to the voiceprint, and (ii) the second background noise to the initial background noise in order to confirm that the one of the plurality of participants uttered the second utterance; determine, based on the comparing, that the identifier is associated with the second utterance; and provide the identifier to at least another client terminal in response to determining that the identifier is associated with the second utterance. | 10. A teleconference system comprising: a plurality of client terminals for respective ones of a plurality of participants; and a server that is in communication with the plurality of client terminals, the server configured to: receive (i) a first utterance from one of the plurality of client terminals, the first utterance including a plurality of words, the plurality of words including an identifier of one of the plurality of participants and at least one additional word, and (ii) an initial background noise that is local to the one of the plurality of participants; recognize the plurality of words; parse the identifier from the at least one additional word; associate (i) the identifier to a voiceprint of the one of the plurality of participants, the voiceprint including a set of vocal characteristics that can be used to identify speech as originating from the one of the plurality of participants, and (ii) the initial background noise to the identifier and the voiceprint; receive a second utterance and a second background noise from the one of the plurality of participants; compare (i) the second utterance to the voiceprint, and (ii) the second background noise to the initial background noise in order to confirm that the one of the plurality of participants uttered the second utterance; determine, based on the comparing, that the identifier is associated with the second utterance; and provide the identifier to at least another client terminal in response to determining that the identifier is associated with the second utterance. 17. The teleconference system of claim 10 , further comprising a plurality of microphones, and wherein the server is further configured to: associate each of the plurality of microphones with corresponding ones of the plurality of participants; determine which one of the plurality of microphones received the second utterance; and confirm that the one of the plurality of participants uttered the second utterance based on which of the plurality of microphones received the second utterance. | 0.656904 |
4,724,523 | 44 | 50 | 44. A method according to claim 41 in which said second pattern storing step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. | 44. A method according to claim 41 in which said second pattern storing step comprises storing a signal representative of at least one of a partial verbal paradigm and a partial nominal paradigm. 50. A method according to claim 44 in which said second pattern storing step comprises storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal. | 0.931624 |
8,615,804 | 13 | 18 | 13. A method for enforcing security policies for executable computer code in a web application in which the web application constructs statements of a component language by mixing characters provided by a first source and characters provided by a second source, comprising the steps of: a) on a first computer processor residing on a first device, encoding each of the characters with two code points, resulting in a standard character and a complement character of the standard character, wherein said standard character is encoded into the complement character by complimenting each standard character individually in the executable statement, and wherein the complement characters indicate the untrusted data and the standard characters indicate the trusted data; b) using the standard characters to represent trusted characters and using the complement characters to represent untrusted characters, wherein the trusted characters are defined as component language code or developer code that is developer generated and wherein the untrusted characters are defined as any data that is input by said user; c) interleaving the encoded characters from the first source with the encoded characters from the second source to create the executable computer code for execution on a second computer processor residing on a second device, and comparing the characters using value comparison, wherein value comparison compares all of the bits of a character not including the sign bit; d) specifying security policies for the second computer processor by designating tokens in the language of the second computer processor to be either a sensitive token or an allowed token, wherein an allowed token is a token deemed trusted and a sensitive token is a token deemed untrusted; and e) using the second computer processor to parse the executable computer code created by matching the sensitive tokens using full comparison and matching the allowed tokens using value comparison, wherein full comparison compares all of the bits of the character including the sign bit. | 13. A method for enforcing security policies for executable computer code in a web application in which the web application constructs statements of a component language by mixing characters provided by a first source and characters provided by a second source, comprising the steps of: a) on a first computer processor residing on a first device, encoding each of the characters with two code points, resulting in a standard character and a complement character of the standard character, wherein said standard character is encoded into the complement character by complimenting each standard character individually in the executable statement, and wherein the complement characters indicate the untrusted data and the standard characters indicate the trusted data; b) using the standard characters to represent trusted characters and using the complement characters to represent untrusted characters, wherein the trusted characters are defined as component language code or developer code that is developer generated and wherein the untrusted characters are defined as any data that is input by said user; c) interleaving the encoded characters from the first source with the encoded characters from the second source to create the executable computer code for execution on a second computer processor residing on a second device, and comparing the characters using value comparison, wherein value comparison compares all of the bits of a character not including the sign bit; d) specifying security policies for the second computer processor by designating tokens in the language of the second computer processor to be either a sensitive token or an allowed token, wherein an allowed token is a token deemed trusted and a sensitive token is a token deemed untrusted; and e) using the second computer processor to parse the executable computer code created by matching the sensitive tokens using full comparison and matching the allowed tokens using value comparison, wherein full comparison compares all of the bits of the character including the sign bit. 18. The method as claimed in claim 13 , wherein each of the characters of the data comprises at least two bit representations. | 0.758621 |
8,209,321 | 12 | 13 | 12. The one or more computer-readable media of claim 11 , wherein identifying passages that are mapped to the matching set of semantic representations further comprises: ascertaining a location within the passages of the at least one document from which the semantic representations are derived; and appending a pointer to the semantic representations that indicates the locations within the passages, thereby facilitating navigation to an appropriate character string for inclusion in the emphasized region. | 12. The one or more computer-readable media of claim 11 , wherein identifying passages that are mapped to the matching set of semantic representations further comprises: ascertaining a location within the passages of the at least one document from which the semantic representations are derived; and appending a pointer to the semantic representations that indicates the locations within the passages, thereby facilitating navigation to an appropriate character string for inclusion in the emphasized region. 13. The one or more computer-readable media of claim 12 , wherein the location within the passages of the at least one document from which the semantic representations are derived comprises at least one of character positions or byte positions within the passages. | 0.93423 |
8,001,119 | 6 | 8 | 6. The method of claim 1 ,wherein the step of adaptively gathering information relevant to a current state of the information analysis task further comprises the step of adaptive information selection based on evolving analytic context persisted in the analytic action graph. | 6. The method of claim 1 ,wherein the step of adaptively gathering information relevant to a current state of the information analysis task further comprises the step of adaptive information selection based on evolving analytic context persisted in the analytic action graph. 8. The method of claim 6 , wherein the step of adaptive information selection based on evolving analytic context persisted in the analytic action graph further comprises the step of re-ranking previously persisted information in the analytic action graph when the analytic context evolves so as to identify previous information relevant to current analysis in non-linear investigations. | 0.827832 |
8,612,424 | 1 | 10 | 1. A computerized method for optimizing search result rankings through use of a game interface, the method comprising: electronically, via a processing device, receiving from a plurality of users, requests to engage in an electronic competition via a game interface; providing the game interface to a first user and a second user in response to the requests, the game interface presenting a plurality of search result sets and at least one textual search query to the first user and the second user, the plurality of search result sets indicative of possible search result sets based on the at least one textual search query wherein each search result set includes a plurality of search results; providing a game objective and game instructions to the first user and the second user via the game interface, wherein the game objective includes determining a most relevant result set from the plurality of search result sets for the at least one textual search query, the game instructions are for the first user and the second user to select at least one of the plurality of search result sets based on a competition criteria; electronically, via the processing device, receiving selection commands from the first user and the second user, the selection commands indicating a user selection of the at least one of the plurality of search result sets relative to the game objective; updating ranking data for search result data associated with the at least one textual search query and the plurality of search results in response to the selection commands; and determining an optimum ranking for the plurality of search results in response to a search request including the at least one textual search query using the updated ranking data. | 1. A computerized method for optimizing search result rankings through use of a game interface, the method comprising: electronically, via a processing device, receiving from a plurality of users, requests to engage in an electronic competition via a game interface; providing the game interface to a first user and a second user in response to the requests, the game interface presenting a plurality of search result sets and at least one textual search query to the first user and the second user, the plurality of search result sets indicative of possible search result sets based on the at least one textual search query wherein each search result set includes a plurality of search results; providing a game objective and game instructions to the first user and the second user via the game interface, wherein the game objective includes determining a most relevant result set from the plurality of search result sets for the at least one textual search query, the game instructions are for the first user and the second user to select at least one of the plurality of search result sets based on a competition criteria; electronically, via the processing device, receiving selection commands from the first user and the second user, the selection commands indicating a user selection of the at least one of the plurality of search result sets relative to the game objective; updating ranking data for search result data associated with the at least one textual search query and the plurality of search results in response to the selection commands; and determining an optimum ranking for the plurality of search results in response to a search request including the at least one textual search query using the updated ranking data. 10. The method of claim 1 wherein the game objective includes ranking the plurality of search result sets. | 0.805147 |
9,582,823 | 11 | 12 | 11. The system of claim 10 , further comprising: determining whether all of the tagged items selected during the single search event have identical metadata for the first type of metadata; determining a majority metadata in response to a determination that all of the tagged items selected during the single search event do not have identical metadata, the majority metadata being metadata that is commonly assigned to a majority of the tagged items selected during the single search event; and identifying the majority metadata as data with which to tag the untagged item. | 11. The system of claim 10 , further comprising: determining whether all of the tagged items selected during the single search event have identical metadata for the first type of metadata; determining a majority metadata in response to a determination that all of the tagged items selected during the single search event do not have identical metadata, the majority metadata being metadata that is commonly assigned to a majority of the tagged items selected during the single search event; and identifying the majority metadata as data with which to tag the untagged item. 12. The system of claim 11 , further comprising providing a notification to an administrator, the notification indicating that the majority metadata should be assigned to the untagged item. | 0.925998 |
9,031,379 | 1 | 7 | 1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. | 1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. 7. The device of claim 1 , wherein the device comprises one of a mobile device, a computer, a set-top-box, a telephone, a personal digital assistant, a server, a computing tablet, or combinations thereof. | 0.748768 |
8,032,830 | 7 | 9 | 7. The method of claim 3 , wherein annotating of the captured portion of the reference document further comprises: displaying the captured portion of the reference document to be annotated; receiving a first input from a user designating a first point in the captured portion of the reference document defining a corner of an annotation rectangle; receiving a second input from the user designating a second point in the captured portion of the reference document defining an opposite corner of the annotation rectangle; and annotating the captured portion of the reference document from the first point to the second point of the annotation rectangle when the second input is released. | 7. The method of claim 3 , wherein annotating of the captured portion of the reference document further comprises: displaying the captured portion of the reference document to be annotated; receiving a first input from a user designating a first point in the captured portion of the reference document defining a corner of an annotation rectangle; receiving a second input from the user designating a second point in the captured portion of the reference document defining an opposite corner of the annotation rectangle; and annotating the captured portion of the reference document from the first point to the second point of the annotation rectangle when the second input is released. 9. The method as recited in claim 7 , wherein if the user does not immediately release the second input, allowing the user to drag the second point to visually show a shape and a size of the annotation rectangle. | 0.879271 |
9,396,412 | 1 | 7 | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. 7. The method of claim 1 wherein determining the affinity score comprises linearly combining the similarity and additional similarities. | 0.880071 |
8,988,543 | 2 | 5 | 2. The method according to claim 1 , comprising displaying the captured image, and f) digital image filtering of the captured image including contrast enhancement, shadow compensation, unwarping and rotation of the captured image in order to obtain an artifact reduced image with a substantially horizontal text alignment, wherein the detection of the plurality of word blocks is based on the artifact reduced image; g) performing OCR within each word block to get its text content; h) assigning to each A-block an attribute; i) indicating the A-blocks in the display by a frame or a background color and displaying their attributes as overlays within the artifact reduced and displayed image for the selection of the keyword; j) the selection of the A-block containing the keyword being based on the displayed attribute of the keyword; and k) upon the selection of the A-block, displaying the text content of the selected A-block. | 2. The method according to claim 1 , comprising displaying the captured image, and f) digital image filtering of the captured image including contrast enhancement, shadow compensation, unwarping and rotation of the captured image in order to obtain an artifact reduced image with a substantially horizontal text alignment, wherein the detection of the plurality of word blocks is based on the artifact reduced image; g) performing OCR within each word block to get its text content; h) assigning to each A-block an attribute; i) indicating the A-blocks in the display by a frame or a background color and displaying their attributes as overlays within the artifact reduced and displayed image for the selection of the keyword; j) the selection of the A-block containing the keyword being based on the displayed attribute of the keyword; and k) upon the selection of the A-block, displaying the text content of the selected A-block. 5. The method according to claim 2 , wherein the keyword probability determination within (d) takes into account for each detected word contained in the word blocks a keyword probability parameter determined by a correlation with a database, the database containing words with a low probability and words with high probability, and whereupon the word blocks containing so calculated most likely keywords are preselected as A-blocks for the selection. | 0.858668 |
7,996,479 | 1 | 2 | 1. A method of controlling a system of monitoring messages in a network, the method comprising: a) receiving a message sent by a user of the network to one or more recipients; b) applying a weight to any text from any previous message that appears in the message; c) forming a measure of language content used in the message; d) storing the measure of the language content used in the message, and information identifying the sender of the message in one or more data stores; e) reporting the stored measure of the language content, and the stored information identifying the sender to an administrator of the system. | 1. A method of controlling a system of monitoring messages in a network, the method comprising: a) receiving a message sent by a user of the network to one or more recipients; b) applying a weight to any text from any previous message that appears in the message; c) forming a measure of language content used in the message; d) storing the measure of the language content used in the message, and information identifying the sender of the message in one or more data stores; e) reporting the stored measure of the language content, and the stored information identifying the sender to an administrator of the system. 2. A method as claimed in claim 1 , further comprising storing a timestamp for each message. | 0.858025 |
9,798,806 | 14 | 15 | 14. The system of claim 10 , further comprising logic operable to provide a query database with the first query terms and the second query terms. | 14. The system of claim 10 , further comprising logic operable to provide a query database with the first query terms and the second query terms. 15. The system of claim 14 , further comprising logic operable to generate at least one query suggestion from the query database in response to the current query. | 0.971816 |
7,761,433 | 2 | 3 | 2. The document processing method according to claim 1 , further comprising a restriction message displaying step of displaying a message for restricting an operation on the third document file generated as a result of importing of the first document file to which security information is added. | 2. The document processing method according to claim 1 , further comprising a restriction message displaying step of displaying a message for restricting an operation on the third document file generated as a result of importing of the first document file to which security information is added. 3. The document processing method according to claim 2 , wherein the restriction message displaying step displays a message indicating restriction of an operation on the third document file in accordance with the type of security information added to the first document file. | 0.918639 |
9,483,518 | 7 | 11 | 7. One or more computer-readable hardware storage devices storing instructions that, when executed by a processor, configure the processor to perform acts that generate a combined display of presented content and contextually-related search results, comprising: detecting a single search indication comprising an action performed by a user on a user device while media content is being presented via one or more of a webpage or a television program on the user device, wherein the single search indication A) captures, on the user device, media content being presented on the user device, B) defines a search scope corresponding to only a portion of the media content being presented, wherein the portion of the media content being presented comprises a region of content defined by the single search indication, C) includes a specific item of interest within the content being presented, and D) initiates a search related to the media content being presented; in response to detecting the single search indication, automatically obtaining contextual information related to the media content at or near detection of the single search indication; automatically communicating the contextual information at least to a remote search service that formulates a query based on the contextual information; and receiving one or more search results related to the obtained contextual information related to the media content; and modifying a display of the presented content on the user device, such that the one or more search results are presented on the user device with the content. | 7. One or more computer-readable hardware storage devices storing instructions that, when executed by a processor, configure the processor to perform acts that generate a combined display of presented content and contextually-related search results, comprising: detecting a single search indication comprising an action performed by a user on a user device while media content is being presented via one or more of a webpage or a television program on the user device, wherein the single search indication A) captures, on the user device, media content being presented on the user device, B) defines a search scope corresponding to only a portion of the media content being presented, wherein the portion of the media content being presented comprises a region of content defined by the single search indication, C) includes a specific item of interest within the content being presented, and D) initiates a search related to the media content being presented; in response to detecting the single search indication, automatically obtaining contextual information related to the media content at or near detection of the single search indication; automatically communicating the contextual information at least to a remote search service that formulates a query based on the contextual information; and receiving one or more search results related to the obtained contextual information related to the media content; and modifying a display of the presented content on the user device, such that the one or more search results are presented on the user device with the content. 11. The devices of claim 7 , wherein the contextual information comprises one or more of: text associated with the media content; an identifier of the media content; a time associated with the single search indication; metadata associated with the media content; a time associated with presentation of the media content; or a channel presenting the media content. | 0.672383 |
8,028,239 | 1 | 18 | 1. One or more tangible computer-readable media having computer-executable instructions for performing a method to determine one or more user interface elements to display for a user interface surface, the method comprising: receiving a definition of the user interface surface; receiving an indication of a current context with multiple current context factors, each current context factor having a possible set of management element definitions with an associated set of user interface element definitions for presentation on the user interface surface, wherein the possible sets of management element definitions comprise logic for retrieving data to be displayed on the user interface surface determining an intersection of the associated sets of user interface element definitions as a display set of user interface element definitions, the determining the intersection comprising, applying a first subtractive filter before querying a management element store for one or more interface elements, applying a second subtractive filter after querying the management element store, the second subtractive filter being associated with the management element store, and applying a third subtractive filter after receiving the definition of the user interface surface, the third subtractive filter being associated with the definition of the user interface surface; and displaying at least a portion of the display set of user interface element definitions on the user interface surface using the logic for retrieving data to be displayed on the user interface surface of the sets of management element definitions associated with the user interface element definitions. | 1. One or more tangible computer-readable media having computer-executable instructions for performing a method to determine one or more user interface elements to display for a user interface surface, the method comprising: receiving a definition of the user interface surface; receiving an indication of a current context with multiple current context factors, each current context factor having a possible set of management element definitions with an associated set of user interface element definitions for presentation on the user interface surface, wherein the possible sets of management element definitions comprise logic for retrieving data to be displayed on the user interface surface determining an intersection of the associated sets of user interface element definitions as a display set of user interface element definitions, the determining the intersection comprising, applying a first subtractive filter before querying a management element store for one or more interface elements, applying a second subtractive filter after querying the management element store, the second subtractive filter being associated with the management element store, and applying a third subtractive filter after receiving the definition of the user interface surface, the third subtractive filter being associated with the definition of the user interface surface; and displaying at least a portion of the display set of user interface element definitions on the user interface surface using the logic for retrieving data to be displayed on the user interface surface of the sets of management element definitions associated with the user interface element definitions. 18. The one or more tangible computer-readable media of claim 1 wherein the current context includes one or more of the following factors affecting which user interface element definitions are chosen for display: a user role factor, a management item type factor, and a category factor. | 0.900348 |
9,679,049 | 10 | 11 | 10. A method for providing visual suggestions for document classification via injection, comprising: obtaining clusters of unclassified documents; obtaining a set of reference documents, each reference document associated with a classification code; comparing one or more of the unclassified documents within one such cluster to the reference documents; identifying for the cluster, one or more of the reference documents that are similar to the compared unclassified documents; injecting the similar reference documents into the cluster; setting a threshold for a number of the similar reference documents to be injected into the cluster; displaying each of the similar reference documents in the cluster with a visual indicator representative of the associated classification code and further displaying the unclassified documents of the cluster; and providing a suggestion for classification for one of the unclassified documents within each cluster based on the visual indicators of the similar reference documents. | 10. A method for providing visual suggestions for document classification via injection, comprising: obtaining clusters of unclassified documents; obtaining a set of reference documents, each reference document associated with a classification code; comparing one or more of the unclassified documents within one such cluster to the reference documents; identifying for the cluster, one or more of the reference documents that are similar to the compared unclassified documents; injecting the similar reference documents into the cluster; setting a threshold for a number of the similar reference documents to be injected into the cluster; displaying each of the similar reference documents in the cluster with a visual indicator representative of the associated classification code and further displaying the unclassified documents of the cluster; and providing a suggestion for classification for one of the unclassified documents within each cluster based on the visual indicators of the similar reference documents. 11. The method according to claim 10 , further comprising: generating the reference set, comprising: obtaining a corpus of uncoded documents; determining a similarity between each of the uncoded documents in the corpus; identifying those uncoded documents that are dissimilar to the other uncoded documents in the corpus; assigning the classification codes to the dissimilar uncoded documents; and grouping the dissimilar uncoded documents with the assigned classification codes as the reference set. | 0.762808 |
9,229,544 | 1 | 3 | 1. A computer implemented method for processing content written in an application form by an electronic pen (e-pen), comprising: obtaining stroke data corresponding to content written in a plurality of fields of an application form; extracting words corresponding to the written content from the obtained stroke data; computing distance between each of the words and a plurality of fields of a template application form; assigning a confidence value to each of the words with respect to each of the plurality of fields based on a probability matrix obtained from normalization and filtering of an initial confidence matrix including the distance between each of the words and the plurality of fields of the template application form; computing distance between the extracted words corresponding to the written content; mapping each of the words to one of the plurality of fields based on the confidence value assigned to each of the words, distance between the plurality of fields of a template application form and the distance between the extracted words; and storing each of the words mapped to said corresponding one of the plurality of the fields in a database. | 1. A computer implemented method for processing content written in an application form by an electronic pen (e-pen), comprising: obtaining stroke data corresponding to content written in a plurality of fields of an application form; extracting words corresponding to the written content from the obtained stroke data; computing distance between each of the words and a plurality of fields of a template application form; assigning a confidence value to each of the words with respect to each of the plurality of fields based on a probability matrix obtained from normalization and filtering of an initial confidence matrix including the distance between each of the words and the plurality of fields of the template application form; computing distance between the extracted words corresponding to the written content; mapping each of the words to one of the plurality of fields based on the confidence value assigned to each of the words, distance between the plurality of fields of a template application form and the distance between the extracted words; and storing each of the words mapped to said corresponding one of the plurality of the fields in a database. 3. The method of claim 1 , further comprising: computing a skew angle associated with the obtained stroke data; and correcting skew errors associated with the obtained stroke data based on the computed skew angle. | 0.817637 |
9,026,518 | 1 | 4 | 1. A computer implemented method for clustering content according to similarity, the method comprising: receiving a set of features for a plurality of content items; calculating, by a processor, a distance matrix for the plurality of content items based on user navigation of at least some of the content items; labeling, by a processor, at least some of the content items as pairwise constraints based on the distance matrix; creating, by a processor, a boosted cluster by incorporating the pairwise constraints into a clustering algorithm; applying a pattern analysis to the boosted cluster; and modifying the boosted cluster based on relations identified by the pattern analysis. | 1. A computer implemented method for clustering content according to similarity, the method comprising: receiving a set of features for a plurality of content items; calculating, by a processor, a distance matrix for the plurality of content items based on user navigation of at least some of the content items; labeling, by a processor, at least some of the content items as pairwise constraints based on the distance matrix; creating, by a processor, a boosted cluster by incorporating the pairwise constraints into a clustering algorithm; applying a pattern analysis to the boosted cluster; and modifying the boosted cluster based on relations identified by the pattern analysis. 4. The method of claim 1 , wherein the set of features is in the form of a topic model built using latent Dirichlet allocation (LDA). | 0.680288 |
9,971,757 | 1 | 2 | 1. A syntax parsing apparatus based on preprocessing, the apparatus comprising a processor and a memory, wherein said processor comprising: a pattern chunk recognizing unit configured to receive a part-of-speech tagged sentence, recognize, from the received part-of-speech tagged sentence, a pre-defined syntax pattern, and generate, according to the recognized pre-defined syntax pattern, a recognized result; a basic noun phrase recognizing unit comprising a basic noun phrase statistics learning module configured to receive basic noun phrase (BNP) attachment corpuses, convert, based on a predetermined grammar, the received BNP attachment corpuses into learning corpuses by tagging basic noun phrases, classify, using a Finite State Transducer (FST), the learning corpuses with a parenthesis and a word, extract features from the classified learning corpuses, generate a BNP statistical model from the classified learning corpuses based on the extracted features, and store the generated BNP statistical model into the memory, and a statistics-based basic noun phrase recognizing module configured to receive the recognized result from the pattern chunk recognizing unit and the generated BNP statistical model from the memory, and recognize a BNP from an input sentence using the recognized result and the generated BNP statistical model; and a syntax parsing unit configured to receive the recognized result and the recognized BNP, parse a syntax of the input sentence based on the recognized result and the recognized BNP, and generate a syntax tree based on the parsed syntax. | 1. A syntax parsing apparatus based on preprocessing, the apparatus comprising a processor and a memory, wherein said processor comprising: a pattern chunk recognizing unit configured to receive a part-of-speech tagged sentence, recognize, from the received part-of-speech tagged sentence, a pre-defined syntax pattern, and generate, according to the recognized pre-defined syntax pattern, a recognized result; a basic noun phrase recognizing unit comprising a basic noun phrase statistics learning module configured to receive basic noun phrase (BNP) attachment corpuses, convert, based on a predetermined grammar, the received BNP attachment corpuses into learning corpuses by tagging basic noun phrases, classify, using a Finite State Transducer (FST), the learning corpuses with a parenthesis and a word, extract features from the classified learning corpuses, generate a BNP statistical model from the classified learning corpuses based on the extracted features, and store the generated BNP statistical model into the memory, and a statistics-based basic noun phrase recognizing module configured to receive the recognized result from the pattern chunk recognizing unit and the generated BNP statistical model from the memory, and recognize a BNP from an input sentence using the recognized result and the generated BNP statistical model; and a syntax parsing unit configured to receive the recognized result and the recognized BNP, parse a syntax of the input sentence based on the recognized result and the recognized BNP, and generate a syntax tree based on the parsed syntax. 2. The apparatus of claim 1 , said processor further comprising: a statistical model learning unit configured to learn a statistical model from a syntax structure attachment corpus and store, as a syntax parsing statistical model, the learned statistical model into the memory, wherein the syntax parsing unit is configured to parse the syntax of the input sentence based on the recognized result, the recognized BNP, and the syntax parsing statistical model stored in the memory. | 0.668508 |
9,342,665 | 1 | 7 | 1. A client computer for facilitating intellectual property rights compliance comprising: a hardware network module connectable to at least one first domain and at least one second domain; a processor operatively connected to the hardware network module; and a data-storage device operatively connected to the processor, the data-storage device storing instructions, the instructions being executable by the processor to provide an application for i) receiving a structured document from the first domain, the structured document having at least one content, a reference to at least one digital rights compliance (DRC) object located on at least one second domain, and application-specific instructions being executable by the application, the at least one DRC object being defined in a non-executable format and containing information indicative of intellectual property rights associated with the at least one content; and ii) executing the application-specific instructions to cause the application to: send at least one request to the at least one second domain for the at least one DRC object, receive the at least one DRC object from the at least one second domain, and present the at least one content in accordance with the at least one DRC object; wherein the application is configured to limit application instructions that the application is permitted to execute such that the application is compliant with a same-origin security policy that prohibits the application from executing application-specific instructions from any domain that is different from the first domain. | 1. A client computer for facilitating intellectual property rights compliance comprising: a hardware network module connectable to at least one first domain and at least one second domain; a processor operatively connected to the hardware network module; and a data-storage device operatively connected to the processor, the data-storage device storing instructions, the instructions being executable by the processor to provide an application for i) receiving a structured document from the first domain, the structured document having at least one content, a reference to at least one digital rights compliance (DRC) object located on at least one second domain, and application-specific instructions being executable by the application, the at least one DRC object being defined in a non-executable format and containing information indicative of intellectual property rights associated with the at least one content; and ii) executing the application-specific instructions to cause the application to: send at least one request to the at least one second domain for the at least one DRC object, receive the at least one DRC object from the at least one second domain, and present the at least one content in accordance with the at least one DRC object; wherein the application is configured to limit application instructions that the application is permitted to execute such that the application is compliant with a same-origin security policy that prohibits the application from executing application-specific instructions from any domain that is different from the first domain. 7. The client computer according to claim 1 wherein the application is further operable to display at least some of the information contained in the at least one DRC object. | 0.615556 |
8,364,666 | 6 | 10 | 6. A data analysis system for performing a data analysis task having an associated analysis context, the system comprising: a processor configured to define the analysis context associated with the data analysis task, wherein data items have a variable relevance in accordance with the context, and wherein data items are grouped together to form logical transactions conducted by a user over a predetermined time period; a network interface configured to receive the logical transactions exchanged over a communication network, wherein the logical transactions include a first data item type and a second data item type that is different from the first data item type; the processor configured to process the logical transactions with a set of prioritization rules to generate relevance scores that quantify a relevance of the logical transactions to the analysis context, wherein the relevance scores are assigned according to a common scale, and generate a prioritization of the logical transactions based on the relevance scores. | 6. A data analysis system for performing a data analysis task having an associated analysis context, the system comprising: a processor configured to define the analysis context associated with the data analysis task, wherein data items have a variable relevance in accordance with the context, and wherein data items are grouped together to form logical transactions conducted by a user over a predetermined time period; a network interface configured to receive the logical transactions exchanged over a communication network, wherein the logical transactions include a first data item type and a second data item type that is different from the first data item type; the processor configured to process the logical transactions with a set of prioritization rules to generate relevance scores that quantify a relevance of the logical transactions to the analysis context, wherein the relevance scores are assigned according to a common scale, and generate a prioritization of the logical transactions based on the relevance scores. 10. The system of claim 6 further comprising the processor configured to display the prioritization of the data items on a user interface. | 0.920962 |
9,813,366 | 17 | 18 | 17. An apparatus for providing music messaging comprising: a processor; a memory; a music messaging service software platform stored in the memory and when executed by the processor perform operations comprising; first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to exactly one vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; second program code operative to control access to the short snippet to a recipient of a music message note having a user account, and prompting the intended recipient to log into or create a user account; and third program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. | 17. An apparatus for providing music messaging comprising: a processor; a memory; a music messaging service software platform stored in the memory and when executed by the processor perform operations comprising; first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to exactly one vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; second program code operative to control access to the short snippet to a recipient of a music message note having a user account, and prompting the intended recipient to log into or create a user account; and third program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. 18. The music messaging software-as-a-service platform of claim 17 , further comprising program code operative to debit a user account balance of the sender in response to receipt of data indicating that the reference is selected by the intended recipient. | 0.867769 |
9,959,013 | 12 | 22 | 12. A family tree building system for implementing an interactive display of a family tree with family members and relationships between family members, the system comprising: a processor; a memory communicatively connected with and readable by the processor and containing instructions that, when executed by the processor, cause the system to: provide access to a data store of information at a social network website corresponding to one or more of a plurality of users of a social network website, the social network website operated at a system separate from the family tree building system that implements the display of a family tree, wherein access to the data store at the social network web site is through a user of both the family tree building system and the social network website, wherein that user provides information to the family tree building system in order for the family tree building system to access the separate social network website, and wherein the social network website comprises: a plurality of data nodes, each data node representing data relating to a corresponding one of the plurality of users, and a plurality of edges, each edge defining a connection between a corresponding pair of the nodes; determine whether the connection between a first node in the social network website, corresponding to a first user, and any one of a plurality of second nodes in the social network website, corresponding to other users, reflects a possible family relationship; display, in an order, user names for the other users corresponding to each of at least some of the second nodes; receive, from the first user and based on the displayed user names, a selection of at least one of the second nodes as representing a relative; receive, from the first user, data identifying the family relationship of the relative, represented by each of the selected second nodes; and arrange the first node and the selected second nodes accessed from the separate social networking website, as arranged nodes in a family tree, with the arranged nodes connected in the family tree according to the family relationship between the arranged nodes. | 12. A family tree building system for implementing an interactive display of a family tree with family members and relationships between family members, the system comprising: a processor; a memory communicatively connected with and readable by the processor and containing instructions that, when executed by the processor, cause the system to: provide access to a data store of information at a social network website corresponding to one or more of a plurality of users of a social network website, the social network website operated at a system separate from the family tree building system that implements the display of a family tree, wherein access to the data store at the social network web site is through a user of both the family tree building system and the social network website, wherein that user provides information to the family tree building system in order for the family tree building system to access the separate social network website, and wherein the social network website comprises: a plurality of data nodes, each data node representing data relating to a corresponding one of the plurality of users, and a plurality of edges, each edge defining a connection between a corresponding pair of the nodes; determine whether the connection between a first node in the social network website, corresponding to a first user, and any one of a plurality of second nodes in the social network website, corresponding to other users, reflects a possible family relationship; display, in an order, user names for the other users corresponding to each of at least some of the second nodes; receive, from the first user and based on the displayed user names, a selection of at least one of the second nodes as representing a relative; receive, from the first user, data identifying the family relationship of the relative, represented by each of the selected second nodes; and arrange the first node and the selected second nodes accessed from the separate social networking website, as arranged nodes in a family tree, with the arranged nodes connected in the family tree according to the family relationship between the arranged nodes. 22. The system of claim 12 , wherein the information provided by a user to the family tree building system in order for the family tree building system to access the separate social network website comprises login information of that user. | 0.868969 |
9,449,096 | 14 | 15 | 14. The computer system of claim 10 , wherein performing one or more iterations of Gibbs Sampling utilizing the initial values, further comprising program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to: perform a first iteration of Gibbs Sampling, wherein performing the first iteration assigns a first set of values as new values representing variables of the dataset; and perform a second iteration of Gibbs Sampling, wherein performing the second iteration assigns a second set of values as part of the new values representing variables of the dataset. | 14. The computer system of claim 10 , wherein performing one or more iterations of Gibbs Sampling utilizing the initial values, further comprising program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to: perform a first iteration of Gibbs Sampling, wherein performing the first iteration assigns a first set of values as new values representing variables of the dataset; and perform a second iteration of Gibbs Sampling, wherein performing the second iteration assigns a second set of values as part of the new values representing variables of the dataset. 15. The computer system of claim 14 , wherein the second set of values replaces a part of the first set of values. | 0.973252 |
8,201,080 | 1 | 4 | 1. A method for annotating a content data stream, comprising: receiving a content data stream; annotating a portion of an image representing a person in the content data stream with metadata that symbolically describes emotional information conveyed by the person, wherein the portion is a body part of the person; and outputting the content data stream augmented with non-textual annotations of the portion of the image representing the person having a requested modality for the interpretation or cognition of the annotated content, wherein the emotion information is conveyed by both the portion of the image and the non-textual annotations individually, wherein the non-textual annotations are configured to be detected and processed by a personal annotation output device receiving the outputted content data stream to output the portion of the image and output the non-textual annotations in the requested modality for the interpretation or cognition of the annotated content, wherein the requested modality is transmitted by the personal annotation output device. | 1. A method for annotating a content data stream, comprising: receiving a content data stream; annotating a portion of an image representing a person in the content data stream with metadata that symbolically describes emotional information conveyed by the person, wherein the portion is a body part of the person; and outputting the content data stream augmented with non-textual annotations of the portion of the image representing the person having a requested modality for the interpretation or cognition of the annotated content, wherein the emotion information is conveyed by both the portion of the image and the non-textual annotations individually, wherein the non-textual annotations are configured to be detected and processed by a personal annotation output device receiving the outputted content data stream to output the portion of the image and output the non-textual annotations in the requested modality for the interpretation or cognition of the annotated content, wherein the requested modality is transmitted by the personal annotation output device. 4. The method of claim 1 , further comprising rendering the non-textual annotations using a personal annotation output device which generates and outputs the non-textual annotations to an individual using said device. | 0.870833 |
8,271,473 | 8 | 12 | 8. The computer-implemented method of claim 1 , further comprising determining, for at least one of the created job listing pages, at least one keyword for inclusion in the created job listing page based on the respective base information. | 8. The computer-implemented method of claim 1 , further comprising determining, for at least one of the created job listing pages, at least one keyword for inclusion in the created job listing page based on the respective base information. 12. The computer-implemented method of claim 8 , wherein determining, for at least one of the created job listing pages, at least one keyword for inclusion in the created job listing page based on the respective base information comprises scanning the respective base information for possible keywords and comparing the possible keywords against a database of keywords. | 0.816783 |
7,496,497 | 5 | 6 | 5. A system to allow a user to select a web site home page in a desired language comprising: a processor in communication with a memory, said processor operable to execute code for: identifying within a web address request to said web site a directional information item by extracting from said request a site language cookie stored in said users access device; providing a web page associated with said web address to a second web site corresponding to said directional information item, wherein said second web site includes a language translator; translating information on said web page in accordance with said language translator; and returning said translated web page to said user. | 5. A system to allow a user to select a web site home page in a desired language comprising: a processor in communication with a memory, said processor operable to execute code for: identifying within a web address request to said web site a directional information item by extracting from said request a site language cookie stored in said users access device; providing a web page associated with said web address to a second web site corresponding to said directional information item, wherein said second web site includes a language translator; translating information on said web page in accordance with said language translator; and returning said translated web page to said user. 6. The system as recited in claim 5 , wherein said processor is further operable to execute code for: accessing a control table to determine a status of said web page; and accessing a version of said web page stored locally on said second site, when said status indicates said web page is locally stored and valid; otherwise obtaining a current version of said web page; and translating said obtained web page. | 0.501217 |
8,787,819 | 16 | 24 | 16. A non-transitory computer readable storage medium having embodied thereon instructions, the instructions being executable by a processor to perform a method for creating a forum, the method comprising: receiving a selection of a topic-based lesson from a plurality of topics of interest; providing an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. | 16. A non-transitory computer readable storage medium having embodied thereon instructions, the instructions being executable by a processor to perform a method for creating a forum, the method comprising: receiving a selection of a topic-based lesson from a plurality of topics of interest; providing an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. 24. The non-transitory computer readable storage medium of claim 16 , wherein the submissions are received as one of a binary answer, multiple choice, or vote based on the selected template type of discussion. | 0.502381 |
9,460,419 | 17 | 18 | 17. A method implemented by at least one computing device, the method comprising: receiving multiple different authoring inputs from an author of a document, the multiple different authoring inputs identifying author-specified portions of multiple different websites having unstructured data, the multiple different websites including a first website having a first author-specified portion with first unstructured data and a second website having a second author-specified portion with second unstructured data; obtaining a first pointer that links to the first author-specified portion of the first website; obtaining a second pointer that links to the second author-specified portion of the second website; storing the first pointer to the first author-specified portion of the first website and the second pointer to the second author-specified portion of the second website in a document in a cloud computing environment; receiving validation inputs from a validating user indicating that the document is a validated document, wherein the validation inputs include a correction to part of the document and the validated document includes the correction; storing the validated document in the cloud computing environment; detecting that the first unstructured data of the first author-specified portion of the first website is updated by the first website with updated first unstructured data and obtaining the updated first unstructured data from the first website; and detecting that the second unstructured data of the second author-specified portion of the second website is updated by the second website with updated second unstructured data and obtaining the updated second unstructured data from the second website; and when a user other than the author of the validated document accesses the validated document, automatically providing the updated first unstructured data and the updated second unstructured data to the user other than the author of the validated document. | 17. A method implemented by at least one computing device, the method comprising: receiving multiple different authoring inputs from an author of a document, the multiple different authoring inputs identifying author-specified portions of multiple different websites having unstructured data, the multiple different websites including a first website having a first author-specified portion with first unstructured data and a second website having a second author-specified portion with second unstructured data; obtaining a first pointer that links to the first author-specified portion of the first website; obtaining a second pointer that links to the second author-specified portion of the second website; storing the first pointer to the first author-specified portion of the first website and the second pointer to the second author-specified portion of the second website in a document in a cloud computing environment; receiving validation inputs from a validating user indicating that the document is a validated document, wherein the validation inputs include a correction to part of the document and the validated document includes the correction; storing the validated document in the cloud computing environment; detecting that the first unstructured data of the first author-specified portion of the first website is updated by the first website with updated first unstructured data and obtaining the updated first unstructured data from the first website; and detecting that the second unstructured data of the second author-specified portion of the second website is updated by the second website with updated second unstructured data and obtaining the updated second unstructured data from the second website; and when a user other than the author of the validated document accesses the validated document, automatically providing the updated first unstructured data and the updated second unstructured data to the user other than the author of the validated document. 18. The method of claim 17 , wherein the obtaining the updated first unstructured data from the first website and the obtaining the updated second unstructured data from the second website are performed responsive to the user other than the author accessing the validated document. | 0.727713 |
9,411,800 | 21 | 23 | 21. One or more storage devices comprising instructions that, responsive to being executed by a computing system, cause the computing system to: receive letters to initiate segmentation into a first letter set and a second letter set, each of the first and second letter sets comprising one or more of the letters; determine a statistical relationship between the first letter set and the second letter set; determine whether the statistical relationship satisfies a condition; responsive to satisfying the condition, add a word composed of the first letter set and the second letter set into a data store containing one or more words and one or more bigrams, each of the one or more words and one or more bigrams having associated count information, each of the one or more bigrams composed of a leading data word and one or more trailing data words, the word configured to be interpolated with at least one of the one or more bigrams in the data store to transform the word and the at least one of the more or more bigrams into a new bigram, and compute updated count information for the new bigram using a proportional adjustment based at least in part on a relationship between the word following a leading data word or preceding a trailing data word of a respective bigram of the one or more bigrams; and analyze received user generated content using the data store to predict text associated with the user generated content. | 21. One or more storage devices comprising instructions that, responsive to being executed by a computing system, cause the computing system to: receive letters to initiate segmentation into a first letter set and a second letter set, each of the first and second letter sets comprising one or more of the letters; determine a statistical relationship between the first letter set and the second letter set; determine whether the statistical relationship satisfies a condition; responsive to satisfying the condition, add a word composed of the first letter set and the second letter set into a data store containing one or more words and one or more bigrams, each of the one or more words and one or more bigrams having associated count information, each of the one or more bigrams composed of a leading data word and one or more trailing data words, the word configured to be interpolated with at least one of the one or more bigrams in the data store to transform the word and the at least one of the more or more bigrams into a new bigram, and compute updated count information for the new bigram using a proportional adjustment based at least in part on a relationship between the word following a leading data word or preceding a trailing data word of a respective bigram of the one or more bigrams; and analyze received user generated content using the data store to predict text associated with the user generated content. 23. One or more storage devices of claim 21 , wherein the instructions further comprise instructions that cause the computing system to: identify a set of bigrams from the one or more bigrams in the data store, each bigram of the set having the associated count information and including the second letter set as the leading data word; determine a delta value for a first bigram of the set; responsive to determining a positive delta value indicating a relationship between the first bigram of the set and the word, compute updated associated count information for the first bigram of the set; and create the new bigram to add into the data store, the new bigram composed of: the word as a leading data word of the new bigram and a trailing data word of the first bigram of the set as a trailing data word of the new bigram. | 0.585513 |
9,686,337 | 1 | 7 | 1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user. | 1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user. 7. The method of claim 1 , wherein the device of the user comprises: a smartphone; a computer; a digital music device; a tablet computer; or a television. | 0.856075 |
8,990,086 | 16 | 17 | 16. A recognition confidence measurement method comprising: extracting candidates by matching a phoneme string of a speech signal, extracted by a feature vector which is detected from the speech signal through normalization of a histogram, and phoneme strings of vocabularies registered in a predetermined dictionary; obtaining information about a distance between a phoneme string of the input speech signal and a phoneme string of a predetermined vocabulary, by a predetermined phoneme confusion matrix which sets the distance to be decreased in proportion to the increase of a matching degree between phonemes; extracting as candidates, the phoneme string of the vocabulary that has a higher similarity and that has a comparatively shorter distance from the speech signal, from a predetermined dictionary; estimating a lexical distance between the extracted candidates, the estimating of the lexical distance comprising performing a dynamic matching of a pair of candidates selected from the extracted candidates; and determining whether the speech signal is an in-vocabulary, based on the lexical distance, wherein the dynamic matching comprises: for each phoneme in a first candidate of the selected pair of candidates, determining as a first matching pair the phoneme in the first candidate and the corresponding phoneme in a second candidate of the selected pair of candidates and determining as a second matching pair the phoneme in the first candidate and a phoneme having an identical shape to the phoneme in the first candidate; wherein the estimating of the lexical distance further comprises: calculating a score for the pair of candidates; and estimating the lexical distance using the calculated score; wherein the calculating of the score calculates the score using the phoneme confusion matrix. | 16. A recognition confidence measurement method comprising: extracting candidates by matching a phoneme string of a speech signal, extracted by a feature vector which is detected from the speech signal through normalization of a histogram, and phoneme strings of vocabularies registered in a predetermined dictionary; obtaining information about a distance between a phoneme string of the input speech signal and a phoneme string of a predetermined vocabulary, by a predetermined phoneme confusion matrix which sets the distance to be decreased in proportion to the increase of a matching degree between phonemes; extracting as candidates, the phoneme string of the vocabulary that has a higher similarity and that has a comparatively shorter distance from the speech signal, from a predetermined dictionary; estimating a lexical distance between the extracted candidates, the estimating of the lexical distance comprising performing a dynamic matching of a pair of candidates selected from the extracted candidates; and determining whether the speech signal is an in-vocabulary, based on the lexical distance, wherein the dynamic matching comprises: for each phoneme in a first candidate of the selected pair of candidates, determining as a first matching pair the phoneme in the first candidate and the corresponding phoneme in a second candidate of the selected pair of candidates and determining as a second matching pair the phoneme in the first candidate and a phoneme having an identical shape to the phoneme in the first candidate; wherein the estimating of the lexical distance further comprises: calculating a score for the pair of candidates; and estimating the lexical distance using the calculated score; wherein the calculating of the score calculates the score using the phoneme confusion matrix. 17. A non-transitory medium comprising computer readable instructions implementing the method of claim 16 . | 0.875291 |
9,736,488 | 20 | 23 | 20. A computer system for transcoding a tile based video bitstream, the system comprising: a processor; and a non-transitory computer-readable storage medium storing computer program instructions, executed by the processor, the computer program instructions comprising instructions for: receiving a picture of an input video bitstream, the picture comprising a plurality of coding blocks partitioned into a plurality of tiles, each tile comprising tile rows of coding blocks; parsing the plurality of coding blocks of the picture in a tile scan order to produce a plurality of subsets of entropy coding state data, each subset of entropy coding state data associated with a corresponding tile row of coding blocks of each tile; generating a list of identified coding blocks in the tile scan order based on the parsing of the plurality of coding blocks, wherein the list of identified coding blocks includes a plurality of identifiers, each identifier associated with a corresponding first coding block of each tile row of coding blocks of each tile, each identifier indicating a position of the corresponding first coding block in the input video bitstream; storing the plurality of subsets of entropy coding state data and the list of identified coding blocks in a data repository, wherein each identifier of the list of identified coding locks is associated with a corresponding subset of entropy coding state data; parsing the same plurality of coding blocks of the picture in a raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a first portion of a parsed video bitstream, wherein the parsing the same plurality of coding blocks comprises: sorting the list of identified coding blocks into the raster scan order, wherein a sequence of tile rows in the raster scan order corresponds to a full row of coding blocks that spans the picture, and for each tile row in the full row of coding blocks that spans the picture: identifying a present identifier from the sorted list of identified coding blocks that corresponds to a present position in the input video bitstream, restoring a selected subset of entropy coding state data that corresponds to the present identifier, and decoding syntax elements of a set of coding blocks that correspond to a present tile row using the selected subset of entropy coding state data. | 20. A computer system for transcoding a tile based video bitstream, the system comprising: a processor; and a non-transitory computer-readable storage medium storing computer program instructions, executed by the processor, the computer program instructions comprising instructions for: receiving a picture of an input video bitstream, the picture comprising a plurality of coding blocks partitioned into a plurality of tiles, each tile comprising tile rows of coding blocks; parsing the plurality of coding blocks of the picture in a tile scan order to produce a plurality of subsets of entropy coding state data, each subset of entropy coding state data associated with a corresponding tile row of coding blocks of each tile; generating a list of identified coding blocks in the tile scan order based on the parsing of the plurality of coding blocks, wherein the list of identified coding blocks includes a plurality of identifiers, each identifier associated with a corresponding first coding block of each tile row of coding blocks of each tile, each identifier indicating a position of the corresponding first coding block in the input video bitstream; storing the plurality of subsets of entropy coding state data and the list of identified coding blocks in a data repository, wherein each identifier of the list of identified coding locks is associated with a corresponding subset of entropy coding state data; parsing the same plurality of coding blocks of the picture in a raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a first portion of a parsed video bitstream, wherein the parsing the same plurality of coding blocks comprises: sorting the list of identified coding blocks into the raster scan order, wherein a sequence of tile rows in the raster scan order corresponds to a full row of coding blocks that spans the picture, and for each tile row in the full row of coding blocks that spans the picture: identifying a present identifier from the sorted list of identified coding blocks that corresponds to a present position in the input video bitstream, restoring a selected subset of entropy coding state data that corresponds to the present identifier, and decoding syntax elements of a set of coding blocks that correspond to a present tile row using the selected subset of entropy coding state data. 23. The system of claim 20 , wherein the computer program instructions for parsing the same plurality of coding blocks of the picture in a raster scan order comprise computer program instructions for: sorting the list of identified coding blocks into the raster scan order; and copying entropy coding state data associated with each identified coding block from the data repository; for a full row of coding blocks that spans the picture: restoring entropy coding state data for a selected coding block from the sorted list of the identified coding blocks, the selected coding block having a position within the full row; and decoding syntax elements of coding blocks subsequent to the selected coding block that also have a position within the full row using the copied entropy coding state data of the selected coding block from the sorted list. | 0.73094 |
6,070,139 | 1 | 2 | 1. A speech recognition device, comprising: a data processing terminal, comprising: a speech input unit to receive sounds including speech and translate the received speech into digital form; a speech analyzer coupled to said speech input unit to generate voice feature parameters for the received digitized speech; and a speaker accommodation unit comprising: a first feature reference memory for storing pre-registered non-specific speaker feature information, a conversion rule generated in advance highlighting variations between previously stored specific speaker feature information and the pre-registered non-specific speaker feature information, and a feature converter for generating converted voice feature parameters received from said speech analyzer based on the conversion rule, and a speech recognition processor, comprising: a second feature reference memory for storing standard feature information corresponding to pre-registered phrases; a phrase detector to determine whether the converted voice feature parameters substantially match any pre-registered phrases in said second feature reference memory and generate phrase detection data in response thereto; and a comprehension controller coupled to said phrase detector to receive the phrase detection data, to recognize a meaning of the received speech based on the received phrase detection data, and to perform at least one of controlling an action and formulating an appropriate response responsive to the recognized meaning; wherein said data processing terminal transmits the converted voice feature parameters to said speech recognition processor which is in radio frequency communication with said data processing terminal to receive the converted voice feature parameters. | 1. A speech recognition device, comprising: a data processing terminal, comprising: a speech input unit to receive sounds including speech and translate the received speech into digital form; a speech analyzer coupled to said speech input unit to generate voice feature parameters for the received digitized speech; and a speaker accommodation unit comprising: a first feature reference memory for storing pre-registered non-specific speaker feature information, a conversion rule generated in advance highlighting variations between previously stored specific speaker feature information and the pre-registered non-specific speaker feature information, and a feature converter for generating converted voice feature parameters received from said speech analyzer based on the conversion rule, and a speech recognition processor, comprising: a second feature reference memory for storing standard feature information corresponding to pre-registered phrases; a phrase detector to determine whether the converted voice feature parameters substantially match any pre-registered phrases in said second feature reference memory and generate phrase detection data in response thereto; and a comprehension controller coupled to said phrase detector to receive the phrase detection data, to recognize a meaning of the received speech based on the received phrase detection data, and to perform at least one of controlling an action and formulating an appropriate response responsive to the recognized meaning; wherein said data processing terminal transmits the converted voice feature parameters to said speech recognition processor which is in radio frequency communication with said data processing terminal to receive the converted voice feature parameters. 2. The speech recognition processor of claim 1, wherein said data processing terminal includes a radio frequency transmitter coupled to said speaker accommodation unit to transmit the converted voice feature parameters to said speech recognition processor and wherein said speech recognition processor includes a complementary radio frequency receiver in radio frequency communication with said terminal transmitter to receive the converted voice feature parameters. | 0.52449 |
9,798,703 | 1 | 9 | 1. A document preparation system comprising: a computer processor; a taxonomy module including one or more taxonomies having one or more concepts; a document editor module that facilitates: tagging of one or more entries of a document with one or more tags based on the concepts to produce a tagged document, and generating, by the computer processor, an instance document from the tagged document, the instance document including code corresponding to the tagged one or more entries of the document; a document validation system that validates the generated instance document and generates a status indication corresponding to the code included in the instance document; a validation report processing module that associates the status indication with a specific source among the one or more tagged entries of the document according to the generated instance document; and a user interface module that identifies and facilitates editing the specific source among the one or more tagged entries of the document. | 1. A document preparation system comprising: a computer processor; a taxonomy module including one or more taxonomies having one or more concepts; a document editor module that facilitates: tagging of one or more entries of a document with one or more tags based on the concepts to produce a tagged document, and generating, by the computer processor, an instance document from the tagged document, the instance document including code corresponding to the tagged one or more entries of the document; a document validation system that validates the generated instance document and generates a status indication corresponding to the code included in the instance document; a validation report processing module that associates the status indication with a specific source among the one or more tagged entries of the document according to the generated instance document; and a user interface module that identifies and facilitates editing the specific source among the one or more tagged entries of the document. 9. The document preparation system of claim 1 , wherein the user interface facilitates navigation of the document to identify and edit the specific source among the one or more tagged entries of the document via autoscrolling the document to the one or more tagged entries. | 0.604348 |
10,042,935 | 11 | 14 | 11. An apparatus comprising: at least one processor; a memory storing instructions executable by the processor to perform operations comprising: identifying at least one style attribute associated with a first image in a design; receiving a first search query for a second image during editing of the design, the first search query including at least a first search term, wherein the first search query is received subsequent to identifying the at least one style attribute associated with the first image; generating, by the processor, a second search query for the second image by adding to the first search query at least one term that is based on the at least one style attribute associated with the first image; searching at least one database based on the second search query instead of the first search query to generate search results, wherein a first search result of the search results is ranked higher than a second search result of the search results based on a determination that the first search result more closely matches the at least one style attribute associated with the first image than the second search result, and wherein determining that the first search result more closely matches the at least one style attribute associated with the first image than the second search result comprises: generating a first hash value of one or more style attributes associated with the first search result; generating a second hash value of one or more style attributes associated with the second search result; generating a third hash value of the at least one style attribute associated with the first image; and determining that a first distance between the first hash value and the third hash value is less than a second distance between the second hash value and the third hash value; and outputting the search results, each search result indicating a respective image. | 11. An apparatus comprising: at least one processor; a memory storing instructions executable by the processor to perform operations comprising: identifying at least one style attribute associated with a first image in a design; receiving a first search query for a second image during editing of the design, the first search query including at least a first search term, wherein the first search query is received subsequent to identifying the at least one style attribute associated with the first image; generating, by the processor, a second search query for the second image by adding to the first search query at least one term that is based on the at least one style attribute associated with the first image; searching at least one database based on the second search query instead of the first search query to generate search results, wherein a first search result of the search results is ranked higher than a second search result of the search results based on a determination that the first search result more closely matches the at least one style attribute associated with the first image than the second search result, and wherein determining that the first search result more closely matches the at least one style attribute associated with the first image than the second search result comprises: generating a first hash value of one or more style attributes associated with the first search result; generating a second hash value of one or more style attributes associated with the second search result; generating a third hash value of the at least one style attribute associated with the first image; and determining that a first distance between the first hash value and the third hash value is less than a second distance between the second hash value and the third hash value; and outputting the search results, each search result indicating a respective image. 14. The apparatus of claim 11 , further comprising at least one network interface configured to receive the first search query from a computing device and to output the search results to the computing device. | 0.776824 |
9,569,178 | 5 | 6 | 5. The method of claim 1 , wherein the displaying the identity of each of the two or more streams application actors and the fusion recommendation occurs via a user interface. | 5. The method of claim 1 , wherein the displaying the identity of each of the two or more streams application actors and the fusion recommendation occurs via a user interface. 6. The method of claim 5 , wherein the user interface is part of a job execution design recommendation of a performance management system. | 0.964652 |
7,996,763 | 7 | 11 | 7. A method for assessing complexity levels of data representations, comprising: a computer processor obtaining a first document having information associated with a first data representation being used to model a concept and a second document having information associated with a second data representation being used to model the same concept; the computer processor prompting a user to provide individual element values for individual element objects contained in the data representation, individual attribute values for individual attribute objects contained in the data representation, and nesting values for nesting levels contained in the data representation; the computer processor inputting the element values, the attribute values, and the nesting values received from the user in a table of values; the computer processor analyzing structural components of the first document and the second document to assess a complexity score for the first data representation associated with the first document and a complexity score for the second data representation associated with the second document, wherein nesting levels of structural components in a respective document being analyzed and individual values assigned to different types of structural components in the respective document being analyzed are factored into computing the complexity score for the respective document, a customizable nesting value assigned to a nesting level being multiplied against all of the individual values of the structural components residing at the nesting level, the complexity score of the respective document being impacted by an attribute structural component of the respective document; and the computer processor determining which of the first data representation of the first document and the second data representation of the second document has a smaller complexity score, wherein the structural components comprise element objects and attribute objects, the element objects comprising a first element object having a first individual element value and a second element object having a second individual element value that is different than the first individual element value, wherein, to determine the complexity score for the respective document, the customizable nesting value of a nesting level for each element object within a respective data representation is multiplied against an element value for the element object and the customizable nesting value of the nesting level for each attribute object within the respective data representation is multiplied against an attribute value for the attribute object to determine complexity levels of the structural components of the respective data representation, the complexity levels of the structural components being aggregated. | 7. A method for assessing complexity levels of data representations, comprising: a computer processor obtaining a first document having information associated with a first data representation being used to model a concept and a second document having information associated with a second data representation being used to model the same concept; the computer processor prompting a user to provide individual element values for individual element objects contained in the data representation, individual attribute values for individual attribute objects contained in the data representation, and nesting values for nesting levels contained in the data representation; the computer processor inputting the element values, the attribute values, and the nesting values received from the user in a table of values; the computer processor analyzing structural components of the first document and the second document to assess a complexity score for the first data representation associated with the first document and a complexity score for the second data representation associated with the second document, wherein nesting levels of structural components in a respective document being analyzed and individual values assigned to different types of structural components in the respective document being analyzed are factored into computing the complexity score for the respective document, a customizable nesting value assigned to a nesting level being multiplied against all of the individual values of the structural components residing at the nesting level, the complexity score of the respective document being impacted by an attribute structural component of the respective document; and the computer processor determining which of the first data representation of the first document and the second data representation of the second document has a smaller complexity score, wherein the structural components comprise element objects and attribute objects, the element objects comprising a first element object having a first individual element value and a second element object having a second individual element value that is different than the first individual element value, wherein, to determine the complexity score for the respective document, the customizable nesting value of a nesting level for each element object within a respective data representation is multiplied against an element value for the element object and the customizable nesting value of the nesting level for each attribute object within the respective data representation is multiplied against an attribute value for the attribute object to determine complexity levels of the structural components of the respective data representation, the complexity levels of the structural components being aggregated. 11. The method of claim 7 , further comprising: outputting a result indicating which of the first data representation of the first document and the second data representation of the second document has the smaller complexity score. | 0.510593 |
8,554,696 | 8 | 14 | 8. An apparatus comprising: a memory operable to: store an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; and a processor operable to execute logic to: generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. | 8. An apparatus comprising: a memory operable to: store an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; and a processor operable to execute logic to: generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. 14. The apparatus of claim 8 , the processor further operable to: generate an ontology affinity matrix comprising a plurality of entries, each entry corresponding to a directional affinity of a term pair comprising a first term and a second term, the directional affinity comprising the probability that the second term appears in a document of the document set given that the first term appears in the document. | 0.708628 |
9,141,964 | 1 | 8 | 1. A computer-implemented method for generating an electronic content item, the method comprising: receiving, at a server, a request from a content sponsor to generate an electronic content item associated with a concept, wherein the electronic content item is of the form of a creative and being generated automatically by the server; automatically determining, by the server and based on the concept, an image for inclusion in the electronic content item, wherein the determining includes comparing the concept to a title associated with the image and/or metadata associated with the image; suggesting, by the server and based on the determining, presentation content to the content sponsor for inclusion in the electronic content item including presenting at least a portion of the determined image responsive to the received request; receiving, at the server and from the content sponsor, a selection from the suggested presentation content; automatically generating, at the server, the electronic content item for the content sponsor using the selection; associating one or more keywords with the electronic content item; and storing the electronic content item and the associated one or more keywords such that it may be retrieved in response to a user query received in the future upon comparison with the associated one or more keywords. | 1. A computer-implemented method for generating an electronic content item, the method comprising: receiving, at a server, a request from a content sponsor to generate an electronic content item associated with a concept, wherein the electronic content item is of the form of a creative and being generated automatically by the server; automatically determining, by the server and based on the concept, an image for inclusion in the electronic content item, wherein the determining includes comparing the concept to a title associated with the image and/or metadata associated with the image; suggesting, by the server and based on the determining, presentation content to the content sponsor for inclusion in the electronic content item including presenting at least a portion of the determined image responsive to the received request; receiving, at the server and from the content sponsor, a selection from the suggested presentation content; automatically generating, at the server, the electronic content item for the content sponsor using the selection; associating one or more keywords with the electronic content item; and storing the electronic content item and the associated one or more keywords such that it may be retrieved in response to a user query received in the future upon comparison with the associated one or more keywords. 8. The method of claim 1 , wherein the electronic content item comprises at least one of an email or a web page. | 0.859649 |
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