patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
8,082,493 | 11 | 18 | 11. The one or more machine-readable storage media of claim 7 , wherein the instructions include additional instructions which, when executed by one or more processors, further cause: generating a current node event based on a first node in the input document; generating a current operation event based on a first operation of the set of operations; for each node event in the plurality of node events, determining whether the node identified by the current operation event is the same as the node identified by the current node event. | 11. The one or more machine-readable storage media of claim 7 , wherein the instructions include additional instructions which, when executed by one or more processors, further cause: generating a current node event based on a first node in the input document; generating a current operation event based on a first operation of the set of operations; for each node event in the plurality of node events, determining whether the node identified by the current operation event is the same as the node identified by the current node event. 18. The one or more machine-readable storage media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause: after determining that the node identified by the current operation event is the same as the node identified by the current node event, determining the operation that is specified by the current operation event; and in response to determining that the operation that is specified by the current operation event is a deletion, generating a new operation event from the edit script without returning the current node event; wherein the node that is identified by the current node event is not included in the output document. | 0.66798 |
9,484,024 | 8 | 10 | 8. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instruction stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, based on past interactions with a user participating in a dialog with a speech dialog system, an adaptation schema which, when applied to a speech recognition model, increases a likelihood the speech recognition model will recognize misrecognized speech from the user relative to an unadapted speech recognition model; determining that the user has previously repeated speech inputs based on interactions with the user prior to initiating the dialog, to yield a determination; and adapting, based on the determination, the speech recognition model using the adaptation schema before an expected repeat speech input, wherein adapting the speech recognition model further comprises modifying an acoustic model, a language model, and a semantic model. | 8. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instruction stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, based on past interactions with a user participating in a dialog with a speech dialog system, an adaptation schema which, when applied to a speech recognition model, increases a likelihood the speech recognition model will recognize misrecognized speech from the user relative to an unadapted speech recognition model; determining that the user has previously repeated speech inputs based on interactions with the user prior to initiating the dialog, to yield a determination; and adapting, based on the determination, the speech recognition model using the adaptation schema before an expected repeat speech input, wherein adapting the speech recognition model further comprises modifying an acoustic model, a language model, and a semantic model. 10. The system of claim 8 , wherein adapting the speech recognition model further comprises preparing a personalized search speech recognition model for the expected repeat speech input based on a usage history of the user and entries in a recognition lattice. | 0.748062 |
7,680,767 | 1 | 4 | 1. A method for providing data services to an application, comprising acts of: providing data services by a computing platform, which allow an application to access and update data in a database, wherein providing data services comprises: generating a query view that expresses at least a portion of an application schema associated with said application in terms of a database schema associated with said database; generating an update view that expresses at least a portion of said database schema in terms of said application schema; in response to a query request from the application requesting access to data, processing the query request by utilizing said query view to query said database on behalf of said requesting application; in response to an update request from the application requesting an update to data, processing the update request by utilizing said update view to update said database on behalf of said requesting application. | 1. A method for providing data services to an application, comprising acts of: providing data services by a computing platform, which allow an application to access and update data in a database, wherein providing data services comprises: generating a query view that expresses at least a portion of an application schema associated with said application in terms of a database schema associated with said database; generating an update view that expresses at least a portion of said database schema in terms of said application schema; in response to a query request from the application requesting access to data, processing the query request by utilizing said query view to query said database on behalf of said requesting application; in response to an update request from the application requesting an update to data, processing the update request by utilizing said update view to update said database on behalf of said requesting application. 4. The method of claim 1 , further comprising receiving, from said requesting application, an expression in a Data Manipulation Language (DML), said expression comprising data for use in updating said database. | 0.755814 |
7,483,973 | 1 | 12 | 1. A method for managing state data of a service in a service-oriented architecture by establishing a gateway for service-oriented state comprising: configuring an extensible, pluggable interface to support for extensible processor interfaces; data query support on service state data, automated notification capability on service state to a client; and automated data transform on service state data to a client format; defining an interface framework for interaction between a service and said gateway; establishing an extensible meta-data definition comprising an extensible set of service state data attributes including state data qualifiers, constraints, and access mechanisms; and utilizing one or more pluggable processors configured to utilize said extensible meta-data definition for interfaces and decision making based on said meta-data; wherein said extensible data query support on service state data includes: enabling a service developer to define a query type based on a state data schema definition; enabling a service user to send a state data query and query type to said service and transmitting said state data query and query type to a service state query processor; wherein said service state query processor evaluates said query and informs said gateway with state data information to facilitate processing said query and said gateway retrieves said state data information using meta-data information of said service state data; wherein said state data information is converted to a canonical data format to facilitate comprehension by said service query processor; wherein said query processor conducts said query on said service state data; and wherein query results are sent back to said client in a format as requested using a transformation processor. | 1. A method for managing state data of a service in a service-oriented architecture by establishing a gateway for service-oriented state comprising: configuring an extensible, pluggable interface to support for extensible processor interfaces; data query support on service state data, automated notification capability on service state to a client; and automated data transform on service state data to a client format; defining an interface framework for interaction between a service and said gateway; establishing an extensible meta-data definition comprising an extensible set of service state data attributes including state data qualifiers, constraints, and access mechanisms; and utilizing one or more pluggable processors configured to utilize said extensible meta-data definition for interfaces and decision making based on said meta-data; wherein said extensible data query support on service state data includes: enabling a service developer to define a query type based on a state data schema definition; enabling a service user to send a state data query and query type to said service and transmitting said state data query and query type to a service state query processor; wherein said service state query processor evaluates said query and informs said gateway with state data information to facilitate processing said query and said gateway retrieves said state data information using meta-data information of said service state data; wherein said state data information is converted to a canonical data format to facilitate comprehension by said service query processor; wherein said query processor conducts said query on said service state data; and wherein query results are sent back to said client in a format as requested using a transformation processor. 12. The method of claim 1 wherein said flexible meta-model definition supports different versions of meta-data and enables consistency across meta-data modeling. | 0.908834 |
10,013,480 | 11 | 12 | 11. The system of claim 9 , at least one edge of the plurality representing more than one transition of the plurality. | 11. The system of claim 9 , at least one edge of the plurality representing more than one transition of the plurality. 12. The system of claim 11 , the instructions further comprising instructions to: assign a weight to each edge between the two buckets of the first plurality, the weight representing a volume of transitions between the two buckets. | 0.927175 |
8,019,750 | 30 | 31 | 30. The system as recited in claim 26 , wherein the processor determines a cost associated with using the tuned database query. | 30. The system as recited in claim 26 , wherein the processor determines a cost associated with using the tuned database query. 31. The system as recited in claim 30 , wherein the processor compares a cost associated with using the selected database query to the cost associated with using the tuned database query. | 0.92735 |
8,226,416 | 3 | 32 | 3. A non-transitory computer readable medium containing an executable program for recognizing an utterance spoken by a reader, where the program performs the steps of: receiving text comprising one or more words to be read by the reader; generating a grammar for speech recognition, in accordance with the text; inserting at least one reading learner grammar feature into the grammar, wherein the at least one reading learner grammar feature comprises a recognition of at least one reading learner mistake; receiving the utterance; interpreting the utterance in accordance with the grammar; and outputting feedback indicative of reader performance. | 3. A non-transitory computer readable medium containing an executable program for recognizing an utterance spoken by a reader, where the program performs the steps of: receiving text comprising one or more words to be read by the reader; generating a grammar for speech recognition, in accordance with the text; inserting at least one reading learner grammar feature into the grammar, wherein the at least one reading learner grammar feature comprises a recognition of at least one reading learner mistake; receiving the utterance; interpreting the utterance in accordance with the grammar; and outputting feedback indicative of reader performance. 32. The non-transitory computer readable medium of claim 3 , wherein the text is received from a remote computing device. | 0.76087 |
9,390,197 | 27 | 30 | 27. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from the first activity data; and if a match for the user identifier is not identified in the social graph, performing a deterministic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, and behavioral patterns. | 27. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from the first activity data; and if a match for the user identifier is not identified in the social graph, performing a deterministic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, and behavioral patterns. 30. The method of claim 27 comprising: when the sender sends the message to the first recipient and a second recipient, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a first amount; and when the sender sends the message to only the first recipient and no other recipients, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a second amount, wherein the second amount is greater than the first amount. | 0.515817 |
8,477,095 | 16 | 20 | 16. A method comprising: loading audio content corresponding to printed material into a pen based computer, wherein said audio content comprises audio speech of a plurality of textual words contained in said printed material; accessing an activation of a control input to said pen based computer; and responsive to said activation, producing audio output corresponding to said printed material, wherein said printed material is a book comprising pages and wherein further said audio output corresponds to textual words of said pages, wherein said pen based computer is configured to selectively produce audio output corresponding to a single word of said textual words or produce audio output corresponding to more than one consecutive word of said textual words responsive to an operational parameter of said pen-based computer, wherein said operational parameter may be changed by said control input to said pen-based computer. | 16. A method comprising: loading audio content corresponding to printed material into a pen based computer, wherein said audio content comprises audio speech of a plurality of textual words contained in said printed material; accessing an activation of a control input to said pen based computer; and responsive to said activation, producing audio output corresponding to said printed material, wherein said printed material is a book comprising pages and wherein further said audio output corresponds to textual words of said pages, wherein said pen based computer is configured to selectively produce audio output corresponding to a single word of said textual words or produce audio output corresponding to more than one consecutive word of said textual words responsive to an operational parameter of said pen-based computer, wherein said operational parameter may be changed by said control input to said pen-based computer. 20. The method of claim 16 wherein said audio output comprises spoken word output corresponding to a word in said printed material. | 0.662371 |
8,713,485 | 11 | 14 | 11. A non-transitory computer readable storage medium having instructions stored thereon which, when executed, cause a processor to perform the following operations: receiving, from a design rule checker, two or more of violations of a design rule within an integrated circuit (IC) layout, each violation having an error marker and the IC layout having two or more cells; determining dynamically a local region for each of the violations wherein the local region is in a first cell, the violation is associated with a particular cell adjacent to the first cell, and the parameters associated with the local region include an identification parameter of the adjacent cell, wherein the adjacent cell includes the violation; and for each of the violations: determining one or more parameters associated with the local region, wherein the parameters include the identification parameter associated with a cell associated with the design rule violation, the identification parameter including at least that the cell associated with the design rule violation is an instance of a particular parent cell, and dynamically classifying the violation as being in a particular error category when the associated parameters are substantially similar to corresponding parameters for the error category. | 11. A non-transitory computer readable storage medium having instructions stored thereon which, when executed, cause a processor to perform the following operations: receiving, from a design rule checker, two or more of violations of a design rule within an integrated circuit (IC) layout, each violation having an error marker and the IC layout having two or more cells; determining dynamically a local region for each of the violations wherein the local region is in a first cell, the violation is associated with a particular cell adjacent to the first cell, and the parameters associated with the local region include an identification parameter of the adjacent cell, wherein the adjacent cell includes the violation; and for each of the violations: determining one or more parameters associated with the local region, wherein the parameters include the identification parameter associated with a cell associated with the design rule violation, the identification parameter including at least that the cell associated with the design rule violation is an instance of a particular parent cell, and dynamically classifying the violation as being in a particular error category when the associated parameters are substantially similar to corresponding parameters for the error category. 14. The storage medium of claim 11 , wherein the parameters associated with the local region includes a geometric parameter. | 0.820809 |
8,280,924 | 1 | 8 | 1. In a computing network at which data is made available from a variety of different sources and in a variety of different data types and formats, a computer-implemented method for use at a computer system having a processor and memory, and which is running a database application configured to communicate with a database using at least one of a variety of different database schemas, the computer-implemented method facilitating the ability of the database application to more easily use the data from the variety of different sources, and comprising: receiving at the database application input data from a database; instantiating at the database application a metadata inferring module that infers object relational mapping (ORM) metadata for one or more database objects of the received input data, the ORM metadata inferred from at least one of the database schemas that the database application is configured to use, the inferred ORM metadata including an indication of database object properties and database schema settings associated with one or more database objects of the received input data, thereby allowing the database application to implement ORM capabilities to retrieve and access information from the database; instantiating at the database application an object relational mapping (ORM) query module configured to use ORM metadata to generate information that is used to generate an object graph, the ORM query module processing the ORM metadata for the one or more database objects of the received input data; instantiating an object graph generator and, using the information derived by the ORM query module after processing the ORM metadata, the object graph generator then mapping the one or more database objects of the input data into a graph of objects which enables the mapped one or more database objects to be sent to another application or to be subsequently displayed in an ORM object view. | 1. In a computing network at which data is made available from a variety of different sources and in a variety of different data types and formats, a computer-implemented method for use at a computer system having a processor and memory, and which is running a database application configured to communicate with a database using at least one of a variety of different database schemas, the computer-implemented method facilitating the ability of the database application to more easily use the data from the variety of different sources, and comprising: receiving at the database application input data from a database; instantiating at the database application a metadata inferring module that infers object relational mapping (ORM) metadata for one or more database objects of the received input data, the ORM metadata inferred from at least one of the database schemas that the database application is configured to use, the inferred ORM metadata including an indication of database object properties and database schema settings associated with one or more database objects of the received input data, thereby allowing the database application to implement ORM capabilities to retrieve and access information from the database; instantiating at the database application an object relational mapping (ORM) query module configured to use ORM metadata to generate information that is used to generate an object graph, the ORM query module processing the ORM metadata for the one or more database objects of the received input data; instantiating an object graph generator and, using the information derived by the ORM query module after processing the ORM metadata, the object graph generator then mapping the one or more database objects of the input data into a graph of objects which enables the mapped one or more database objects to be sent to another application or to be subsequently displayed in an ORM object view. 8. The method of claim 1 , further comprising: an act of determining that at least a portion of schema settings in the database have been updated; and an act of invalidating a displayed ORM object view based on the determination that schema settings in the database have been updated. | 0.626316 |
9,251,206 | 17 | 19 | 17. A hardware computer readable storage device encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: selecting one or more query pairs of queries from user sessions, each query pair being a first query and a second query that were submitted as separately during a search session with up to a maximum number of intervening queries between the first query and the second query, each first and second query including at least one term; for each query pair: selecting one or more term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each selected term pair, wherein the co-occurrence value is based at least in part on terms included in a first query that are also included in a second query; aggregating the co-occurrence values determined for each selected term pair over all selected query pairs; for each unique term pair of the selected term pairs, determining a probability that the unique term pair co-occurs; determining a transition cost based on the probability that the unique term pair co-occurs and an edit distance indicating similarity between the first term and the second term, the transition cost indicative of a cost of transitioning from the first term in the first query to the second term in the second query; normalizing the transition cost; and storing the normalized transition cost in a cost-matrix. | 17. A hardware computer readable storage device encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: selecting one or more query pairs of queries from user sessions, each query pair being a first query and a second query that were submitted as separately during a search session with up to a maximum number of intervening queries between the first query and the second query, each first and second query including at least one term; for each query pair: selecting one or more term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each selected term pair, wherein the co-occurrence value is based at least in part on terms included in a first query that are also included in a second query; aggregating the co-occurrence values determined for each selected term pair over all selected query pairs; for each unique term pair of the selected term pairs, determining a probability that the unique term pair co-occurs; determining a transition cost based on the probability that the unique term pair co-occurs and an edit distance indicating similarity between the first term and the second term, the transition cost indicative of a cost of transitioning from the first term in the first query to the second term in the second query; normalizing the transition cost; and storing the normalized transition cost in a cost-matrix. 19. The computer readable storage device of claim 17 , wherein the operations further comprise: for each unique term pair: the normalizing the transition cost being based on at least one of a probability that a first term of the unique term pair co-occurs with any query and a probability that a second term of the unique term pair co-occurs with any query. | 0.742424 |
8,938,384 | 11 | 16 | 11. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages, wherein the plurality of languages belong to a plurality of disjoint subsets, wherein any two languages that are in different disjoint subsets do not overlap with each other; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, segments a test document into one or more segments of consecutive characters, wherein each segment contains n-grams that have greater than a default probability of occurrence only for languages in a same one of the plurality of disjoint subsets, and further generates a set of segment scores for the test document, wherein the set of segment scores includes a score for each one of the segments scored against each one of the language models in the one of the plurality of disjoint subsets applicable to that segment; and a second process that, when executed, identifies one or more of the plurality of languages as being languages of the documents based on the set of segment scores. | 11. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages, wherein the plurality of languages belong to a plurality of disjoint subsets, wherein any two languages that are in different disjoint subsets do not overlap with each other; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, segments a test document into one or more segments of consecutive characters, wherein each segment contains n-grams that have greater than a default probability of occurrence only for languages in a same one of the plurality of disjoint subsets, and further generates a set of segment scores for the test document, wherein the set of segment scores includes a score for each one of the segments scored against each one of the language models in the one of the plurality of disjoint subsets applicable to that segment; and a second process that, when executed, identifies one or more of the plurality of languages as being languages of the documents based on the set of segment scores. 16. The system of claim 11 wherein two languages do not overlap with each other in the event that the respective n-gram based language models for the two languages have no n-grams in common. | 0.860294 |
7,613,719 | 22 | 31 | 22. A method of displaying information retrieved from a data source stored on a computer storage medium, comprising: receiving a first natural language input from a user; analyzing the first natural language input to identify semantic information contained therein; associating portions of the first natural language input with a command object, a frame object and an entity object of a schema based on the semantic information and the first natural language input; displaying a table of columns and rows to the user illustrating data retrieved from the data source as a function of the command object, the frame object and the entity object; receiving a second natural language input from the user referring to the table of columns and rows; altering the schema based on the second natural language input; and modifying the arrangement of the previously displayed data in the table as a function of the altered schema and displaying the newly arranged data in a modified table to the user. | 22. A method of displaying information retrieved from a data source stored on a computer storage medium, comprising: receiving a first natural language input from a user; analyzing the first natural language input to identify semantic information contained therein; associating portions of the first natural language input with a command object, a frame object and an entity object of a schema based on the semantic information and the first natural language input; displaying a table of columns and rows to the user illustrating data retrieved from the data source as a function of the command object, the frame object and the entity object; receiving a second natural language input from the user referring to the table of columns and rows; altering the schema based on the second natural language input; and modifying the arrangement of the previously displayed data in the table as a function of the altered schema and displaying the newly arranged data in a modified table to the user. 31. The method of claim 22 wherein the second natural language input relates to switching the row and column information. | 0.891964 |
8,682,907 | 26 | 30 | 26. The computer-readable medium of claim 25 , wherein computing a score for the second term comprises: computing respective changes in co-occurrence frequency between corresponding elements of the first vector and the second vector; generating an order of co-occurring terms according to the corresponding computed changes in co-occurrence frequency; and computing a measure of importance of a top number of co-occurring terms in the order. | 26. The computer-readable medium of claim 25 , wherein computing a score for the second term comprises: computing respective changes in co-occurrence frequency between corresponding elements of the first vector and the second vector; generating an order of co-occurring terms according to the corresponding computed changes in co-occurrence frequency; and computing a measure of importance of a top number of co-occurring terms in the order. 30. The computer-readable medium of claim 26 , wherein the measure of importance for a term x is based on frequencies of terms that co-occur with the term in received search queries, and is given by: imp ( x ) = 1 - ∑ i = 1 k H i · DF ( Term i ) , wherein H i is a co-occurrence frequency value for Term i and DF(Term i ) is a document frequency value of Term i . | 0.846633 |
7,519,566 | 29 | 42 | 29. A computer program product embedded in a computer memory for updating at least one prediction model for use by at least one interactive server, wherein each interactive server performs a plurality of actions in the context of a plurality of input attribute values of an input dataset and wherein the actions are selected based on each prediction model, the computer program product comprising: (a) code for automatically and continually obtaining contextual data from the interactive server as it performs the plurality of actions, wherein the contextual data indicates at least which action was performed, which input attribute values are present for each action that was performed, and which outcome is achieved for each action was performed; (b) code for automatically and continually updating a learning model based on all of the obtained contextual data, wherein the learning model predicts a probability of each of a plurality of specific outcomes occurring for each of a plurality of specific actions being performed by the interactive server when specific combinations of one or more input attribute values are present, wherein the updating of the learning model is based on counts of each attribute value as it is present along with each of the other attribute values; (c) code for generating an updated prediction model, wherein generating comprises, determining a correlation between one or more values of input attributes and a target of prediction, comparing the correlation with a threshold, eliminating each value of input attributes from the input dataset if the value of input attribute fails to satisfy the threshold, and in response to eliminating, generating the updated prediction model based on the input dataset; (d) code for generating a prediction of a probability of an outcome using the updated prediction model; (e) code for selecting an action of the plurality of actions based on the prediction; and (f) code for performing the action, wherein operations (b) and (c) are performed each time condition is met, the condition being selected from a group consisting of (i) a predetermined level of contextual data has been obtained, (ii) a predetermined number of actions have been performed, (iii) a predetermine time period has expired, and (iv) a number of new input attributes from the collected contextual data has reached a predetermined percentage of a total number of the attributes or a predetermined minimum number of new input attributes has been reached. | 29. A computer program product embedded in a computer memory for updating at least one prediction model for use by at least one interactive server, wherein each interactive server performs a plurality of actions in the context of a plurality of input attribute values of an input dataset and wherein the actions are selected based on each prediction model, the computer program product comprising: (a) code for automatically and continually obtaining contextual data from the interactive server as it performs the plurality of actions, wherein the contextual data indicates at least which action was performed, which input attribute values are present for each action that was performed, and which outcome is achieved for each action was performed; (b) code for automatically and continually updating a learning model based on all of the obtained contextual data, wherein the learning model predicts a probability of each of a plurality of specific outcomes occurring for each of a plurality of specific actions being performed by the interactive server when specific combinations of one or more input attribute values are present, wherein the updating of the learning model is based on counts of each attribute value as it is present along with each of the other attribute values; (c) code for generating an updated prediction model, wherein generating comprises, determining a correlation between one or more values of input attributes and a target of prediction, comparing the correlation with a threshold, eliminating each value of input attributes from the input dataset if the value of input attribute fails to satisfy the threshold, and in response to eliminating, generating the updated prediction model based on the input dataset; (d) code for generating a prediction of a probability of an outcome using the updated prediction model; (e) code for selecting an action of the plurality of actions based on the prediction; and (f) code for performing the action, wherein operations (b) and (c) are performed each time condition is met, the condition being selected from a group consisting of (i) a predetermined level of contextual data has been obtained, (ii) a predetermined number of actions have been performed, (iii) a predetermine time period has expired, and (iv) a number of new input attributes from the collected contextual data has reached a predetermined percentage of a total number of the attributes or a predetermined minimum number of new input attributes has been reached. 42. A computer program product as recited in claim 29 , further comprising code for publishing the prediction model to the interactive server. | 0.869963 |
9,069,753 | 6 | 9 | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving Pinyin inputs; converting the Pinyin inputs to corresponding candidates, each of the corresponding candidates comprising one or more Hanzi characters; receiving rates of user selections for each of the corresponding candidates, the rates indicating how often users select each of the corresponding candidates; identifying, from the received rates, Pinyin inputs converted to candidates having low rates of user selection as non-selected Pinyin inputs; identifying, from the received rates, Pinyin inputs converted to candidates having higher rates of user selection than the non-selected Pinyin inputs, as intended Pinyin inputs; comparing the intended Pinyin inputs to the non-selected Pinyin inputs to identify one or more-non-selected Pinyin input and intended Pinyin input pairs; for each non-selected Pinyin input, determining a number of times that users did not select from the corresponding candidates and a number of times the non-selected Pinyin input was entered as input by users; and generating a proximity measurement for each-non-selected Pinyin input and intended Pinyin input pair based on a ratio of the number of times the corresponding candidates were not selected by users to the number of times the non-selected Pinyin input was entered as input by users. | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving Pinyin inputs; converting the Pinyin inputs to corresponding candidates, each of the corresponding candidates comprising one or more Hanzi characters; receiving rates of user selections for each of the corresponding candidates, the rates indicating how often users select each of the corresponding candidates; identifying, from the received rates, Pinyin inputs converted to candidates having low rates of user selection as non-selected Pinyin inputs; identifying, from the received rates, Pinyin inputs converted to candidates having higher rates of user selection than the non-selected Pinyin inputs, as intended Pinyin inputs; comparing the intended Pinyin inputs to the non-selected Pinyin inputs to identify one or more-non-selected Pinyin input and intended Pinyin input pairs; for each non-selected Pinyin input, determining a number of times that users did not select from the corresponding candidates and a number of times the non-selected Pinyin input was entered as input by users; and generating a proximity measurement for each-non-selected Pinyin input and intended Pinyin input pair based on a ratio of the number of times the corresponding candidates were not selected by users to the number of times the non-selected Pinyin input was entered as input by users. 9. The computer storage medium of claim 6 , wherein the Pinyin inputs are inputs for search queries. | 0.89605 |
9,997,069 | 1 | 11 | 1. A method of providing context aware audible navigation prompts during a navigation presentation that an electronic device provides to offer guidance through a navigated route, the electronic device comprising a plurality of services utilizing audio, the electronic device audio played on a plurality of stereo speakers, the method comprising: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive a voice input; based on detecting that a first audio service is currently receiving the voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the voice input, determining that a non-verbal audio prompt is allowed; in response to determining that the non-verbal audio is allowed, suppressing verbal navigation prompts when a service in the plurality of services of the electronic device is being utilized to conduct the second audio service through the electronic device; determining that the electronic device has approached a juncture along the navigated route that requires a turn; playing a non-verbal audible prompt having a directional component that is defined for a particular direction of the next navigation turn when verbal navigation prompts are suppressed; and displaying a textual notification on the device describing the next navigation turn using textual instructions when verbal navigation prompts are suppressed. | 1. A method of providing context aware audible navigation prompts during a navigation presentation that an electronic device provides to offer guidance through a navigated route, the electronic device comprising a plurality of services utilizing audio, the electronic device audio played on a plurality of stereo speakers, the method comprising: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive a voice input; based on detecting that a first audio service is currently receiving the voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the voice input, determining that a non-verbal audio prompt is allowed; in response to determining that the non-verbal audio is allowed, suppressing verbal navigation prompts when a service in the plurality of services of the electronic device is being utilized to conduct the second audio service through the electronic device; determining that the electronic device has approached a juncture along the navigated route that requires a turn; playing a non-verbal audible prompt having a directional component that is defined for a particular direction of the next navigation turn when verbal navigation prompts are suppressed; and displaying a textual notification on the device describing the next navigation turn using textual instructions when verbal navigation prompts are suppressed. 11. The method of claim 1 , wherein playing the non-verbal prompt comprises panning the non-verbal prompt to a right speaker in the set of stereo speakers when the non-verbal prompt includes a right directional component. | 0.831555 |
8,843,847 | 1 | 6 | 1. A system configured to use HTML5 layout for rendering a native downloaded graphical user interface, the system comprising: a mobile communication device; a native downloadable application; a mobile web services API; a HTML 5 authoring tool utilized to create an application layout conformant with HTML5 standards and practices; a native application authoring tool utilized to develop the native downloadable application and comprising an HTML5 layout as a resource file in a process of building the native downloadable application whereby the HTML5 layout is embedded into the native downloadable application; and an application server comprising at least the native downloadable application; wherein the native downloadable application is downloaded from the application server over a network to the mobile communication device, the native downloadable application is configured to run on the mobile communication device and is configured to be displayed on the mobile communication device, the native downloadable application is configured to open a browser view within the native downloadable application on the mobile communication device when the native downloadable application is running and displayed on the mobile communication device, the browser view configured to execute the HTML5 layout as the graphical user interface of the native downloadable application and transmit a request for information to a server over a network, wherein the HTML 5 layout is part of the native downloadable application and operates with the native downloadable application, the native downloadable application configured to intercept the request for information, and the native downloadable application configured to satisfy the request from a plurality of resources included in a downloaded file, wherein a request made to one of a plurality of native downloadable application features supported in the mobile web services API is satisfied without going outside of the mobile communication device to a network, wherein an application content is presented in an HTML5 layout on the mobile communication device. | 1. A system configured to use HTML5 layout for rendering a native downloaded graphical user interface, the system comprising: a mobile communication device; a native downloadable application; a mobile web services API; a HTML 5 authoring tool utilized to create an application layout conformant with HTML5 standards and practices; a native application authoring tool utilized to develop the native downloadable application and comprising an HTML5 layout as a resource file in a process of building the native downloadable application whereby the HTML5 layout is embedded into the native downloadable application; and an application server comprising at least the native downloadable application; wherein the native downloadable application is downloaded from the application server over a network to the mobile communication device, the native downloadable application is configured to run on the mobile communication device and is configured to be displayed on the mobile communication device, the native downloadable application is configured to open a browser view within the native downloadable application on the mobile communication device when the native downloadable application is running and displayed on the mobile communication device, the browser view configured to execute the HTML5 layout as the graphical user interface of the native downloadable application and transmit a request for information to a server over a network, wherein the HTML 5 layout is part of the native downloadable application and operates with the native downloadable application, the native downloadable application configured to intercept the request for information, and the native downloadable application configured to satisfy the request from a plurality of resources included in a downloaded file, wherein a request made to one of a plurality of native downloadable application features supported in the mobile web services API is satisfied without going outside of the mobile communication device to a network, wherein an application content is presented in an HTML5 layout on the mobile communication device. 6. The system according to claim 1 wherein the HTML layout comprises HTML markup. | 0.820796 |
7,900,208 | 16 | 21 | 16. A non-transitory computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method for translating an incoming message into a native format, said method comprising: invoking each of a plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the incoming message; identifying, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the incoming message; upon a successful identification of the particular exchange protocol, decoding said incoming message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoking each of a plurality of extensible document protocol plug-ins to identify a particular document format protocol associated with the decoded message; identifying, by a particular one of said plurality of extensible document protocol plug ins, the particular document format protocol associated with the decoded message; upon a successful identification of the particular document format protocol, translating said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of said native format. | 16. A non-transitory computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method for translating an incoming message into a native format, said method comprising: invoking each of a plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the incoming message; identifying, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the incoming message; upon a successful identification of the particular exchange protocol, decoding said incoming message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoking each of a plurality of extensible document protocol plug-ins to identify a particular document format protocol associated with the decoded message; identifying, by a particular one of said plurality of extensible document protocol plug ins, the particular document format protocol associated with the decoded message; upon a successful identification of the particular document format protocol, translating said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of said native format. 21. A non-transitory computer-implemented storage medium as described in claim 16 , said method further comprising de-batching a plurality of incoming messages that includes said incoming message. | 0.866485 |
7,660,793 | 37 | 48 | 37. The system of claim 36 wherein the data store comprises a relational database in which at least a portion of the structured data is stored, and wherein the appliance further comprises a second data store in which at least a portion of the unstructured data is stored. | 37. The system of claim 36 wherein the data store comprises a relational database in which at least a portion of the structured data is stored, and wherein the appliance further comprises a second data store in which at least a portion of the unstructured data is stored. 48. The system of claim 37 wherein the processor is configured to execute API software to handle the received query. | 0.963727 |
8,131,728 | 1 | 2 | 1. A method for processing large relationship-specifying markup language documents, the method comprising: generating an index of nodes each node corresponding to a clause in the markup language document; processing the index in lieu of the markup language document; identifying clauses referenced within the index to be written to a database; and, extracting the identified clauses from the markup language document and writing the extracted clauses to the database. | 1. A method for processing large relationship-specifying markup language documents, the method comprising: generating an index of nodes each node corresponding to a clause in the markup language document; processing the index in lieu of the markup language document; identifying clauses referenced within the index to be written to a database; and, extracting the identified clauses from the markup language document and writing the extracted clauses to the database. 2. The method of claim 1 , wherein generating an index of nodes each node corresponding to a clause in the markup language document, comprises: reading small chunks of the markup language document into a rolling buffer; expression matching on the small chunks to identify individual clauses; and, responsive to identifying an individual clause in the rolling buffer, adding a node to the index with both an identifier for the individual clause and a position in the markup language document of the individual clause. | 0.708804 |
9,586,091 | 1 | 10 | 1. A method for a primary user exercising in communication with a remote secondary user, comprising the steps of: the primary user using an exercise system, said exercise system comprising: a primary user interface configured for interaction with the primary user; an electric motor, said electric motor configured to provide a resistive force to said primary user interface; a controller communicatively coupled with said electric motor, said controller configured to control the resistive force supplied by said electric motor as a function of time; and means for communication with the secondary user, said means for communication communicatively coupled with said controller; and communicating output of said exercise system with the remote secondary user, wherein said controller dynamically maintains the resistive force supplied by said electric motor within twenty percent of an iso-inertial force as a function of time within one-half of a repetition by adjusting the resistive force as a function of monitored acceleration of said primary user interface. | 1. A method for a primary user exercising in communication with a remote secondary user, comprising the steps of: the primary user using an exercise system, said exercise system comprising: a primary user interface configured for interaction with the primary user; an electric motor, said electric motor configured to provide a resistive force to said primary user interface; a controller communicatively coupled with said electric motor, said controller configured to control the resistive force supplied by said electric motor as a function of time; and means for communication with the secondary user, said means for communication communicatively coupled with said controller; and communicating output of said exercise system with the remote secondary user, wherein said controller dynamically maintains the resistive force supplied by said electric motor within twenty percent of an iso-inertial force as a function of time within one-half of a repetition by adjusting the resistive force as a function of monitored acceleration of said primary user interface. 10. The method of claim 1 , further comprising the step of: said controller dynamically adjusting, by at least twenty percent, the resistive force supplied by said electric motor during a repetition of movement of the primary user interface by the primary user. | 0.72293 |
9,632,985 | 77 | 79 | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. 79. The system of claim 77 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a zoomable manipulable image object. | 0.96445 |
8,280,740 | 13 | 14 | 13. The system of claim 12 , wherein the biometric voice analyzer: evaluates a personal histogram to determine whether a biometric voice print matches one of the said plurality of biometric voice prints for verifying an identity of the user, wherein the identify is validated when a first plurality of bins of the personal histogram are filled, and wherein the identity is invalidated when a second plurality of bins of the personal histogram are filled. | 13. The system of claim 12 , wherein the biometric voice analyzer: evaluates a personal histogram to determine whether a biometric voice print matches one of the said plurality of biometric voice prints for verifying an identity of the user, wherein the identify is validated when a first plurality of bins of the personal histogram are filled, and wherein the identity is invalidated when a second plurality of bins of the personal histogram are filled. 14. The system of claim 13 , wherein the biometric voice analyzer: calculates a logarithmic distance; and evaluates a threshold for determining when the first plurality of bins of the personal histogram is filled. | 0.930754 |
9,338,295 | 1 | 5 | 1. A method of dynamically adjusting a script for an interactive communication during the interactive communication, comprising: monitoring, using a computer with a processor and memory, an interactive communication over a communication network for input during the interactive communication; detecting, for the interactive communication, input incompatible with an original script for the interactive communication; categorizing a type of the incompatible input, and dynamically modifying the original script during the interactive communication into a dynamically updated script different from the original script in accordance with the categorizing and providing, over the communication network, information to an initiator of the interactive communication in accordance with the dynamically updated script, wherein a remainder of the interactive communication is conducted in accordance with the dynamically updated script. | 1. A method of dynamically adjusting a script for an interactive communication during the interactive communication, comprising: monitoring, using a computer with a processor and memory, an interactive communication over a communication network for input during the interactive communication; detecting, for the interactive communication, input incompatible with an original script for the interactive communication; categorizing a type of the incompatible input, and dynamically modifying the original script during the interactive communication into a dynamically updated script different from the original script in accordance with the categorizing and providing, over the communication network, information to an initiator of the interactive communication in accordance with the dynamically updated script, wherein a remainder of the interactive communication is conducted in accordance with the dynamically updated script. 5. The method of claim 1 , wherein the incompatible input comprises silence. | 0.79235 |
7,921,390 | 1 | 14 | 1. A method of using text from a design tool to display an output to a user, said method comprising: graphically displaying said output from said text of said design tool; graphically listing design rule violations; displaying said output as part of a software layer of said design tool such that no permanent changes are made to any original design file; requesting that particular violations be saved in a subset output file; generating and annotating said subset output file for use by other users such that said subset output file contains only said particular violations said user requested to be saved; generating said subset output file in a form that allows said subset output file to be applied against the design file; generating software help functions allowing said user to gain information about design rule violations; and iterating this process using said subset output file through a rule checking process as many times as necessary to remove said particular violations. | 1. A method of using text from a design tool to display an output to a user, said method comprising: graphically displaying said output from said text of said design tool; graphically listing design rule violations; displaying said output as part of a software layer of said design tool such that no permanent changes are made to any original design file; requesting that particular violations be saved in a subset output file; generating and annotating said subset output file for use by other users such that said subset output file contains only said particular violations said user requested to be saved; generating said subset output file in a form that allows said subset output file to be applied against the design file; generating software help functions allowing said user to gain information about design rule violations; and iterating this process using said subset output file through a rule checking process as many times as necessary to remove said particular violations. 14. The method of claim 1 further comprising reselecting said design rule violations to return to an originally presented view. | 0.802795 |
4,499,553 | 23 | 38 | 23. A digital data processing means for locating from a plurality of digital coded candidate words at least one which is both an acceptable misspelling and an acceptable inflection of a digital coded query word, the query word and each of plural ones of the candidate words comprising plural characters, the means comprising: means for determining the characters forming a stem portion and an ending portion of such query word; means for forming a suffix class indication for any one of a plurality of classes in which the query word may be included; means for comparing the characters of the stem portion of the query word with characters in the beginning of such candidate words for finding candidate words with acceptable misspelling matches and candidate words with nonacceptable misspelling matches; means for determining characters forming an ending portion, if any, in each of individual ones of the candidate words; means for utilizing the suffix class indication to select from among other suffixes a representation of characters forming at least one acceptable suffix for the candidate words; and means for comparing character by character the characters of said at least one selected acceptable suffix with the characters in the ending portion in each of the individual ones of the candidate words for finding acceptable ending portions, the first and second recited means thereby locating candidate words which are both an acceptable misspelling and an acceptable inflection of the query word. | 23. A digital data processing means for locating from a plurality of digital coded candidate words at least one which is both an acceptable misspelling and an acceptable inflection of a digital coded query word, the query word and each of plural ones of the candidate words comprising plural characters, the means comprising: means for determining the characters forming a stem portion and an ending portion of such query word; means for forming a suffix class indication for any one of a plurality of classes in which the query word may be included; means for comparing the characters of the stem portion of the query word with characters in the beginning of such candidate words for finding candidate words with acceptable misspelling matches and candidate words with nonacceptable misspelling matches; means for determining characters forming an ending portion, if any, in each of individual ones of the candidate words; means for utilizing the suffix class indication to select from among other suffixes a representation of characters forming at least one acceptable suffix for the candidate words; and means for comparing character by character the characters of said at least one selected acceptable suffix with the characters in the ending portion in each of the individual ones of the candidate words for finding acceptable ending portions, the first and second recited means thereby locating candidate words which are both an acceptable misspelling and an acceptable inflection of the query word. 38. Means according to claim 23 wherein the digital data processing means comprises at least one memory for storing a plurality of tables each having digitally coded representations therein, the means for utilizing the suffix class indication comprising: means for utilizing representations of the suffix class indications to access and to derive from a first one of the tables a representation of a list of acceptable suffixes, the acceptable suffix list corresponding to a value represented by the suffix class indication; and means for utilizing representations of the acceptable suffix list to access and to derive from a second one of the tables a representation of the characters of at least one acceptable suffix. | 0.707555 |
8,495,002 | 1 | 2 | 1. A computer-implemented software tool for training and testing a knowledge base of a computerized customer relationship management system, comprising: corpus editing processes, performed on one or more computers, for displaying and editing corpus items belonging to a corpus, and for assigning a suitable category from a set of predefined categories to individual corpus items; knowledge base building processes, performed on the one or more computers, for building a knowledge base of a computerized customer relationship management system by performing natural language and semantic analysis of a first subset of the corpus items and thereby deriving semantic and statistical information from the corpus items that are associated with nodes in the knowledge base; knowledge base testing processes, performed on the one or more computers, for testing the knowledge base of the computerized customer relationship management system on a second subset of the corpus items by extracting concepts from the corpus items of the second subset, performing statistical pattern matching to generate a set of match scores for each corpus item of the second subset, wherein each match score in the match score set represents a confidence level for classifying each corpus item of the second subset into at least one of the predefined categories using the semantic and statistical information associated with the nodes in the knowledge base of the computerized customer relationship management system; and reporting processes, performed on the one or more computers, for generating reports based on results produced by the knowledge base testing processes and causing the reports to be displayed to a user of the computerized customer relationship management system to gauge performance of the knowledge base, so that appropriate adjustments are made to improve the performance of the knowledge base. | 1. A computer-implemented software tool for training and testing a knowledge base of a computerized customer relationship management system, comprising: corpus editing processes, performed on one or more computers, for displaying and editing corpus items belonging to a corpus, and for assigning a suitable category from a set of predefined categories to individual corpus items; knowledge base building processes, performed on the one or more computers, for building a knowledge base of a computerized customer relationship management system by performing natural language and semantic analysis of a first subset of the corpus items and thereby deriving semantic and statistical information from the corpus items that are associated with nodes in the knowledge base; knowledge base testing processes, performed on the one or more computers, for testing the knowledge base of the computerized customer relationship management system on a second subset of the corpus items by extracting concepts from the corpus items of the second subset, performing statistical pattern matching to generate a set of match scores for each corpus item of the second subset, wherein each match score in the match score set represents a confidence level for classifying each corpus item of the second subset into at least one of the predefined categories using the semantic and statistical information associated with the nodes in the knowledge base of the computerized customer relationship management system; and reporting processes, performed on the one or more computers, for generating reports based on results produced by the knowledge base testing processes and causing the reports to be displayed to a user of the computerized customer relationship management system to gauge performance of the knowledge base, so that appropriate adjustments are made to improve the performance of the knowledge base. 2. The software tool of claim 1 , wherein the knowledge base testing processes calculate a set of match scores for each corpus item in the second subset, each match score from the calculated set of match scores being associated with a corresponding category and being representative of a confidence that the corpus item belongs to the corresponding category. | 0.501393 |
7,992,131 | 19 | 21 | 19. A computer programmed to convert assembly language instructions into object code, the computer comprising: means for receiving invocation of a first macro and a variable as an argument for the first macro; means, coupled to said means for receiving, for automatically identifying a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; and wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; means for automatically expanding the second macro, using at least said first assembler instructions to generate second assembler instructions in an assembly language; and means for using an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. | 19. A computer programmed to convert assembly language instructions into object code, the computer comprising: means for receiving invocation of a first macro and a variable as an argument for the first macro; means, coupled to said means for receiving, for automatically identifying a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; and wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; means for automatically expanding the second macro, using at least said first assembler instructions to generate second assembler instructions in an assembly language; and means for using an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. 21. The computer of claim 19 wherein: the means for identifying comprises a macro expander. | 0.91787 |
6,161,130 | 45 | 48 | 45. The apparatus in claim 42 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class. | 45. The apparatus in claim 42 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class. 48. The apparatus in claim 45 wherein the authoring attributes comprise whether the incoming message contains an address of a single recipient, or contains addresses of plurality of recipients or contains no sender at all, or a time at which the incoming message was transmitted. | 0.908404 |
9,679,251 | 6 | 8 | 6. The method according to claim 5 , wherein the at least one hardware processor further performs: obtaining a set complement of the largest composite sets of evidences G that supports negation of the target rule L; and computing a composite object ω 2 p indicative according to a deductive reasoning of a second plausibility value for the target rule L. | 6. The method according to claim 5 , wherein the at least one hardware processor further performs: obtaining a set complement of the largest composite sets of evidences G that supports negation of the target rule L; and computing a composite object ω 2 p indicative according to a deductive reasoning of a second plausibility value for the target rule L. 8. The method according to claim 6 , wherein the at least one hardware processor further performs adding a new object in form U→L, where the new object is the target rule L supported by the U, to the knowledge base, to expand the knowledge base to an expanded knowledge base; and the largest composite sets of evidences G is created from the expanded knowledge base that supports a logical truth T created on basis of the target rule L, subject to the relationship constraints κ which support the composite rule L 0 , to compute a third plausibility value for the target rule L. | 0.870054 |
8,380,490 | 15 | 16 | 15. The computer program product of claim 14 , wherein said computer readable means for initializing further comprises computer readable means for initializing domains. | 15. The computer program product of claim 14 , wherein said computer readable means for initializing further comprises computer readable means for initializing domains. 16. The computer program product of claim 15 , wherein said Computer readable means for initializing further comprises computer readable means for initializing transactional needs. | 0.858268 |
8,656,266 | 12 | 14 | 12. One or more devices, comprising: means for identifying a group of comments; means for determining that a first comment, of the group of comments, does not include a plurality of links pointing to a plurality of different documents; means for removing the first comment from the group of comments based on the first comment not including the plurality of links pointing to the plurality of different documents; means for identifying a second comment that includes: a first link pointing to a first document, and a second link pointing to a second document that is different than the first document; means for identifying one or more factors associated with the first link, the one or more factors associated with the first link including at least one of: a click through rate associated with the first link, explicit user feedback regarding the first link, a length of an address associated with the first link, a measure of popularity associated with the first document, or a comparison of a topic associated with the second comment and a topic associated with the first document; means for identifying one or more factors associated with the second link, the one or more factors associated with the second link including at least one of: a click through rate associated with the second link, explicit user feedback regarding the second link, a length of an address associated with the second link, a measure of popularity associated with the second document, or a comparison of the topic associated with the second comment and a topic associated with the second document; means for assigning a score to the first link based on the one or more factors associated with the first link; means for assigning a score to the second link based on the one or more factors associated with the second link; means for associating the second comment with one of the first document or the second document based on the score assigned to the first link and the score assigned to the second link, the second comment being associated with the first document when the score assigned to the first link is greater than the score assigned to the second link, and the second comment being associated with the second document when the score assigned to the second link is greater than the score assigned to the first link; and means for providing information regarding the second comment to a client device for presentation in connection with presentation of the first document or the second document, the information regarding the second comment being provided in connection with the first document when the second comment is associated with the first document, and the information regarding the second comment being provided in connection with the second document when the second comment is associated with the second document. | 12. One or more devices, comprising: means for identifying a group of comments; means for determining that a first comment, of the group of comments, does not include a plurality of links pointing to a plurality of different documents; means for removing the first comment from the group of comments based on the first comment not including the plurality of links pointing to the plurality of different documents; means for identifying a second comment that includes: a first link pointing to a first document, and a second link pointing to a second document that is different than the first document; means for identifying one or more factors associated with the first link, the one or more factors associated with the first link including at least one of: a click through rate associated with the first link, explicit user feedback regarding the first link, a length of an address associated with the first link, a measure of popularity associated with the first document, or a comparison of a topic associated with the second comment and a topic associated with the first document; means for identifying one or more factors associated with the second link, the one or more factors associated with the second link including at least one of: a click through rate associated with the second link, explicit user feedback regarding the second link, a length of an address associated with the second link, a measure of popularity associated with the second document, or a comparison of the topic associated with the second comment and a topic associated with the second document; means for assigning a score to the first link based on the one or more factors associated with the first link; means for assigning a score to the second link based on the one or more factors associated with the second link; means for associating the second comment with one of the first document or the second document based on the score assigned to the first link and the score assigned to the second link, the second comment being associated with the first document when the score assigned to the first link is greater than the score assigned to the second link, and the second comment being associated with the second document when the score assigned to the second link is greater than the score assigned to the first link; and means for providing information regarding the second comment to a client device for presentation in connection with presentation of the first document or the second document, the information regarding the second comment being provided in connection with the first document when the second comment is associated with the first document, and the information regarding the second comment being provided in connection with the second document when the second comment is associated with the second document. 14. The one or more devices of claim 12 , where the second comment is associated with the first document, the method further comprising: means for identifying a plurality of comments associated with the first document, where the second comment is one of the plurality of comments; and means for selecting one or more of the plurality of comments to present in connection with the presentation of the first document. | 0.504773 |
7,647,349 | 1 | 6 | 1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common. | 1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common. 6. The method according to claim 1 , further comprising freezing a selected second of the one or more document service requests in the imported meta-document when said binding does not map the document service request at (a) or (b). | 0.64526 |
9,805,018 | 13 | 14 | 13. The method of claim 11 , wherein step c) involves accessing a plurality of textual postings from the Internet. | 13. The method of claim 11 , wherein step c) involves accessing a plurality of textual postings from the Internet. 14. The method of claim 13 , further including rerouting bidirectional private communications from a central site computer to the Internet through representatives' computers to conceal the fact that web accesses are part of a web crawling activity. | 0.937405 |
5,493,608 | 1 | 2 | 1. A caller adaptive voice response system which adapts to a conversational pace of a caller, comprising: (a) means for measuring an amount of time indicative of the time required for said caller to respond to a voice message spoken by said system at a predetermined speaking rate; and (b) means for adjusting a subsequent speaking rate of a subsequent voice message to be spoken by said system, said adjusting means being responsive to said measuring means so as to increase said subsequent speaking rate of said subsequent voice message if said amount of time was shorter in duration than a first predetermined amount of time. | 1. A caller adaptive voice response system which adapts to a conversational pace of a caller, comprising: (a) means for measuring an amount of time indicative of the time required for said caller to respond to a voice message spoken by said system at a predetermined speaking rate; and (b) means for adjusting a subsequent speaking rate of a subsequent voice message to be spoken by said system, said adjusting means being responsive to said measuring means so as to increase said subsequent speaking rate of said subsequent voice message if said amount of time was shorter in duration than a first predetermined amount of time. 2. The apparatus according to claim 1 further comprising: means for determining if a caller response is an expected response and thereby a valid response and determining if a caller response is not a valid response and therefore an erroneous response; and means for decreasing said speaking rate of said subsequent voice message if said caller performs an action selected from a group consisting of no response and an erroneous response to said voice message preceding said subsequent voice message. | 0.891096 |
6,049,811 | 1 | 4 | 1. A machine for drafting a patent application having at least sections including claims, a summary of the invention, an abstract of the disclosure, and a detailed description of a preferred embodiment of the invention, said machine comprising: one or more input devices, one or more output devices, and a computer with memory for receiving and storing data from the input devices, transmitting data to the output devices, and storing program steps for program control and manipulating data in memory; the computer, through input and output devices, requests and stores primary elements (PE) of the invention that define the invention apart from prior technology before the claims are drafted; the claims are drafted before the summary of the invention, abstract, and the detailed description of a preferred embodiment of the invention is drafted; and the computer requires drafting the sections in a predetermined order prohibiting jumping ahead to draft a latter section. | 1. A machine for drafting a patent application having at least sections including claims, a summary of the invention, an abstract of the disclosure, and a detailed description of a preferred embodiment of the invention, said machine comprising: one or more input devices, one or more output devices, and a computer with memory for receiving and storing data from the input devices, transmitting data to the output devices, and storing program steps for program control and manipulating data in memory; the computer, through input and output devices, requests and stores primary elements (PE) of the invention that define the invention apart from prior technology before the claims are drafted; the claims are drafted before the summary of the invention, abstract, and the detailed description of a preferred embodiment of the invention is drafted; and the computer requires drafting the sections in a predetermined order prohibiting jumping ahead to draft a latter section. 4. A machine as claimed in claim 1 wherein the computer creates a draft independent claim based on the primary elements. | 0.835165 |
7,827,125 | 24 | 28 | 24. A system for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the system comprising: at least one computer system; a computer-readable storage medium storing software components for execution by the at least one computer system, the components comprising: an adaptive and collaborative user profiling engine for: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, by determining an implicit feedback value, an explicit feedback value, and a negative feedback value for the search results for which feedback is received, wherein, for concepts associated with search criteria applied to retrieve the search results, feedback is received to create a source concept that is compared against a reference concept to form a set of source concept values and a set of reference concept values, and wherein the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values by: applying the implicit feedback value to the values in the set of source concept values but not in the set of reference concept values; applying the explicit feedback value to the values in both the set of source concept values and the set of reference concept values; and applying the negative feedback value to the values in the set of reference concept values but not in the set of source concept values; and a personalized search and match engine for: modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. | 24. A system for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the system comprising: at least one computer system; a computer-readable storage medium storing software components for execution by the at least one computer system, the components comprising: an adaptive and collaborative user profiling engine for: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, by determining an implicit feedback value, an explicit feedback value, and a negative feedback value for the search results for which feedback is received, wherein, for concepts associated with search criteria applied to retrieve the search results, feedback is received to create a source concept that is compared against a reference concept to form a set of source concept values and a set of reference concept values, and wherein the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values by: applying the implicit feedback value to the values in the set of source concept values but not in the set of reference concept values; applying the explicit feedback value to the values in both the set of source concept values and the set of reference concept values; and applying the negative feedback value to the values in the set of reference concept values but not in the set of source concept values; and a personalized search and match engine for: modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. 28. The system of claim 24 , wherein at least one of the one or more profiles is a user profile that pertains to the user's general preferences that are not specifically associated with a search, and wherein at least one of the one or more profiles is a search profile that pertains to a particular query or query type not specifically associated with the user. | 0.501381 |
8,794,972 | 31 | 32 | 31. The non-transitory computer readable media containing instructions for the method of claim 23 further comprising the steps of: determining whether one of the sentences in the legal text includes a primary exception clause; and in response to a determination that one of the sentences in the legal text includes a primary exception clause, applying the primary exception marking to the legal text such that the primary exception clause is visually enhanced. | 31. The non-transitory computer readable media containing instructions for the method of claim 23 further comprising the steps of: determining whether one of the sentences in the legal text includes a primary exception clause; and in response to a determination that one of the sentences in the legal text includes a primary exception clause, applying the primary exception marking to the legal text such that the primary exception clause is visually enhanced. 32. The non-transitory computer readable media containing instructions for the method of claim 31 further comprising the steps of: determining whether one of the sentences in the legal text includes a secondary exception clause; and in response to a determination that one of the sentences in the legal text includes a secondary exception clause, applying the secondary exception marking to the legal text such that the secondary exception clause is visually enhanced. | 0.858866 |
8,630,995 | 1 | 13 | 1. A computer-implemented method for acquiring and processing information about non-human animal diseases, the method comprising: importing veterinary-related text information, wherein the veterinary-related text information is related to one or more non-human animal diseases; parsing the veterinary-related text information into one or more terms; determining relations between the one or more terms; classifying the one or more terms such that each term relates to one of: a non-human animal species, an animal disease, a medical sign and a treatment; and generating a database table associated with the imported veterinary-related text information, the database table comprising the one or more classified terms and the relations therebetween. | 1. A computer-implemented method for acquiring and processing information about non-human animal diseases, the method comprising: importing veterinary-related text information, wherein the veterinary-related text information is related to one or more non-human animal diseases; parsing the veterinary-related text information into one or more terms; determining relations between the one or more terms; classifying the one or more terms such that each term relates to one of: a non-human animal species, an animal disease, a medical sign and a treatment; and generating a database table associated with the imported veterinary-related text information, the database table comprising the one or more classified terms and the relations therebetween. 13. The method of claim 1 , further comprising: virtually linking the generated database table associated with the imported veterinary-related text information with one or more remote resources in the network. | 0.77381 |
7,920,742 | 4 | 6 | 4. The image processing apparatus according to claim 1 , wherein: when at least one of the start position and the end position of the mark, which defines the mark is identified by the second identifying unit, is less than a beginning of the position of the string or an end of the position of the string, the character string extracting unit determines whether or not the string identified by the first identifying unit is to be extracted based on a extraction condition that is preset. | 4. The image processing apparatus according to claim 1 , wherein: when at least one of the start position and the end position of the mark, which defines the mark is identified by the second identifying unit, is less than a beginning of the position of the string or an end of the position of the string, the character string extracting unit determines whether or not the string identified by the first identifying unit is to be extracted based on a extraction condition that is preset. 6. The image processing apparatus according to claim 4 , wherein the extraction condition is based on a type of word represented by the given string. | 0.910024 |
8,576,430 | 1 | 16 | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. 16. The method of claim 1 wherein the historical decision database stores an indication of previously successful decision frequencies for a plurality of decision levels. | 0.621076 |
7,849,091 | 3 | 4 | 3. The method of claim 2 , further comprising associating by inheritance a second set of elements of the plurality of elements of the tree-structured data with explicit meta-data levels of closest ancestor elements of the first set of elements. | 3. The method of claim 2 , further comprising associating by inheritance a second set of elements of the plurality of elements of the tree-structured data with explicit meta-data levels of closest ancestor elements of the first set of elements. 4. The method of claim 3 , further comprising: packing the plurality of elements of the tree-structured data, including the first set of elements and the second set of elements and the meta-data levels associated therewith, into a plurality of leaf nodes of the index structure; merging the plurality of leaf nodes of the index structure into a plurality of non-leaf nodes of the index structure until a root non-leaf node is generated; and associating the plurality of non-leaf nodes of the index structure with the explicit meta-data levels of the packed first set of elements. | 0.782003 |
8,761,351 | 1 | 2 | 1. A method comprising: receiving, by a processor, via an internet protocol (IP) network, information pertaining to an event, wherein: the information is indicative of speech; the information is formatted in accordance with a voice over internet protocol (VoIP); the information is indicative of being provided by a P25 land mobile radio, via a federally regulated land mobile radio system; providing the information for storage, wherein the stored information is available for access by at least one entity associated with an emergency operations center; automatically converting the VoIP formatted information to text; automatically formatting, by the processor, the text in accordance with a WebEOC emergency operations center log format; and providing the formatted text for storage, wherein the stored formatted text is available for access by at least one entity associated with the emergency operations center. | 1. A method comprising: receiving, by a processor, via an internet protocol (IP) network, information pertaining to an event, wherein: the information is indicative of speech; the information is formatted in accordance with a voice over internet protocol (VoIP); the information is indicative of being provided by a P25 land mobile radio, via a federally regulated land mobile radio system; providing the information for storage, wherein the stored information is available for access by at least one entity associated with an emergency operations center; automatically converting the VoIP formatted information to text; automatically formatting, by the processor, the text in accordance with a WebEOC emergency operations center log format; and providing the formatted text for storage, wherein the stored formatted text is available for access by at least one entity associated with the emergency operations center. 2. The method of claim 1 , further comprising providing an instant messaging service to an originator of the information. | 0.886278 |
7,788,103 | 17 | 19 | 17. A system, in accordance with claim 10 , further comprising: a self-monitoring and adaptation mechanism capable of collecting confirmation results. | 17. A system, in accordance with claim 10 , further comprising: a self-monitoring and adaptation mechanism capable of collecting confirmation results. 19. The system according to claim 17 , wherein the self-monitoring and adaptation mechanism adapts the speech recognizer producing the speech recognition result based on collected confirmation results. | 0.926374 |
9,891,792 | 45 | 46 | 45. The method for building and utilizing tax preparation system related models using biometric data of claim 44 , wherein the manual feedback data obtained from the user is combined with additional baseline data associated with the user to create reference set data for the user. | 45. The method for building and utilizing tax preparation system related models using biometric data of claim 44 , wherein the manual feedback data obtained from the user is combined with additional baseline data associated with the user to create reference set data for the user. 46. The method for building and utilizing tax preparation system related models using biometric data of claim 45 , wherein the additional baseline data associated with the user includes one or more of: data acquired from the user's own characterization of his or her emotional state; data acquired from historical user data; and data acquired from a segment of users having characteristics comparable to the user. | 0.953855 |
9,626,362 | 2 | 3 | 2. The system of claim 1 , wherein the content management application is further to receive a request from the external application for collection information regarding the at least a portion of the persistent document collection, and in response to the request from the external application, the content management application further to retrieve the collection information from the data store and return the collection information to the external application. | 2. The system of claim 1 , wherein the content management application is further to receive a request from the external application for collection information regarding the at least a portion of the persistent document collection, and in response to the request from the external application, the content management application further to retrieve the collection information from the data store and return the collection information to the external application. 3. The system of claim 2 , wherein the collection information that is provided to the external application is used by the external application to allow management of one or more of the sub-set of documents that are represented by the collection information. | 0.90123 |
9,696,969 | 18 | 20 | 18. A system, comprising: a memory, communicatively coupled to a processor, the memory storing the computer-executable components comprising: an editor component configured to: infer a first industrial programming language of a plurality of industrial programming languages to utilize for programming an industrial controller and infer a second industrial programming language of the plurality of industrial programming languages to utilize in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises interaction techniques between respective industrial programming languages of the industrial programming languages; and combine at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to create the custom programming language for programming the industrial controller, wherein the first industrial programming language, the industrial second programming language and the custom programming language are disparate. | 18. A system, comprising: a memory, communicatively coupled to a processor, the memory storing the computer-executable components comprising: an editor component configured to: infer a first industrial programming language of a plurality of industrial programming languages to utilize for programming an industrial controller and infer a second industrial programming language of the plurality of industrial programming languages to utilize in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises interaction techniques between respective industrial programming languages of the industrial programming languages; and combine at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to create the custom programming language for programming the industrial controller, wherein the first industrial programming language, the industrial second programming language and the custom programming language are disparate. 20. The system of claim 18 , wherein the at least one criteria further comprises graphical properties of respective industrial programming languages of the industrial programming languages. | 0.772837 |
9,128,985 | 1 | 6 | 1. A computer implemented method, comprising: receiving raw data at a computing device; parsing the raw data into event records by determining event boundaries in the raw data, wherein each of the event records includes a portion of the raw data and is associated with a time derived from the raw data; storing the event records in an indexed data store; generating a summarization table that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more of the event records in the indexed data store; and for each field value, identifies a set of one or more event records in the indexed data store that contain the field value for the associated field; receiving a query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the summarization table to generate a preliminary result set; determining that the query cannot be answered fully by the summarization table by determining that the indexed data store includes event records that have not been processed for inclusion in the summarization table; and based on determining that the indexed data store includes event records that have not been processed for inclusion in the summarization table: using the search criteria to identify supplemental event records in the indexed data store that satisfy the search criteria and that have not been processed for inclusion in the summarization table; generating a query result using the preliminary result set from the summarization table and the supplemental event records; and causing display of the query result or transmitting the query result to a second computing device for further processing and output. | 1. A computer implemented method, comprising: receiving raw data at a computing device; parsing the raw data into event records by determining event boundaries in the raw data, wherein each of the event records includes a portion of the raw data and is associated with a time derived from the raw data; storing the event records in an indexed data store; generating a summarization table that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more of the event records in the indexed data store; and for each field value, identifies a set of one or more event records in the indexed data store that contain the field value for the associated field; receiving a query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the summarization table to generate a preliminary result set; determining that the query cannot be answered fully by the summarization table by determining that the indexed data store includes event records that have not been processed for inclusion in the summarization table; and based on determining that the indexed data store includes event records that have not been processed for inclusion in the summarization table: using the search criteria to identify supplemental event records in the indexed data store that satisfy the search criteria and that have not been processed for inclusion in the summarization table; generating a query result using the preliminary result set from the summarization table and the supplemental event records; and causing display of the query result or transmitting the query result to a second computing device for further processing and output. 6. The method of claim 1 , wherein the raw data includes machine data. | 0.958234 |
9,076,251 | 21 | 22 | 21. A system for modifying color in an image using component specific natural language color commands comprising: a computing system including at least one computing device, the computing system configured to: identify an input image to be modified; segment the input image into a plurality of image components, the input components being discrete segments of the input image; assign each of the plurality of image components a component identity based on content of the image component using pattern recognition, object recognition, and boundaries analysis; classify the plurality of image components into a plurality of component types; receive a component specific natural language color command for a color modification of an input image, the component specific natural language color command including a component type identifier and a color modifier; parse the component specific natural language color command to obtain the component type identifier and the color modifier contained in the component specific natural language color command; identify, without user input, the one or more component types corresponding to the parsed component type identifier; identify all of the image components classified with each of the identified component types; attribute the color modifier to a predefined color space associated with each of the identified image components, the color modifier indicating the color modification to be performed; and apply the color modification to the identified image components to adjust the color of the identified image components. | 21. A system for modifying color in an image using component specific natural language color commands comprising: a computing system including at least one computing device, the computing system configured to: identify an input image to be modified; segment the input image into a plurality of image components, the input components being discrete segments of the input image; assign each of the plurality of image components a component identity based on content of the image component using pattern recognition, object recognition, and boundaries analysis; classify the plurality of image components into a plurality of component types; receive a component specific natural language color command for a color modification of an input image, the component specific natural language color command including a component type identifier and a color modifier; parse the component specific natural language color command to obtain the component type identifier and the color modifier contained in the component specific natural language color command; identify, without user input, the one or more component types corresponding to the parsed component type identifier; identify all of the image components classified with each of the identified component types; attribute the color modifier to a predefined color space associated with each of the identified image components, the color modifier indicating the color modification to be performed; and apply the color modification to the identified image components to adjust the color of the identified image components. 22. The system of claim 21 , wherein the computing system is configured to apply the color modification without affecting the plurality of image components other than the identified at least one image component in the image. | 0.753304 |
10,108,661 | 1 | 5 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: creating a structured resource from a corpus of documents, wherein the structured resource comprises a plurality of first member entities and a plurality of second member entities; identifying a plurality of sentences in the corpus of documents that each comprises one of the plurality of first member entities and one of the plurality of second member entities; constructing a natural language context, for each of the plurality of sentences, based on a sentence context of the first member entity included in the sentence relative to the second member entity included in the sentence, wherein the constructing produces a plurality of natural language contexts that are different from each other; generating a plurality of database queries based on the plurality of natural language contexts, wherein each of the plurality of database queries are different from each other; creating a plurality of pattern maps that each comprise one of the plurality of natural language contexts and one of the plurality of database queries corresponding to the natural language context; in response to matching a question to each of the plurality of natural language contexts, assigning a priority score to each of the plurality of pattern maps based upon a relative amount at which their corresponding one of the plurality of natural language contexts have been matched against one or more previous questions; and invoking each of the plurality of database queries corresponding to the each of the plurality of the patterns maps in an order based on the corresponding priority score assigned to each of the plurality of the pattern maps, until a data resource match is reached. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: creating a structured resource from a corpus of documents, wherein the structured resource comprises a plurality of first member entities and a plurality of second member entities; identifying a plurality of sentences in the corpus of documents that each comprises one of the plurality of first member entities and one of the plurality of second member entities; constructing a natural language context, for each of the plurality of sentences, based on a sentence context of the first member entity included in the sentence relative to the second member entity included in the sentence, wherein the constructing produces a plurality of natural language contexts that are different from each other; generating a plurality of database queries based on the plurality of natural language contexts, wherein each of the plurality of database queries are different from each other; creating a plurality of pattern maps that each comprise one of the plurality of natural language contexts and one of the plurality of database queries corresponding to the natural language context; in response to matching a question to each of the plurality of natural language contexts, assigning a priority score to each of the plurality of pattern maps based upon a relative amount at which their corresponding one of the plurality of natural language contexts have been matched against one or more previous questions; and invoking each of the plurality of database queries corresponding to the each of the plurality of the patterns maps in an order based on the corresponding priority score assigned to each of the plurality of the pattern maps, until a data resource match is reached. 5. The method of claim 1 further comprising: determining that the structured resource comprises a plurality of entity-cluster centroids; generating a synthetic event for each one of the plurality of entity-cluster centroids, resulting in a plurality of synthetic events; selecting one of the plurality of synthetic events; and linking a plurality of synthetic event relations to the selected synthetic event. | 0.620112 |
7,672,844 | 4 | 8 | 4. A voice processing apparatus as set forth in claim 3 , wherein said data processing means compares said first speaker data with said second speaker data and, only when the two are matched, processes the voice signal output from said one microphone by associating with said second speaker data. | 4. A voice processing apparatus as set forth in claim 3 , wherein said data processing means compares said first speaker data with said second speaker data and, only when the two are matched, processes the voice signal output from said one microphone by associating with said second speaker data. 8. A voice processing apparatus as set forth in claim 4 , further comprising a voice conversion means for converting a voice signal to character string data, wherein said voice conversion means converts the voice signal collected by said one microphone to character string data; and said data processing means processes said character string data by associating with the speaker data obtained by checking against said voice signal. | 0.873681 |
9,264,784 | 9 | 13 | 9. A recommendation system comprising: one or more communication interfaces; one or more memories that store instructions; and one or more processors to execute the instructions to: obtain, via at least one of the one or more communication interfaces, program historical data associated with users that each receive one or more programs via one or more channels of a program delivery network that provides a program service to which the users belong; obtain, via at least one of the one or more communication interfaces, social network data associated with the users from social network sites to which the users belong, wherein the social network data includes a social graph, communication data pertaining to communications between the users via a communication network that provides a communication service to which the users belong, wherein the communication service includes a mobile phone service and a messaging service, and the communication data includes mobile phone calls, and user profile information pertaining to the users; calculate based on the social network data, the communication data, and the user profile information, a social similarity value that indicates a social similarity between one of the users and other users; calculate based on the program historical data, a channel-interest similarity value that indicates a common interest between the one of the users and the other users in relation to the one or more channels used by the users to receive the one or more programs; calculate based on the social similarity value and the channel-interest similarity value, a similarity index value that indicates a similarity between the one of the users and the other users; calculate based on the program historical data a program regularity value, for each program, that indicates a regularity of consumption of each program over a time period; calculate based on the program regularity value, a program weight value, for each program, that indicates a priority value; calculate based on the program historical data, a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users. | 9. A recommendation system comprising: one or more communication interfaces; one or more memories that store instructions; and one or more processors to execute the instructions to: obtain, via at least one of the one or more communication interfaces, program historical data associated with users that each receive one or more programs via one or more channels of a program delivery network that provides a program service to which the users belong; obtain, via at least one of the one or more communication interfaces, social network data associated with the users from social network sites to which the users belong, wherein the social network data includes a social graph, communication data pertaining to communications between the users via a communication network that provides a communication service to which the users belong, wherein the communication service includes a mobile phone service and a messaging service, and the communication data includes mobile phone calls, and user profile information pertaining to the users; calculate based on the social network data, the communication data, and the user profile information, a social similarity value that indicates a social similarity between one of the users and other users; calculate based on the program historical data, a channel-interest similarity value that indicates a common interest between the one of the users and the other users in relation to the one or more channels used by the users to receive the one or more programs; calculate based on the social similarity value and the channel-interest similarity value, a similarity index value that indicates a similarity between the one of the users and the other users; calculate based on the program historical data a program regularity value, for each program, that indicates a regularity of consumption of each program over a time period; calculate based on the program regularity value, a program weight value, for each program, that indicates a priority value; calculate based on the program historical data, a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users. 13. The recommendation system of claim 9 , wherein when calculating the program regularity value, at least one of the one or more processors to execute the instructions to: filter the program historical data into 30 minute periods of a day; calculate a number of time tags included in the program historical data for each 30 minute period; and calculate a probability of program regularity, wherein the program historical data does not include program identifiers and does not include regularity data that indicates a regularity of a program. | 0.709227 |
8,219,385 | 28 | 29 | 28. The computer program product of claim 22 wherein said electronically stored information includes information on a plurality of members of a group and characteristics of said members, and wherein said search results comprise an identification of a particular subset of members of said group. | 28. The computer program product of claim 22 wherein said electronically stored information includes information on a plurality of members of a group and characteristics of said members, and wherein said search results comprise an identification of a particular subset of members of said group. 29. The computer program product of claim 28 wherein said members of said group comprise shoppers at one or more given businesses, and wherein said characteristics comprise attributes of said shoppers and past shopping behaviors. | 0.921629 |
9,158,816 | 18 | 19 | 18. A computer-readable storage device comprising instructions, that when executed by a computer, cause the computer to: receive, at an event processing system, at least one event from a source, wherein each event is represented in a first data format that is native to the source; convert the at least one event from the first data format to at least one event object formatted in a second data format, the at least one event object including a payload, a validity start time, and a validity end time; execute a query with respect to the at least one event object to produce a result object, wherein the query is represented by an extensible markup language (XML) file that is based on a reusable XML query template that is bindable to a plurality of input adapters and a plurality of output adapters, wherein the result object is produced based on an application of at least one operator of the query, wherein the result object is formatted in the second data format, and wherein the query is executed by comparing the event object to static reference data received from a static reference source without storing any of the plurality of event objects at the memory; convert the result object from the second data format to at least one result formatted in a third data format that is native to a sink; and transmit the at least one result to the sink. | 18. A computer-readable storage device comprising instructions, that when executed by a computer, cause the computer to: receive, at an event processing system, at least one event from a source, wherein each event is represented in a first data format that is native to the source; convert the at least one event from the first data format to at least one event object formatted in a second data format, the at least one event object including a payload, a validity start time, and a validity end time; execute a query with respect to the at least one event object to produce a result object, wherein the query is represented by an extensible markup language (XML) file that is based on a reusable XML query template that is bindable to a plurality of input adapters and a plurality of output adapters, wherein the result object is produced based on an application of at least one operator of the query, wherein the result object is formatted in the second data format, and wherein the query is executed by comparing the event object to static reference data received from a static reference source without storing any of the plurality of event objects at the memory; convert the result object from the second data format to at least one result formatted in a third data format that is native to a sink; and transmit the at least one result to the sink. 19. The computer-readable storage device of claim 18 , wherein the at least one operator is a payload-specific operator, a validity start time-specific operator, a validity end time-specific operator, or any combination thereof. | 0.502183 |
9,773,182 | 16 | 19 | 16. The method of claim 15 , wherein: the electronic document is a markup language document; and the first portion and the second portion are nodes within a document object model (DOM) tree of the markup language document or a sub-tree comprising a parent node and one or more child nodes within the DOM tree of the markup language document. | 16. The method of claim 15 , wherein: the electronic document is a markup language document; and the first portion and the second portion are nodes within a document object model (DOM) tree of the markup language document or a sub-tree comprising a parent node and one or more child nodes within the DOM tree of the markup language document. 19. The method of claim 16 , further comprising determining the content-to-noise ratio using noise metrics, wherein the noise metrics comprises at least one of: a ratio of a number of link nodes in the first portion to a number of text nodes in the first portion; a number of characters in links within the first portion; a number of images in the first portion, wherein the images comprise advertisements; a number of link nodes in the first portion, wherein the link nodes are links to nodes comprising advertisements; a number of valid containers in the first portion; or a number of small images in the first portion, wherein a small image is an image has a size smaller than a threshold. | 0.763661 |
9,093,062 | 10 | 14 | 10. A computer system for delivering an announcement in two or more languages, the system comprising: a plurality of microphones deployed in an environment; and one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the program instructions comprising: program instructions to receive, from the plurality of microphones deployed in the environment, input representative of audio of a group of human speakers speaking in the environment in two or more natural languages during a duration of time, wherein each microphone of the plurality of microphones transmits respective audio signals on separate channels; program instructions to process the input to identify the two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to process the audio signals on each channel to identify a first utterance match for one of the identified two or more natural languages; program instructions to, for each of the identified two or more natural languages, calculate a number of channels on which a first utterance match for that natural language was identified; program instructions to process the input to determine a relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time, wherein the relative proportion of a natural language is based, at least in part, on the calculated number of channels on which a first utterance match for that natural language was identified; program instructions to determine two or more natural languages in which to deliver the announcement based, at least in part, on the relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to determine a descending sequential order in which to deliver the announcement in the determined two or more natural languages based, at least in part, on the relative proportion of each of the identified two or more natural languages; and program instructions to cause to be delivered the announcement in the determined two or more natural languages in the determined descending sequential order by transmitting the announcement to an announcement system. | 10. A computer system for delivering an announcement in two or more languages, the system comprising: a plurality of microphones deployed in an environment; and one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the program instructions comprising: program instructions to receive, from the plurality of microphones deployed in the environment, input representative of audio of a group of human speakers speaking in the environment in two or more natural languages during a duration of time, wherein each microphone of the plurality of microphones transmits respective audio signals on separate channels; program instructions to process the input to identify the two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to process the audio signals on each channel to identify a first utterance match for one of the identified two or more natural languages; program instructions to, for each of the identified two or more natural languages, calculate a number of channels on which a first utterance match for that natural language was identified; program instructions to process the input to determine a relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time, wherein the relative proportion of a natural language is based, at least in part, on the calculated number of channels on which a first utterance match for that natural language was identified; program instructions to determine two or more natural languages in which to deliver the announcement based, at least in part, on the relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to determine a descending sequential order in which to deliver the announcement in the determined two or more natural languages based, at least in part, on the relative proportion of each of the identified two or more natural languages; and program instructions to cause to be delivered the announcement in the determined two or more natural languages in the determined descending sequential order by transmitting the announcement to an announcement system. 14. The system of claim 10 , wherein the plurality of microphones are positioned throughout a mass-transit passenger terminal. | 0.776596 |
9,230,539 | 1 | 9 | 1. A system comprising: a computer-readable medium having stored thereon model data that includes at least one model of a characteristic of a language spoken by a patient; and a speech analyzer configured to analyze an audio sample including speech of the patient, identify phonemes from the speech of the patient, analyze the identified phonemes to identify prosodic characteristics of the speech of the patient using the model, and automatically measure fluency of the speech of the patient based on the prosodic characteristics. | 1. A system comprising: a computer-readable medium having stored thereon model data that includes at least one model of a characteristic of a language spoken by a patient; and a speech analyzer configured to analyze an audio sample including speech of the patient, identify phonemes from the speech of the patient, analyze the identified phonemes to identify prosodic characteristics of the speech of the patient using the model, and automatically measure fluency of the speech of the patient based on the prosodic characteristics. 9. The system of claim 1 , further comprising a spectrogram calculator to calculate a spectrogram from a portion of the audio sample. | 0.871124 |
8,365,138 | 42 | 43 | 42. The process of claim 34 further comprising the step of displaying on the display of a computer diagrams and textual interactive dialogs which said designer of said Conceptual Model interacts with to use object-oriented modelling techniques to define the classes of said Conceptual Model, where said diagrams and textual interactive dialogs are structured to allow specification of services as events or transactions, where events are a single service and where transactions are compositions of multiple services each of which may be an event or a transaction, each said transaction having a formula which defines the composition of services which make up said transaction, and wherein said diagrams and textual interactive dialogs are structured to allow a designer to specify a list of arguments for each service where each argument may be given the following characteristics: name, data type, whether nulls are allowed as a valid value, whether the argument represents a set of objects, a default value, an alias and a selection of a user interface which may be an introduction pattern, a population selection pattern, a defined selection pattern or dependency pattern, and wherein said textual interactive dialogs are structured to allow said designer give each attribute a definition which may include the following characteristics: a name, a formal type which may be defined as a constant, variable or derived variable, a data type, a default value, whether the attribute is an identifier for distinguishing the objects of a class, a length, whether the attribute is required when the object is created, whether the attribute can be assigned a null value, and a field to introduce some remarks regarding why the attribute has been created, and wherein said textual interactive dialogs are structured to allow said designer to include a set of valuation formulas that define how the value of the attribute is changed by means of execution of an event by defining a condition that must be satisfied to apply the effect, each said formula also defining the event that causes the effect and each said formula supplying a mathematical or Boolean expression that defines how the named event affects the value of said attribute, said textual interactive dialogs also structured to allow said designer to select user interface patterns to be applied in the corresponding service arguments related to the attribute. | 42. The process of claim 34 further comprising the step of displaying on the display of a computer diagrams and textual interactive dialogs which said designer of said Conceptual Model interacts with to use object-oriented modelling techniques to define the classes of said Conceptual Model, where said diagrams and textual interactive dialogs are structured to allow specification of services as events or transactions, where events are a single service and where transactions are compositions of multiple services each of which may be an event or a transaction, each said transaction having a formula which defines the composition of services which make up said transaction, and wherein said diagrams and textual interactive dialogs are structured to allow a designer to specify a list of arguments for each service where each argument may be given the following characteristics: name, data type, whether nulls are allowed as a valid value, whether the argument represents a set of objects, a default value, an alias and a selection of a user interface which may be an introduction pattern, a population selection pattern, a defined selection pattern or dependency pattern, and wherein said textual interactive dialogs are structured to allow said designer give each attribute a definition which may include the following characteristics: a name, a formal type which may be defined as a constant, variable or derived variable, a data type, a default value, whether the attribute is an identifier for distinguishing the objects of a class, a length, whether the attribute is required when the object is created, whether the attribute can be assigned a null value, and a field to introduce some remarks regarding why the attribute has been created, and wherein said textual interactive dialogs are structured to allow said designer to include a set of valuation formulas that define how the value of the attribute is changed by means of execution of an event by defining a condition that must be satisfied to apply the effect, each said formula also defining the event that causes the effect and each said formula supplying a mathematical or Boolean expression that defines how the named event affects the value of said attribute, said textual interactive dialogs also structured to allow said designer to select user interface patterns to be applied in the corresponding service arguments related to the attribute. 43. The process of claim 42 further comprising the step of displaying on the display of a computer diagrams and textual interactive dialogs which said designer of said Conceptual Model may interact with to use object-oriented modelling techniques to define the classes of said Conceptual Model and wherein said diagrams and textual interactive dialogs are structured to allow said designer to specify formulas for derivations and constraints for each class, where said textual interactive dialogs allow said designer, for each derivation, to specify a list of pairs, each pair comprising a condition and a formula, each said condition specifying which formula will be applied in each condition, and wherein said textual interactive dialogs allow said designer to specify each constraint as a formula plus an error message which will be displayed if the constraint is violated. | 0.944204 |
9,886,430 | 16 | 18 | 16. A computer-readable storage medium comprising computer-executable instructions that, when executed by a processor, perform a method comprising: detecting a selection mode initiated by a user with regard to a displayed document, the displayed document including content; automatically, while in the initiated selection mode, detecting content selected in the displayed document by a user; automatically determining, in response to the detection of the selection mode initiated by the user, a plurality of entities in the displayed document, each entity of the plurality of entities including a portion of the displayed document content different from the detected selected content; automatically annotating the displayed document to indicate each of the determined plurality of entities; automatically determining, in response to said determining the plurality of entities in the displayed document, at least one entity of the plurality of entities that includes content of the displayed document content that is associated with the detected selected content; automatically indicating in the displayed document the determined at least one entity as one or more active entities; and enabling an action to be performed on the active entities. | 16. A computer-readable storage medium comprising computer-executable instructions that, when executed by a processor, perform a method comprising: detecting a selection mode initiated by a user with regard to a displayed document, the displayed document including content; automatically, while in the initiated selection mode, detecting content selected in the displayed document by a user; automatically determining, in response to the detection of the selection mode initiated by the user, a plurality of entities in the displayed document, each entity of the plurality of entities including a portion of the displayed document content different from the detected selected content; automatically annotating the displayed document to indicate each of the determined plurality of entities; automatically determining, in response to said determining the plurality of entities in the displayed document, at least one entity of the plurality of entities that includes content of the displayed document content that is associated with the detected selected content; automatically indicating in the displayed document the determined at least one entity as one or more active entities; and enabling an action to be performed on the active entities. 18. The computer-readable storage medium of claim 16 , wherein said determining at least one entity of the plurality of entities that is associated with the detected selected content comprises: transmitting the displayed document and an indication of the detected selected content over a network to a document analysis service; and receiving an indication of the at least one entity from the document analysis service over the network. | 0.549689 |
8,386,465 | 12 | 18 | 12. A system for decreasing the perceived end user latency while interacting with a media database comprising: the media database storing metadata associated with media; a media manager in communication with at least one media player and operable to access the media database via at least one of a plurality of connections between the at least one media player and the media manager; the at least one media player each having a user interface operable to display a first set of query results and receive user input based on the displayed first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface; and a predictive module operable to generate at least one query based on the user input and to derive at least one predictive background query of the database displayed on the displayed first set of query results and prior to a user invoking any action within the user interface, the predictive module compares the at least one generated query to the at least one derived background query such that if the generated query corresponds to the at least one background query the user interface displays the another set of query results acquired from the at least one background query that correspond to the at least one generated query. | 12. A system for decreasing the perceived end user latency while interacting with a media database comprising: the media database storing metadata associated with media; a media manager in communication with at least one media player and operable to access the media database via at least one of a plurality of connections between the at least one media player and the media manager; the at least one media player each having a user interface operable to display a first set of query results and receive user input based on the displayed first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface; and a predictive module operable to generate at least one query based on the user input and to derive at least one predictive background query of the database displayed on the displayed first set of query results and prior to a user invoking any action within the user interface, the predictive module compares the at least one generated query to the at least one derived background query such that if the generated query corresponds to the at least one background query the user interface displays the another set of query results acquired from the at least one background query that correspond to the at least one generated query. 18. The system of claim 12 , wherein the predictive module performs all possible background queries of an answer to a generated query. | 0.965694 |
9,568,908 | 13 | 18 | 13. A non-transitory computer-readable medium having stored thereon executable instructions that, in response to execution, cause a computing system to perform operations, the operations comprising: receiving an industrial application and associated metadata from a first client device, the industrial application comprising at least one of programming code for an industrial controller or a human-machine interface graphic, and the metadata specifying at least an industry type and a type of industrial process to which the industrial application pertains; indexing the industrial application in an application library in accordance with the metadata, the application library residing on a cloud platform and classifying the industrial application according to hierarchical categories of a storage schema comprising at least the industry type and the type of industrial process specified by the metadata; receiving browsing input from a second client device; identifying a subset of industrial applications stored in the application library based on the browsing input, wherein the browsing input progressively narrows the subset of the industrial applications based on a selected industry type and a selected type of industrial process identified by the browsing input; displaying identification information for the subset of industrial applications; and provisioning a selected industrial application of the subset of industrial applications to a memory location associated with the second client device. | 13. A non-transitory computer-readable medium having stored thereon executable instructions that, in response to execution, cause a computing system to perform operations, the operations comprising: receiving an industrial application and associated metadata from a first client device, the industrial application comprising at least one of programming code for an industrial controller or a human-machine interface graphic, and the metadata specifying at least an industry type and a type of industrial process to which the industrial application pertains; indexing the industrial application in an application library in accordance with the metadata, the application library residing on a cloud platform and classifying the industrial application according to hierarchical categories of a storage schema comprising at least the industry type and the type of industrial process specified by the metadata; receiving browsing input from a second client device; identifying a subset of industrial applications stored in the application library based on the browsing input, wherein the browsing input progressively narrows the subset of the industrial applications based on a selected industry type and a selected type of industrial process identified by the browsing input; displaying identification information for the subset of industrial applications; and provisioning a selected industrial application of the subset of industrial applications to a memory location associated with the second client device. 18. The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise creating a new category of the hierarchical categories in response to determining that the metadata includes the new category and that the new category is not defined within the storage schema. | 0.782448 |
9,286,619 | 16 | 19 | 16. A method performed by at least one processing unit of a computing device, the method comprising: filtering a plurality of communications to identify a subset of the communications that each refer to a common hashtag or a common web link; computing similarity scores for the identified subset of the communications, the similarity scores reflecting semantic similarities among individual communications of the subset; computing diversity scores for the identified subset of the communications, the diversity scores reflecting semantic differences among individual communications of the subset; combining the similarity scores and the diversity scores to determine total scores for the identified subset of the communications; selecting one or more of the individual communications based on the total scores; and generating a summary of the common hashtag or common web link referred to by each of the communications of the subset, the summary representing the one or more selected individual communications. | 16. A method performed by at least one processing unit of a computing device, the method comprising: filtering a plurality of communications to identify a subset of the communications that each refer to a common hashtag or a common web link; computing similarity scores for the identified subset of the communications, the similarity scores reflecting semantic similarities among individual communications of the subset; computing diversity scores for the identified subset of the communications, the diversity scores reflecting semantic differences among individual communications of the subset; combining the similarity scores and the diversity scores to determine total scores for the identified subset of the communications; selecting one or more of the individual communications based on the total scores; and generating a summary of the common hashtag or common web link referred to by each of the communications of the subset, the summary representing the one or more selected individual communications. 19. The method according to claim 16 , wherein the combining comprises adding the similarity scores and the diversity scores for the individual communications of the subset. | 0.911554 |
4,507,734 | 7 | 8 | 7. A system according to claim 6 comprising a cathode ray display tube; an input buffer for receiving a flow of data from a data-processing system to which it is connected; and an output buffer via which the system is connected to the last-mentioned data-processing system; and the display screen acts as store and is connected to the output buffer by way of a processing unit adapted to convert the displayed data presenting in all the forms of the characters of the second alphabet into a flow of data coded in standard binary code. | 7. A system according to claim 6 comprising a cathode ray display tube; an input buffer for receiving a flow of data from a data-processing system to which it is connected; and an output buffer via which the system is connected to the last-mentioned data-processing system; and the display screen acts as store and is connected to the output buffer by way of a processing unit adapted to convert the displayed data presenting in all the forms of the characters of the second alphabet into a flow of data coded in standard binary code. 8. A system according to claim 7, comprising a keyboard providing data in the standard code and connected to the display screen by way of the processing unit. | 0.933502 |
7,818,658 | 14 | 24 | 14. A system for editing a multimedia presentation that includes plurality of scenes, each scene including a sequence of visual displays, the multimedia presentation being defined by a presentation script such as a presentation script including instructions that include identification of a plurality of content assets, identification of one or more visual displays in which the identified content assets are to be included, one or more modifications of the content assets to be performed prior to inclusion of the identified content assets in the one or more visual displays, instructions for positioning the modified content assets in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display, the system comprising: a processor configured to implement a user interface for editing a presentation script defining a multimedia presentation, the user interface comprising: a timeline strip for indicating a display order for individual scenes in a presentation; and a compose window coupled to the timeline strip for editing individual scenes in a presentation and individual content assets within the individual scenes, resulting in corresponding edits being made to the presentation script by the processor. | 14. A system for editing a multimedia presentation that includes plurality of scenes, each scene including a sequence of visual displays, the multimedia presentation being defined by a presentation script such as a presentation script including instructions that include identification of a plurality of content assets, identification of one or more visual displays in which the identified content assets are to be included, one or more modifications of the content assets to be performed prior to inclusion of the identified content assets in the one or more visual displays, instructions for positioning the modified content assets in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display, the system comprising: a processor configured to implement a user interface for editing a presentation script defining a multimedia presentation, the user interface comprising: a timeline strip for indicating a display order for individual scenes in a presentation; and a compose window coupled to the timeline strip for editing individual scenes in a presentation and individual content assets within the individual scenes, resulting in corresponding edits being made to the presentation script by the processor. 24. The system of claim 14 , the compose window further including a frame out slider for adjusting the frame out cue of a presentation asset. | 0.902624 |
9,223,836 | 18 | 19 | 18. A non-transitory computer-readable medium encoded with a document ranking application comprising modules executable by a processor and configured to rank document data retrieved from a data source in response to a search request, the document ranking application comprising: a term frequency module to: query the data source to identify a plurality of documents that each comprises a key term, the key term matching a search term in the search request; and determine a corresponding term frequency value for the key term in each of the plurality of documents, the term frequency value comprising a total number of occurrences of the key term in a particular document; a negation module to: retrieve at least one negation term from a memory; compare the at least one negation term to other terms included in each document that are within a selected proximity of each occurrence of the key term to determine if each occurrence of the key term has a negative context; determine that the at least one negation term matches another term within the selected proximity of the particular occurrence of the key term according to the at least one negation rule and exclude a particular occurrence of the key term in at least one document for having the negative context; and determine a corresponding term weight value for the key term in each document based on each occurrence of the key term that has not been excluded; a ranking module to determine a corresponding relevancy ranking value for each document based on the corresponding term frequency value and corresponding term weight value; and a user interface module to generate a list of document data for display, the list identifying each document of the plurality of documents in order based on the corresponding relevancy ranking value of each document. | 18. A non-transitory computer-readable medium encoded with a document ranking application comprising modules executable by a processor and configured to rank document data retrieved from a data source in response to a search request, the document ranking application comprising: a term frequency module to: query the data source to identify a plurality of documents that each comprises a key term, the key term matching a search term in the search request; and determine a corresponding term frequency value for the key term in each of the plurality of documents, the term frequency value comprising a total number of occurrences of the key term in a particular document; a negation module to: retrieve at least one negation term from a memory; compare the at least one negation term to other terms included in each document that are within a selected proximity of each occurrence of the key term to determine if each occurrence of the key term has a negative context; determine that the at least one negation term matches another term within the selected proximity of the particular occurrence of the key term according to the at least one negation rule and exclude a particular occurrence of the key term in at least one document for having the negative context; and determine a corresponding term weight value for the key term in each document based on each occurrence of the key term that has not been excluded; a ranking module to determine a corresponding relevancy ranking value for each document based on the corresponding term frequency value and corresponding term weight value; and a user interface module to generate a list of document data for display, the list identifying each document of the plurality of documents in order based on the corresponding relevancy ranking value of each document. 19. The non-transitory computer-readable medium of claim 18 wherein the at least one negation term comprises at least one prefix negation term and at least one suffix negation term. | 0.939546 |
9,965,810 | 1 | 19 | 1. A computer-implemented method for automatically preparing at least a portion of an electronic tax return, the method, comprising: a computer, by programmed instructions of a computerized tax return preparation application stored in a data store and executed by a processor of the computer, receiving data of an account of a computerized accounting application that is not utilized to prepare or file an electronic tax return, the account data comprising: an account name, and an account value associated with the account name and at least one transaction; the computer, by the computerized tax return preparation application, accessing a computer-generated spreadsheet comprising a plurality of rows including respective account name search terms and a plurality of columns including a first column having one or more search terms, a second column having one or more tax categories, and a third column having one or more references to a line of a tax form of the tax preparation application, and searching the computerized spreadsheet; the computer, by the computerized tax return preparation application, identifying a search term in the computerized spreadsheet matching the received account name; the computer, by the computerized tax return preparation application, determining a tax category corresponding to the received account name based at least in part upon the identified search term in the computerized spreadsheet; the computer, by the computerized tax return preparation application, automatically assigning a line of an electronic form of the electronic tax return to the account based at least in part upon the determined tax category, wherein the assigned line of the electronic form prepared by the tax return preparation application is to be populated with the account value; and the computer, by the computerized tax return preparation application, populating at least a portion of the electronic tax return by populating the assigned line of the electronic form with the account value. | 1. A computer-implemented method for automatically preparing at least a portion of an electronic tax return, the method, comprising: a computer, by programmed instructions of a computerized tax return preparation application stored in a data store and executed by a processor of the computer, receiving data of an account of a computerized accounting application that is not utilized to prepare or file an electronic tax return, the account data comprising: an account name, and an account value associated with the account name and at least one transaction; the computer, by the computerized tax return preparation application, accessing a computer-generated spreadsheet comprising a plurality of rows including respective account name search terms and a plurality of columns including a first column having one or more search terms, a second column having one or more tax categories, and a third column having one or more references to a line of a tax form of the tax preparation application, and searching the computerized spreadsheet; the computer, by the computerized tax return preparation application, identifying a search term in the computerized spreadsheet matching the received account name; the computer, by the computerized tax return preparation application, determining a tax category corresponding to the received account name based at least in part upon the identified search term in the computerized spreadsheet; the computer, by the computerized tax return preparation application, automatically assigning a line of an electronic form of the electronic tax return to the account based at least in part upon the determined tax category, wherein the assigned line of the electronic form prepared by the tax return preparation application is to be populated with the account value; and the computer, by the computerized tax return preparation application, populating at least a portion of the electronic tax return by populating the assigned line of the electronic form with the account value. 19. The method of claim 1 , wherein multiple tax categories are determined by the tax return preparation application to correspond to the account name, the method further comprising the computer, by the computerized tax return preparation application, requesting user input to manually select one tax category as corresponding to the account name through an interview screen presented through a display of the computer. | 0.677196 |
9,558,743 | 1 | 9 | 1. A computer-implemented method comprising: receiving, by a computer system, a request to predict a next word to occur in a phrase being uttered by a first user in a dialog between the first user and a second user; accessing, by the computer system, a neural network comprising i) an input layer that includes a first portion representing a local context for the phrase and a second portion representing a semantic context for the phrase, ii) one or more hidden layers that are at least partially interconnected with the input layer by first connections, and iii) an output layer that represents a vocabulary of candidate words and that is at least partially interconnected with at least one of the one or more hidden layers by second connections; identifying, by the computer system, the local context for the phrase being uttered by the first user; identifying, by the computer system, text of one or more previous messages communicated (i) between the first user and the second user, and (ii) before initiation of the dialog between the first user and the second user; determining, by the computer system and based at least on the identified text of the one or more previous messages, at least one vector that represent the semantic context for the phrase, the at least one vector including values for a plurality of dimensions; applying, by the computer system, input to the input layer of the neural network, the input comprising i) the local context of the phrase and ii) the values for the plurality of dimensions of the at least one vector that represents the semantic context of the phrase; generating, by the computer system, probability values for at least a portion of the candidate words in the vocabulary of the output layer based on propagation of the input through the neural network using, at least, the first connections and the second connections between layers of the neural network; using, by the computer system, the generated probability values to determine a transcription for the phrase uttered by the first user; and providing, by the computer system and as output of an automated speech recognizer, the transcription determined using the generated probability values. | 1. A computer-implemented method comprising: receiving, by a computer system, a request to predict a next word to occur in a phrase being uttered by a first user in a dialog between the first user and a second user; accessing, by the computer system, a neural network comprising i) an input layer that includes a first portion representing a local context for the phrase and a second portion representing a semantic context for the phrase, ii) one or more hidden layers that are at least partially interconnected with the input layer by first connections, and iii) an output layer that represents a vocabulary of candidate words and that is at least partially interconnected with at least one of the one or more hidden layers by second connections; identifying, by the computer system, the local context for the phrase being uttered by the first user; identifying, by the computer system, text of one or more previous messages communicated (i) between the first user and the second user, and (ii) before initiation of the dialog between the first user and the second user; determining, by the computer system and based at least on the identified text of the one or more previous messages, at least one vector that represent the semantic context for the phrase, the at least one vector including values for a plurality of dimensions; applying, by the computer system, input to the input layer of the neural network, the input comprising i) the local context of the phrase and ii) the values for the plurality of dimensions of the at least one vector that represents the semantic context of the phrase; generating, by the computer system, probability values for at least a portion of the candidate words in the vocabulary of the output layer based on propagation of the input through the neural network using, at least, the first connections and the second connections between layers of the neural network; using, by the computer system, the generated probability values to determine a transcription for the phrase uttered by the first user; and providing, by the computer system and as output of an automated speech recognizer, the transcription determined using the generated probability values. 9. The computer-implemented method of claim 1 , wherein the at least one vector that represents the semantic context for the phrase comprises at least one vector generated using a latent dirichlet allocation (LDA) model. | 0.831029 |
10,133,736 | 10 | 11 | 10. The computer program product of claim 9 , further comprising program code executable by a processing unit to assign the match to the replaced anaphora in the created sentence structure. | 10. The computer program product of claim 9 , further comprising program code executable by a processing unit to assign the match to the replaced anaphora in the created sentence structure. 11. The computer program product of claim 10 , wherein the sentence structure with the assigned match is a solved analogy association. | 0.95318 |
6,018,742 | 11 | 12 | 11. A method of constructing a context-dependent view of database information in a database including a context-dependent table and a context-independent table, the method including the steps of: identifying a field of a record to be retrieved as being either context-dependent or context-independent; and if the field is context-dependent, then retrieving database information for the field exclusively from a column associated with the field in a context-dependent table without reference to a column associated with a field in the context-independent table. | 11. A method of constructing a context-dependent view of database information in a database including a context-dependent table and a context-independent table, the method including the steps of: identifying a field of a record to be retrieved as being either context-dependent or context-independent; and if the field is context-dependent, then retrieving database information for the field exclusively from a column associated with the field in a context-dependent table without reference to a column associated with a field in the context-independent table. 12. The method of claim 11 including the step of, if the field is context-independent, then retrieving the database information for the field exclusively from a context-independent table. | 0.721726 |
8,762,857 | 1 | 17 | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. 17. The portable dataport of claim 1 , further comprising a photograph taking means. | 0.971755 |
8,417,526 | 7 | 8 | 7. A speech optimizing system comprising: (I) a stimulus data package receiver for receiving a first stimulus data package including one or more spoken utterances comprising at least one phoneme transmitted from a speech receiving device and contextual information relating to a state in which the one or more utterances is spoken; (II) a result data package retriever for retrieving a plurality of first result data packages including a plurality of stored spoken utterances and stored contextual information associated with the plurality of stored spoken utterances relating to a state in which the utterance was spoken; (III) at least one stimulus data package generator for: determining whether the first stimulus data package at least partially requires improvement, based on at least one of the plurality of retrieved first result data packages; and generating a second stimulus data package based on the determination of whether the first stimulus data package at least partially requires improvement, the second stimulus data package including contextual information relating to a state in which the one or more utterances is spoken, at least some of which contextual information is a of different type than the contextual information included in the first stimulus data package; (IV) at least one speech improvement processor for: receiving a plurality of first speech recognition implementation rules for implementing the second stimulus data package, the plurality of first speech recognition implementation rules being associated with the contextual information; and determining whether the second stimulus data package at least partially requires further improvement based at least in part on one or more of the plurality of first speech recognition implementation rules, wherein the one or more of the plurality of first speech recognition implementation rules are based on the contextual information of the second stimulus data package; and (V) an implementation rules generator for generating, based on the determination from the speech improvement processor, one or more second speech recognition implementation rules for improved speech recognition. | 7. A speech optimizing system comprising: (I) a stimulus data package receiver for receiving a first stimulus data package including one or more spoken utterances comprising at least one phoneme transmitted from a speech receiving device and contextual information relating to a state in which the one or more utterances is spoken; (II) a result data package retriever for retrieving a plurality of first result data packages including a plurality of stored spoken utterances and stored contextual information associated with the plurality of stored spoken utterances relating to a state in which the utterance was spoken; (III) at least one stimulus data package generator for: determining whether the first stimulus data package at least partially requires improvement, based on at least one of the plurality of retrieved first result data packages; and generating a second stimulus data package based on the determination of whether the first stimulus data package at least partially requires improvement, the second stimulus data package including contextual information relating to a state in which the one or more utterances is spoken, at least some of which contextual information is a of different type than the contextual information included in the first stimulus data package; (IV) at least one speech improvement processor for: receiving a plurality of first speech recognition implementation rules for implementing the second stimulus data package, the plurality of first speech recognition implementation rules being associated with the contextual information; and determining whether the second stimulus data package at least partially requires further improvement based at least in part on one or more of the plurality of first speech recognition implementation rules, wherein the one or more of the plurality of first speech recognition implementation rules are based on the contextual information of the second stimulus data package; and (V) an implementation rules generator for generating, based on the determination from the speech improvement processor, one or more second speech recognition implementation rules for improved speech recognition. 8. The speech optimizing system of claim 7 wherein system component (III) comprises: a first stimulus data package generator for determining whether the first stimulus data package at least partially requires improvement, based on at least one of the plurality of retrieved first result data packages; and a second stimulus data package generator for generating a second stimulus data package based on the determination of whether the first stimulus data package at least partially requires improvement. | 0.782439 |
9,183,535 | 16 | 28 | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. 28. The non-transitory computer-readable storage medium of claim 16 , wherein the computer program instructions further comprise instructions for performing entity unification between two entities in the user's social network model based on the modified relationship strengths. | 0.747723 |
9,626,353 | 15 | 19 | 15. A system comprising: a data processing apparatus; and a computer-readable medium having instructions stored therein that, when executed by the data processing apparatus, cause the data processing apparatus to: identify a sentence; identify a graph of generalized constituents of the sentence based on rough syntactic analysis of a lexical-morphological structure of the sentence, wherein the graph of generalized constituents comprises arcs and nodes, wherein each of the nodes represents a constituent of the sentence comprising one or more words in the sentence that function as a unit within the sentence, and wherein each of the arcs between a pair of the nodes represents a syntactic slot expressing a type of relationship between lexical values of the pair; filter the arcs of the graph of generalized constituents using a combination classifier comprising a tree classifier and at least one linear classifier, wherein the tree classifier divides the arcs into clusters based on a predetermined set of symbolic features, and wherein the linear classifier filters the clusters of the arcs based on combinations of numerical features for each of the clusters; and identify a syntactic structure of the sentence by performing precise syntactic analysis of the sentence based on the graph of generalized constituents of the sentence with the filtered clusters of the arcs. | 15. A system comprising: a data processing apparatus; and a computer-readable medium having instructions stored therein that, when executed by the data processing apparatus, cause the data processing apparatus to: identify a sentence; identify a graph of generalized constituents of the sentence based on rough syntactic analysis of a lexical-morphological structure of the sentence, wherein the graph of generalized constituents comprises arcs and nodes, wherein each of the nodes represents a constituent of the sentence comprising one or more words in the sentence that function as a unit within the sentence, and wherein each of the arcs between a pair of the nodes represents a syntactic slot expressing a type of relationship between lexical values of the pair; filter the arcs of the graph of generalized constituents using a combination classifier comprising a tree classifier and at least one linear classifier, wherein the tree classifier divides the arcs into clusters based on a predetermined set of symbolic features, and wherein the linear classifier filters the clusters of the arcs based on combinations of numerical features for each of the clusters; and identify a syntactic structure of the sentence by performing precise syntactic analysis of the sentence based on the graph of generalized constituents of the sentence with the filtered clusters of the arcs. 19. The system of claim 15 , wherein an order of symbolic features in the predetermined set of symbolic features is determined based on entropy measures of the symbolic features. | 0.748588 |
9,977,802 | 10 | 13 | 10. One or more computer-readable storage medium comprising computer-executable instructions usable by one or more processors of a computing system, the one or more processors in communication with the one or more computer-readable storage medium, to perform operations to support handling of large string values for a dictionary in memory, the operations comprising: receiving a request to access a large string value, the request comprising a string value; with a separator directory comprising one or more directory separator blocks, at least one of the one or more directory separator blocks comprising separators for multiple dictionary blocks of a dictionary, determining a dictionary block ID associated with the string value, wherein: the multiple dictionary blocks store string values for dictionary compression; a determined dictionary block of the multiple dictionary blocks has the determined dictionary block ID; each of the one or more directory separator blocks stores at least some of the separators; at least a portion of the multiple dictionary blocks store one or more large string values for dictionary compression; the determined dictionary block stores part of a large string value corresponding to the string value of the request and one or more logical pointers for one or more large string blocks comprising a remainder of the large string value; from the determined dictionary block, loaded into memory, accessing a first portion of the requested large string value and one or more logical pointers to at least one of one or more large string blocks containing a remainder of a large string value associated with the string value of the request; loading the first portion of the large string value from the determined dictionary block, and loading the remainder of the large string value by following the one or more logical pointers to load from at least corresponding referenced large string blocks the remainder of the large string value, providing the large string value; storing the loaded large string value into a contiguous memory location, the contiguous memory location comprising an addressable starting memory location having an address; creating a pointer to the starting memory address of the stored large string value; storing the pointer to the large string value; and returning a pointer that can be followed to access the stored large string value in response to the request. | 10. One or more computer-readable storage medium comprising computer-executable instructions usable by one or more processors of a computing system, the one or more processors in communication with the one or more computer-readable storage medium, to perform operations to support handling of large string values for a dictionary in memory, the operations comprising: receiving a request to access a large string value, the request comprising a string value; with a separator directory comprising one or more directory separator blocks, at least one of the one or more directory separator blocks comprising separators for multiple dictionary blocks of a dictionary, determining a dictionary block ID associated with the string value, wherein: the multiple dictionary blocks store string values for dictionary compression; a determined dictionary block of the multiple dictionary blocks has the determined dictionary block ID; each of the one or more directory separator blocks stores at least some of the separators; at least a portion of the multiple dictionary blocks store one or more large string values for dictionary compression; the determined dictionary block stores part of a large string value corresponding to the string value of the request and one or more logical pointers for one or more large string blocks comprising a remainder of the large string value; from the determined dictionary block, loaded into memory, accessing a first portion of the requested large string value and one or more logical pointers to at least one of one or more large string blocks containing a remainder of a large string value associated with the string value of the request; loading the first portion of the large string value from the determined dictionary block, and loading the remainder of the large string value by following the one or more logical pointers to load from at least corresponding referenced large string blocks the remainder of the large string value, providing the large string value; storing the loaded large string value into a contiguous memory location, the contiguous memory location comprising an addressable starting memory location having an address; creating a pointer to the starting memory address of the stored large string value; storing the pointer to the large string value; and returning a pointer that can be followed to access the stored large string value in response to the request. 13. The computer-readable storage medium of claim 10 , wherein a given large string value among the one or more string values is represented using segments that comprise: a first segment specifying a prefix length of a common prefix between the given large string value and its predecessor string value; a second segment specifying a length of a portion of the given large string value; a third segment comprising the portion of the given large string value; a fourth segment specifying zero or more logical pointers to large string pages; a fifth segment specifying number of the logical pointers in the fourth segment; and a sixth segment specifying a total length of the given large string value. | 0.500714 |
8,463,544 | 7 | 8 | 7. The navigation apparatus of claim 1 , wherein: the input unit inputs an address that includes the street name, the building number and a city name; the search unit searches the address from among a plurality of streets recorded as destination search data of the map data, and creates a matched address list; the display control unit displays on the display unit the matched address list of the searched streets from the search unit. | 7. The navigation apparatus of claim 1 , wherein: the input unit inputs an address that includes the street name, the building number and a city name; the search unit searches the address from among a plurality of streets recorded as destination search data of the map data, and creates a matched address list; the display control unit displays on the display unit the matched address list of the searched streets from the search unit. 8. The navigation apparatus of claim 7 , wherein the user selects a desired address from the matched address list and the display control unit displays on the display unit a map of the desired address. | 0.95871 |
9,928,308 | 7 | 8 | 7. A system for dynamically modifying a content item on a per-request basis, the system comprising: a data store for storing content items; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: receiving, from a user device, a content item request that includes context data specifying (i) a set of one or more attributes of a resource on which the content item will be presented and (ii) a set of one or more attributes of a user to which the content item will be presented; in response to receiving the content item request: identifying, from the content items stored in the data store, a given content item to provide in response to the content item request; identifying a set of templates that are eligible for use in generating variations of the given content item; filtering the set of templates based on the one or more attributes of the resource on which the content item will be presented, the filtering including removing, from the set of templates, one or more templates that are not eligible for use in generating content items for presentation with resources having the one or more attributes of the resource on which the content item will be presented; determining, for each particular template from the set of templates, a contextual performance measure that indicates a performance of content items that have been provided using the particular template and in response to content item requests having context data that matches the one or more attributes of the user; selecting, from the set of templates and based on the contextual performance measure of each template in the set of templates, a template for the given content item; creating a different formatted content item by populating the selected template with content for the given content item; and providing, to the user device and for presentation with the resource, the different formatted content item in response to the content item request. | 7. A system for dynamically modifying a content item on a per-request basis, the system comprising: a data store for storing content items; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: receiving, from a user device, a content item request that includes context data specifying (i) a set of one or more attributes of a resource on which the content item will be presented and (ii) a set of one or more attributes of a user to which the content item will be presented; in response to receiving the content item request: identifying, from the content items stored in the data store, a given content item to provide in response to the content item request; identifying a set of templates that are eligible for use in generating variations of the given content item; filtering the set of templates based on the one or more attributes of the resource on which the content item will be presented, the filtering including removing, from the set of templates, one or more templates that are not eligible for use in generating content items for presentation with resources having the one or more attributes of the resource on which the content item will be presented; determining, for each particular template from the set of templates, a contextual performance measure that indicates a performance of content items that have been provided using the particular template and in response to content item requests having context data that matches the one or more attributes of the user; selecting, from the set of templates and based on the contextual performance measure of each template in the set of templates, a template for the given content item; creating a different formatted content item by populating the selected template with content for the given content item; and providing, to the user device and for presentation with the resource, the different formatted content item in response to the content item request. 8. The system of claim 7 , wherein: the context data specifies a combination of the one or more attributes of the resource and the one or more attributes of the user; and the contextual performance measure for the particular template indicates a performance of content items that have been provided using the particular template and in response to content item requests having context data that matches the combination of the one or more attributes of the resource and the one or more attributes of the user. | 0.6 |
8,234,113 | 9 | 12 | 9. An apparatus, comprising a detector device including a detector configured to accept multiple types of input, the multiple types of input comprising a video input, the detector configured to evaluate a person detection classifier to detect a person, the person detection classifier created by: identifying a pool of features from the multiple types of input, the pool of features comprising a first video feature from the video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating the classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature. | 9. An apparatus, comprising a detector device including a detector configured to accept multiple types of input, the multiple types of input comprising a video input, the detector configured to evaluate a person detection classifier to detect a person, the person detection classifier created by: identifying a pool of features from the multiple types of input, the pool of features comprising a first video feature from the video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating the classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature. 12. The apparatus of claim 9 , creation of the person detection classifier comprising defining a second video feature by moving the parent rectangle within the feature rectangle. | 0.624473 |
10,078,411 | 3 | 4 | 3. The computer program product in accordance with claim 1 , the act of detecting a user instruction comprising: an act of detecting a user instruction to move the one or more of the plurality of user interface elements on the canvas. | 3. The computer program product in accordance with claim 1 , the act of detecting a user instruction comprising: an act of detecting a user instruction to move the one or more of the plurality of user interface elements on the canvas. 4. The computer program product in accordance with claim 3 , the method further comprising: an act of detecting that a user is moving the one or more of the plurality of user interface elements; and for each of a plurality of instances during the user's detected moving of the one or more of the plurality of user interface elements, an act of highlighting one or more of the plurality of grid positions so that the highlighted one or more grid positions represents where the one or more of the plurality of user interface elements would be placed on the canvas if the one or more of the plurality of user interface elements were to be dropped at the corresponding instance of the plurality of instances. | 0.890274 |
9,922,088 | 8 | 9 | 8. A system for generating a cardinality estimate, comprising: a memory; and a processor coupled to the memory and configured to: identify a predicate in a query, wherein the predicate is split into a plurality of equivalence classes; generate a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identify spanning trees in the plurality of undirected equivalence graphs; determine a minimum spanning tree of the identified spanning trees; calculate a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and select a query plan corresponding to the cardinality estimate wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by the processor. | 8. A system for generating a cardinality estimate, comprising: a memory; and a processor coupled to the memory and configured to: identify a predicate in a query, wherein the predicate is split into a plurality of equivalence classes; generate a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identify spanning trees in the plurality of undirected equivalence graphs; determine a minimum spanning tree of the identified spanning trees; calculate a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and select a query plan corresponding to the cardinality estimate wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by the processor. 9. The system of claim 8 , wherein an equivalence class in the plurality of equivalence classes shares a set of attributes common to the plurality of tables. | 0.921735 |
9,098,493 | 1 | 9 | 1. A computer implemented method for interpreting sign language, comprising: capturing a scene using a capture device, the scene including a human target; tracking movements of the human target in the scene; detecting one or more gestures of the human target in the scene; comparing the one or more gestures to a library of sign language signs; and determining a match between the one or more gestures and one or more sign by adjusting a probability weight of each sign based on acquired individual profiles of user motion for users, and comparing each probability weight against other signs likely to be assigned to a detected gesture. | 1. A computer implemented method for interpreting sign language, comprising: capturing a scene using a capture device, the scene including a human target; tracking movements of the human target in the scene; detecting one or more gestures of the human target in the scene; comparing the one or more gestures to a library of sign language signs; and determining a match between the one or more gestures and one or more sign by adjusting a probability weight of each sign based on acquired individual profiles of user motion for users, and comparing each probability weight against other signs likely to be assigned to a detected gesture. 9. The computer implemented method of claim 1 further including acquiring individual profiles of user motion for users applying known tendencies to motion and gesture detection for a user to increase the accuracy of gesture detection and sign language translation, and determining a match includes applying known tendencies for the user to motion and gesture detection and grammatical information. | 0.849049 |
8,768,911 | 5 | 6 | 5. The computerized method of claim 4 , further comprising h) receiving at the server computer an indication that the single link to the list of the plurality of quoting web pages has been selected; i) generating at the server computer the list of quoting web pages based on the data stored in the database, the list including a second link to a particular quoting web page; j) receiving at the server computer an indication that the second link to the particular quoting web page has been selected; k) generating a new version of the particular quoting web page distinguishing the quoted text portion quoted in the particular quoting web page and providing a third link to the new version of the quoted web page. | 5. The computerized method of claim 4 , further comprising h) receiving at the server computer an indication that the single link to the list of the plurality of quoting web pages has been selected; i) generating at the server computer the list of quoting web pages based on the data stored in the database, the list including a second link to a particular quoting web page; j) receiving at the server computer an indication that the second link to the particular quoting web page has been selected; k) generating a new version of the particular quoting web page distinguishing the quoted text portion quoted in the particular quoting web page and providing a third link to the new version of the quoted web page. 6. The computerized method of claim 5 , wherein the new version of the particular quoting web page is generated after receiving the indication that the second link has been selected. | 0.938263 |
7,818,179 | 4 | 6 | 4. A device to provide awareness of speech habits of a speaker using the device, comprising: an audio input device; a speech processing system that processes speech input from the speaker through the audio input device, segments in real time speech input from a different speaker through the audio input device, and provides speech processing results; a language analysis system that analyzes the speech processing results output from the speech processing system using pre-specified criteria for identifying a speech habit of the speaker; an alert system that alerts the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented; and a user interface for controlling the device, wherein the speech processing system comprises a word spotting system adapted to analyze the speech input of a user for detecting one or more words or expressions or sounds, if an which are specified in a vocabulary list, in the speech input of the user, and wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. | 4. A device to provide awareness of speech habits of a speaker using the device, comprising: an audio input device; a speech processing system that processes speech input from the speaker through the audio input device, segments in real time speech input from a different speaker through the audio input device, and provides speech processing results; a language analysis system that analyzes the speech processing results output from the speech processing system using pre-specified criteria for identifying a speech habit of the speaker; an alert system that alerts the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented; and a user interface for controlling the device, wherein the speech processing system comprises a word spotting system adapted to analyze the speech input of a user for detecting one or more words or expressions or sounds, if an which are specified in a vocabulary list, in the speech input of the user, and wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. 6. The device of claim 4 , wherein the speech processing system comprises a word spotting system adapted to analyze the speech input of a user for detecting one or more words or expressions or sounds, if any, which are specified in a vocabulary list, in the speech input of the user. | 0.801264 |
9,372,681 | 19 | 20 | 19. A non-transitory computer-readable storage medium having instructions stored thereon, which instructions when executed by one or more microprocessors cause a user's computing device to: register a capability of a first application installed on the user's computing device to process document URLs of a specific type, the first application configured for native operation outside of a web browser on the user's computing device, wherein the web browser on a user's computing device tracks a declaration of a document URL type in a manifest of the first application of the capability of the first application to open a document corresponding to a document URL which conforms to the declared document URL type, and wherein the web browser maintains a registry of document URL types associated with applications including the first application installed on the user's computing device, the document URL types representing types of document URLs that the applications are coded to open or process, the registry of document URLs types being maintained as a table of the declared document URL types registered by the applications; when a navigation event on the user's computing device leads to a navigated-to-document URL that is of the specific type of document URLs registered to the first application on the user's computing device, present a selection dialog permitting the user to select whether the first application should be launched outside the web browser to process the navigated-to-document URL to open the document; and based on the user selection in the selection dialog, redirect the navigated-to-document URL to the first application and launch the application on the user's computing device to open the document corresponding to the navigated-to-document URL by one of using the navigated-to-document URL redirected to the first application to extract the document from the navigated-to-document URL and using the redirected URL as a unique ID to extract the document from a local cache. | 19. A non-transitory computer-readable storage medium having instructions stored thereon, which instructions when executed by one or more microprocessors cause a user's computing device to: register a capability of a first application installed on the user's computing device to process document URLs of a specific type, the first application configured for native operation outside of a web browser on the user's computing device, wherein the web browser on a user's computing device tracks a declaration of a document URL type in a manifest of the first application of the capability of the first application to open a document corresponding to a document URL which conforms to the declared document URL type, and wherein the web browser maintains a registry of document URL types associated with applications including the first application installed on the user's computing device, the document URL types representing types of document URLs that the applications are coded to open or process, the registry of document URLs types being maintained as a table of the declared document URL types registered by the applications; when a navigation event on the user's computing device leads to a navigated-to-document URL that is of the specific type of document URLs registered to the first application on the user's computing device, present a selection dialog permitting the user to select whether the first application should be launched outside the web browser to process the navigated-to-document URL to open the document; and based on the user selection in the selection dialog, redirect the navigated-to-document URL to the first application and launch the application on the user's computing device to open the document corresponding to the navigated-to-document URL by one of using the navigated-to-document URL redirected to the first application to extract the document from the navigated-to-document URL and using the redirected URL as a unique ID to extract the document from a local cache. 20. The non-transitory computer-readable storage medium of claim 19 , wherein the user's computing device on which the application is installed includes a web-based operating system. | 0.728358 |
8,396,709 | 1 | 11 | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. 11. The method of claim 1 , wherein: determining that the docking context indicates docking of the client device with the docking station of the first type comprises determining that the docking station is a vehicle docking station; selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase comprises selecting a set of weighting values associated with a key phrase that is associated with navigation; and selecting at least the first language model of the plurality of language models comprises selecting a language model associated with navigation. | 0.786437 |
7,788,266 | 15 | 30 | 15. A system for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the system comprising: a collection of subsets of content items associated with corresponding strings of one or more unresolved keystrokes for overloaded keys, the subsets of content items being ranked and associated with the content items based on an ordering criteria so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; and a computer memory comprising instructions for causing a computer system to: receive a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items select and present the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receive subsequent unresolved keystrokes from the user and form a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; and select and present the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting and presenting the subset of content items that is associated with the first unresolved keystroke and selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes selects the subset of content items using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. | 15. A system for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the system comprising: a collection of subsets of content items associated with corresponding strings of one or more unresolved keystrokes for overloaded keys, the subsets of content items being ranked and associated with the content items based on an ordering criteria so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; and a computer memory comprising instructions for causing a computer system to: receive a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items select and present the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receive subsequent unresolved keystrokes from the user and form a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; and select and present the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting and presenting the subset of content items that is associated with the first unresolved keystroke and selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes selects the subset of content items using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. 30. The system of claim 15 , wherein at least a portion of the collection of subsets of content items associated with corresponding string of one or more unresolved keystrokes is on said device operated by said user. | 0.77686 |
9,516,058 | 10 | 12 | 10. A system of detecting malicious network behavior by teaching at least one reputation engine to determine whether at least one new domain name is likely to be used for malicious or legitimate uses, the system comprising: at least one reputation engine in communication with at least one hardware processor and at least one database, the at least one reputation engine configured for: obtaining passive domain name system (DNS) query information, wherein the passive DNS query information is obtained using passive DNS collectors; utilizing the passive DNS query information to measure statistical features of known malicious domain names and known legitimate domain names, wherein the statistical features comprise network-based features and/or zone-based features, the network-based features describing how operators who own the at least one domain name and IP addresses the at least one domain name points to are able to allocate their network resources, and the zone-based features measuring a set of related historic domain names (RHDNs) of domain names historically associated with the at least one new domain name; and utilizing the statistical features to determine at least one reputation for the at least one new domain name, by teaching the at least one reputation engine to determine whether the at least one new domain name is likely to be used for malicious or legitimate uses, and thus determine if the network communication is malicious or benign. | 10. A system of detecting malicious network behavior by teaching at least one reputation engine to determine whether at least one new domain name is likely to be used for malicious or legitimate uses, the system comprising: at least one reputation engine in communication with at least one hardware processor and at least one database, the at least one reputation engine configured for: obtaining passive domain name system (DNS) query information, wherein the passive DNS query information is obtained using passive DNS collectors; utilizing the passive DNS query information to measure statistical features of known malicious domain names and known legitimate domain names, wherein the statistical features comprise network-based features and/or zone-based features, the network-based features describing how operators who own the at least one domain name and IP addresses the at least one domain name points to are able to allocate their network resources, and the zone-based features measuring a set of related historic domain names (RHDNs) of domain names historically associated with the at least one new domain name; and utilizing the statistical features to determine at least one reputation for the at least one new domain name, by teaching the at least one reputation engine to determine whether the at least one new domain name is likely to be used for malicious or legitimate uses, and thus determine if the network communication is malicious or benign. 12. The system of claim 10 , wherein the network-based features comprise: border gateway protocol (BGP) features, autonomous system (AS) features, or registration features, or any combination thereof. | 0.502488 |
9,263,045 | 1 | 12 | 1. A computer-implemented method for interacting with content, the computer-implemented method comprising performing computer-implemented operations for: receiving, at a computer, the content from a source; identifying at least one input indicator in the content, the at least one input indicator indicating that the content supports multi-mode input, the input indicator including explicit meta tags, flags, implicit keywords, or form elements, the input indicator associated with a form element; determining a content associated with the form element if the input indicator indicates that the form element supports multi-mode input; determining a type of information to be captured from a plurality of types of information by the computer based on the context for the form element; activating one or more non-textual input devices associated with the computer according to the type of information to be captured; capturing multi-mode input, via the one or more non-textual input devices, for interacting with the content, wherein the multi-mode input includes one or more of camera, speech, and touch input; and converting the multi-mode input to text. | 1. A computer-implemented method for interacting with content, the computer-implemented method comprising performing computer-implemented operations for: receiving, at a computer, the content from a source; identifying at least one input indicator in the content, the at least one input indicator indicating that the content supports multi-mode input, the input indicator including explicit meta tags, flags, implicit keywords, or form elements, the input indicator associated with a form element; determining a content associated with the form element if the input indicator indicates that the form element supports multi-mode input; determining a type of information to be captured from a plurality of types of information by the computer based on the context for the form element; activating one or more non-textual input devices associated with the computer according to the type of information to be captured; capturing multi-mode input, via the one or more non-textual input devices, for interacting with the content, wherein the multi-mode input includes one or more of camera, speech, and touch input; and converting the multi-mode input to text. 12. The method of claim 1 , wherein the multi-mode input includes map information, the map information including a street address having a zip code. | 0.767296 |
9,563,696 | 1 | 7 | 1. A note management system, the system comprising: a device, comprising a sensor configured to generate a first image comprising a first visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a general boundary and recognizable content thereon; and a processing unit comprising: a note recognition module configured to receive, from the sensor, first image data associated with the first image and process the first image data, automatically identify one or more marks associated with one or more of the plurality of physical notes in the first image, determine a location associated with the one or more marks, and use the location to control the sensor to generate a second image comprising a second visual representation of the scene, wherein the second image comprises a zoomed-in image of one or more notes of the plurality of physical notes, the note recognition module further configured to determine the general boundary of one of the plurality of physical notes from the visual representation, a note authentication module configured to authenticate the one of the plurality of physical notes, a note extraction module configured to extract, in response to determining that the one of the plurality of physical notes is authenticated, the recognizable content of the one of the plurality of physical notes from the visual representation based on the determined general boundary of the one of the plurality of physical notes, and a note labeling module configured to label a digital note representing the one of the plurality of physical notes with a category. | 1. A note management system, the system comprising: a device, comprising a sensor configured to generate a first image comprising a first visual representation of a scene having a plurality of physical notes, each of the physical notes comprising a separate physical object having a general boundary and recognizable content thereon; and a processing unit comprising: a note recognition module configured to receive, from the sensor, first image data associated with the first image and process the first image data, automatically identify one or more marks associated with one or more of the plurality of physical notes in the first image, determine a location associated with the one or more marks, and use the location to control the sensor to generate a second image comprising a second visual representation of the scene, wherein the second image comprises a zoomed-in image of one or more notes of the plurality of physical notes, the note recognition module further configured to determine the general boundary of one of the plurality of physical notes from the visual representation, a note authentication module configured to authenticate the one of the plurality of physical notes, a note extraction module configured to extract, in response to determining that the one of the plurality of physical notes is authenticated, the recognizable content of the one of the plurality of physical notes from the visual representation based on the determined general boundary of the one of the plurality of physical notes, and a note labeling module configured to label a digital note representing the one of the plurality of physical notes with a category. 7. The note management system of claim 1 , wherein the note labeling module is configured to automatically label the digital note based on the one or more marks. | 0.71147 |
7,987,088 | 1 | 10 | 1. A domain independent method of creating an ontology comprising: a programmable processor automatically extracting phrases from one or more documents independent of a domain of the one or more documents, wherein said extracting of the phrases further comprises separating a portion of a content of at least some of the extracted phrases based upon barrier characters; the programmable processor extracting core noun phrases from the one or more documents, wherein a plurality of core noun phrases is identified at least in part based on an absence of each of the plurality of core noun phrases from each of an adjective word list, a verb word list, and a barrier word list; the programmable processor extracting links from the one or more documents based at least in part on the plurality of core noun phrases; and the programmable processor generating an ontology in accordance with at least the extracted phrases. | 1. A domain independent method of creating an ontology comprising: a programmable processor automatically extracting phrases from one or more documents independent of a domain of the one or more documents, wherein said extracting of the phrases further comprises separating a portion of a content of at least some of the extracted phrases based upon barrier characters; the programmable processor extracting core noun phrases from the one or more documents, wherein a plurality of core noun phrases is identified at least in part based on an absence of each of the plurality of core noun phrases from each of an adjective word list, a verb word list, and a barrier word list; the programmable processor extracting links from the one or more documents based at least in part on the plurality of core noun phrases; and the programmable processor generating an ontology in accordance with at least the extracted phrases. 10. A method as in claim 1 which includes establishing a frequency indicator for each of the plurality of core noun phrases. | 0.756863 |
10,108,697 | 10 | 16 | 10. A system for event matching by analysis of text characteristics, the system comprising: a processor; a web crawler module coupled to the processor and operable to acquire a document collection comprising a plurality of documents; an initial document grouping module coupled to the processor and operable to identify one or more document subsets of the document collection, each comprising one or more documents, based on one or more structured metadata fields of the documents comprising one or more structured content fields such that two or more documents describing an identical event are grouped in a same document subset, wherein the one or more structured content fields comprise one or more structured content fields an airplane model, time, location, and one or more entities associated with the event; a text feature extraction module coupled to the processor and operable to extract one or more salient text features by at least: determining whether a document in a particular document subset of the one or more document subsets is excluded from combination with other documents in the particular document subset based on the one or more structured metadata fields; after determining that the document in the particular document subset is excluded from combination with other documents in the particular document subset, determining to avoid extracting text features from the document; otherwise, extracting one or more salient text features from documents in the particular document subset by at least: extracting a particular multi-word text feature based on determining that a sequence of words of the particular multi-word text feature occurs relatively frequently given occurrence of individual words in the sequence of words of the particular multi-word text feature, wherein the particular multi-word text feature comprises an aircraft event associated with one of aircraft takeoff, aircraft landing, corrective action, aircraft speed, weather, crew observations, or aircraft subsystem; a normalization module coupled to the processor and operable to determine one or more normalized text features of an aircraft event by at least: converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using one or more regular expressions, and converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using numerical distance and normalizing alphanumeric patterns including numbers and units of measure; a similarity scoring module coupled to the processor and operable to generate an event similarity score for pairs of documents in at least the particular document subset by comparing the one or more normalized text features extracted from the documents in the particular document subset, wherein the event similarity score comprises a weighting of the one or more normalized text features for each pair of the pairs of documents based on a rarity measure measuring word rarity; and a similar document list module coupled to the processor and operable to generate a common event document list comprising sets of documents in the document collection whose event similarity scores with each other are above a similarity threshold for each pair of documents. | 10. A system for event matching by analysis of text characteristics, the system comprising: a processor; a web crawler module coupled to the processor and operable to acquire a document collection comprising a plurality of documents; an initial document grouping module coupled to the processor and operable to identify one or more document subsets of the document collection, each comprising one or more documents, based on one or more structured metadata fields of the documents comprising one or more structured content fields such that two or more documents describing an identical event are grouped in a same document subset, wherein the one or more structured content fields comprise one or more structured content fields an airplane model, time, location, and one or more entities associated with the event; a text feature extraction module coupled to the processor and operable to extract one or more salient text features by at least: determining whether a document in a particular document subset of the one or more document subsets is excluded from combination with other documents in the particular document subset based on the one or more structured metadata fields; after determining that the document in the particular document subset is excluded from combination with other documents in the particular document subset, determining to avoid extracting text features from the document; otherwise, extracting one or more salient text features from documents in the particular document subset by at least: extracting a particular multi-word text feature based on determining that a sequence of words of the particular multi-word text feature occurs relatively frequently given occurrence of individual words in the sequence of words of the particular multi-word text feature, wherein the particular multi-word text feature comprises an aircraft event associated with one of aircraft takeoff, aircraft landing, corrective action, aircraft speed, weather, crew observations, or aircraft subsystem; a normalization module coupled to the processor and operable to determine one or more normalized text features of an aircraft event by at least: converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using one or more regular expressions, and converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using numerical distance and normalizing alphanumeric patterns including numbers and units of measure; a similarity scoring module coupled to the processor and operable to generate an event similarity score for pairs of documents in at least the particular document subset by comparing the one or more normalized text features extracted from the documents in the particular document subset, wherein the event similarity score comprises a weighting of the one or more normalized text features for each pair of the pairs of documents based on a rarity measure measuring word rarity; and a similar document list module coupled to the processor and operable to generate a common event document list comprising sets of documents in the document collection whose event similarity scores with each other are above a similarity threshold for each pair of documents. 16. The system of claim 10 , further comprising a presentation module coupled to the processor and operable to present the common event document list, matching text features, non-matching text features, or a combination thereof. | 0.504348 |
7,882,100 | 1 | 9 | 1. An improved method for optimization of a query requesting data from a database, the method executed by a processor comprising: generating a search space comprising only left deep nested loop join trees for returning data requested by the query; traversing the search space to select an optimal left deep nested loop join tree for execution of the query; after selection of an optimal left deep nested loop join tree including one or more outer joins and/or one or more semi-joins, transforming the selected left deep nested loop join tree into a semantically correct bushy tree structure for returning data requested by the query; and building a query execution plan for returning data requested by the query based on the semantically correct bushy tree structure. | 1. An improved method for optimization of a query requesting data from a database, the method executed by a processor comprising: generating a search space comprising only left deep nested loop join trees for returning data requested by the query; traversing the search space to select an optimal left deep nested loop join tree for execution of the query; after selection of an optimal left deep nested loop join tree including one or more outer joins and/or one or more semi-joins, transforming the selected left deep nested loop join tree into a semantically correct bushy tree structure for returning data requested by the query; and building a query execution plan for returning data requested by the query based on the semantically correct bushy tree structure. 9. The method of claim 1 , further comprising: converting the query into a tree of logical operators. | 0.856941 |
10,083,164 | 17 | 18 | 17. The electronic apparatus of claim 15 , wherein, when the table includes a plurality of rows and a plurality of columns, and a predetermined user command is input to one of a plurality of cells in the table, the at least one computer processor controls the display to display a deletion icon in at least one of up and down and left and right directions of a cell to which the predetermined user command is input, and wherein, when one of the at least one deletion icon is selected, the at least one computer processor deletes a row or a column in direction corresponding to the selected deletion icon on the basis of a cell to which the predetermined user command is input. | 17. The electronic apparatus of claim 15 , wherein, when the table includes a plurality of rows and a plurality of columns, and a predetermined user command is input to one of a plurality of cells in the table, the at least one computer processor controls the display to display a deletion icon in at least one of up and down and left and right directions of a cell to which the predetermined user command is input, and wherein, when one of the at least one deletion icon is selected, the at least one computer processor deletes a row or a column in direction corresponding to the selected deletion icon on the basis of a cell to which the predetermined user command is input. 18. The electronic apparatus of claim 17 , wherein the at least one computer processor controls the display to display a drag icon around the deletion icon, and wherein, when a deletion range is set using the drag icon and one of the at least one deletion icon is selected, the at least one computer processor deletes a plurality of rows or columns included in the deletion range on the basis of a cell to which the predetermined user command is input. | 0.764092 |
9,436,726 | 1 | 22 | 1. A computer-implemented method comprising: translating official sector action non-quantitative text-based data into at least one quantitative risk management tool that electronically anticipates at least one trajectory of at least one official sector cross-border public policy data comprising: receiving electronically, by at least one computer processor, said official sector action non-quantitative text-based data relating to the at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, at least one tag or code relating to said official sector action non quantitative text-based data, comprising: tagging at least one concept electronically, by the at least one computer processor, of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: identifying electronically, by the at least one computer processor, occurrence of a group of words appearing together indicative of a specific concept in said at least one official sector action activity; associating electronically, by the at least one computer processor, said official sector action non-quantitative text-based data with said at least one tag or code, and storing in an electronic computer database; processing electronically, by the at least one computer processor, an algorithmic calculation to obtain the at least one anticipated official sector cross-border public policy data, wherein said algorithmic calculation comprises: linking electronically, by the at least one computer processor, the at least one anticipated official sector cross-border public policy data with said official sector action non-quantitative text-based data and said electronic database; enabling electronically, by the at least one computer processor, a semantic search of said electronic database; extracting electronically, by the at least one computer processor, quantitative data of at least one official sector action activity of the at least one official sector cross-border public policy data from said electronic database, wherein said extracting electronically said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data comprises: identifying electronically, by the at least one computer processor, correlations or covariances between a plurality of said at least one official sector action activity of said at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, said at least one tag or code, and said at least one concept; weighting electronically, by the at least one computer processor, said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: said at least one tag or code, and said at least one concept; a proximity of said at least one official sector action activity to a decision point; and a relative importance of an activity level of said at least one official sector action activity; and anticipating electronically, by the at least one computer processor, the at least one trajectory of the at least one official sector cross-border public policy data of said at least one official sector cross-border public policy based on: said at least one tag or code, and said at least one concept; said identifying electronically of said correlations or covariances, and said weighting electronically based on: said proximity to the deadline, and said relative importance of said activity level; and generating, by the at least one computer processor, at least one graphical representation of said quantitative data and the anticipated at least one trajectory of the at least one official sector cross-border public policy. | 1. A computer-implemented method comprising: translating official sector action non-quantitative text-based data into at least one quantitative risk management tool that electronically anticipates at least one trajectory of at least one official sector cross-border public policy data comprising: receiving electronically, by at least one computer processor, said official sector action non-quantitative text-based data relating to the at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, at least one tag or code relating to said official sector action non quantitative text-based data, comprising: tagging at least one concept electronically, by the at least one computer processor, of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: identifying electronically, by the at least one computer processor, occurrence of a group of words appearing together indicative of a specific concept in said at least one official sector action activity; associating electronically, by the at least one computer processor, said official sector action non-quantitative text-based data with said at least one tag or code, and storing in an electronic computer database; processing electronically, by the at least one computer processor, an algorithmic calculation to obtain the at least one anticipated official sector cross-border public policy data, wherein said algorithmic calculation comprises: linking electronically, by the at least one computer processor, the at least one anticipated official sector cross-border public policy data with said official sector action non-quantitative text-based data and said electronic database; enabling electronically, by the at least one computer processor, a semantic search of said electronic database; extracting electronically, by the at least one computer processor, quantitative data of at least one official sector action activity of the at least one official sector cross-border public policy data from said electronic database, wherein said extracting electronically said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data comprises: identifying electronically, by the at least one computer processor, correlations or covariances between a plurality of said at least one official sector action activity of said at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, said at least one tag or code, and said at least one concept; weighting electronically, by the at least one computer processor, said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: said at least one tag or code, and said at least one concept; a proximity of said at least one official sector action activity to a decision point; and a relative importance of an activity level of said at least one official sector action activity; and anticipating electronically, by the at least one computer processor, the at least one trajectory of the at least one official sector cross-border public policy data of said at least one official sector cross-border public policy based on: said at least one tag or code, and said at least one concept; said identifying electronically of said correlations or covariances, and said weighting electronically based on: said proximity to the deadline, and said relative importance of said activity level; and generating, by the at least one computer processor, at least one graphical representation of said quantitative data and the anticipated at least one trajectory of the at least one official sector cross-border public policy. 22. The method according to claim 1 , wherein said extracting, by the at least one computer processor, of said quantitative data of said official sector action activity of said at least one official sector cross-border public policy data from said official sector action non-quantitative text-based data, comprises: assigning a quantitative value or a numerical value regarding official sector activity levels for at least one of an observation, or an occurrence; aggregating said official sector action activity level over a time period; weighting said official sector action activity level based on an official sector action activity type; and providing analytics regarding said extracted, aggregated, and weighted official sector action activity data in order to anticipate future likely policy trajectories. | 0.798058 |
8,195,468 | 19 | 22 | 19. A method for processing multi-modal natural language inputs, comprising: receiving a multi-modal natural language input at a conversational voice user interface, the multi-modal input including a natural language utterance and a non-speech input provided by a user, wherein a transcription module coupled to the conversational voice user interface transcribes the non-speech input to create a non-speech-based transcription; identifying the user that provided the multi-modal input; creating a speech-based transcription of the natural language utterance using a speech recognition engine and a semantic knowledge-based model, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the conversational voice user interface, a general cognitive model derived from one or more prior interactions between a plurality of users and the conversational voice user interface, and an environmental model derived from an environment of the identified user and the conversational voice user interface; merging the speech-based transcription and the non-speech-based transcription to create a merged transcription; identifying one or more entries in a context stack matching information contained in the merged transcription; determining a most likely context for the multi-modal input based on the identified entries; identifying a domain agent associated with the most likely context for the multi-modal input; communicating a request to the identified domain agent; and generating a response to the user from content provided by the identified domain agent as a result of processing the request. | 19. A method for processing multi-modal natural language inputs, comprising: receiving a multi-modal natural language input at a conversational voice user interface, the multi-modal input including a natural language utterance and a non-speech input provided by a user, wherein a transcription module coupled to the conversational voice user interface transcribes the non-speech input to create a non-speech-based transcription; identifying the user that provided the multi-modal input; creating a speech-based transcription of the natural language utterance using a speech recognition engine and a semantic knowledge-based model, wherein the semantic knowledge-based model includes a personalized cognitive model derived from one or more prior interactions between the identified user and the conversational voice user interface, a general cognitive model derived from one or more prior interactions between a plurality of users and the conversational voice user interface, and an environmental model derived from an environment of the identified user and the conversational voice user interface; merging the speech-based transcription and the non-speech-based transcription to create a merged transcription; identifying one or more entries in a context stack matching information contained in the merged transcription; determining a most likely context for the multi-modal input based on the identified entries; identifying a domain agent associated with the most likely context for the multi-modal input; communicating a request to the identified domain agent; and generating a response to the user from content provided by the identified domain agent as a result of processing the request. 22. The method of claim 19 , wherein the conversational voice user interface supports interactions with the plurality of users during an interleaved session. | 0.827473 |
6,108,676 | 1 | 4 | 1. A document processing apparatus in which structured documents are processed, comprising: a document type holding means for holding information of a plurality of document types; a document holding means for holding a plurality of documents each of which is composed according to any one of the document types held in the document type holding means; a document process designating means for designating a target document type as a target to be processed and process contents to be executed; a document type collating means for constructing finite-state automatons from a content model defining lower elements which can be included in an element of a document type based on the document types held in the document type holding means and for comparing said finite-state automaton of the target document type with finite-state automatons of document types other than the target document type, thereby obtaining related document types having a predetermined relationship with the target document type; and a document process executing means for executing the process instructed by the document process designating means on a document representing the target document type and a document of the related document type which are targets to be processed among the documents held by the document holding means. | 1. A document processing apparatus in which structured documents are processed, comprising: a document type holding means for holding information of a plurality of document types; a document holding means for holding a plurality of documents each of which is composed according to any one of the document types held in the document type holding means; a document process designating means for designating a target document type as a target to be processed and process contents to be executed; a document type collating means for constructing finite-state automatons from a content model defining lower elements which can be included in an element of a document type based on the document types held in the document type holding means and for comparing said finite-state automaton of the target document type with finite-state automatons of document types other than the target document type, thereby obtaining related document types having a predetermined relationship with the target document type; and a document process executing means for executing the process instructed by the document process designating means on a document representing the target document type and a document of the related document type which are targets to be processed among the documents held by the document holding means. 4. The apparatus according to claim 1, wherein the document process designating means gives instructions which includes a relationship with the target document type which should be satisfied by a document type as the target to be processed, and the document type collating means uses the document type having the relationship with the target document type generated by the document process designating means. | 0.825939 |
7,702,997 | 1 | 5 | 1. A method, at least partially implemented on a computer, comprising: presenting at least one table within a document, the table having multiple cells; presenting a free floating field inline with text in the document, wherein the free floating field is integrated into the text, and wherein selecting and applying formatting to the text applies the formatting to the free floating field; overlaying a formula edit box on the free floating field to facilitate entry of a formula into the free floating field, wherein the formula references a cell in the table; automatically recalculating the formula in the free floating field upon modification of the cell in the table; and creating a second free floating field in response to a selection of at least a portion of the text in the document, wherein the second free floating field is configured to contain the selected portion of text. | 1. A method, at least partially implemented on a computer, comprising: presenting at least one table within a document, the table having multiple cells; presenting a free floating field inline with text in the document, wherein the free floating field is integrated into the text, and wherein selecting and applying formatting to the text applies the formatting to the free floating field; overlaying a formula edit box on the free floating field to facilitate entry of a formula into the free floating field, wherein the formula references a cell in the table; automatically recalculating the formula in the free floating field upon modification of the cell in the table; and creating a second free floating field in response to a selection of at least a portion of the text in the document, wherein the second free floating field is configured to contain the selected portion of text. 5. A computer readable medium having computer-executable instructions that, when executed on one or more processors, perform the method as recited in claim 1 . | 0.697719 |
8,401,846 | 8 | 10 | 8. The method of claim 1 , comprising determining, by the client device, whether the response from the remote speech processing system includes a contact telephone number. | 8. The method of claim 1 , comprising determining, by the client device, whether the response from the remote speech processing system includes a contact telephone number. 10. The method of claim 8 , comprising dialing, by the client device, the contact telephone number when the response includes the contact telephone number. | 0.937601 |
8,286,218 | 10 | 11 | 10. An interactive television network comprising: a plurality of programming content, the plurality of programming content provided by a plurality of content from different providers, the plurality of programming content received from multiple video cameras positioned at different locations; at least one server at a production facility that receives the plurality of programming content from the Internet, wherein the production facility manipulates the programming content to create a viewer-customized production; first viewer input received from user computers that are remotely located from the production facility, the first viewer input submitted by multiple first viewers over the Internet to the server at the production facility, wherein the multiple first viewers vote on different portions of the programming content received from the multiple video cameras to select different portions of the programming content received from the multiple video cameras; wherein the multiple first viewers vote on different portions of the music to select desired music from different music from different providers, wherein the different music is composed by the different providers; different audio commentaries about the programming content from different providers, wherein the different audio commentaries represent different points of view; second viewer input that selects a desired commentary from the different audio commentaries, wherein the server is configured to combine the selected different portions of the programming content from the multiple video cameras and the desired music based on the first viewer input with the desired commentary based on the second viewer input , and wherein the viewer-customized production is viewed over the Internet by at least the second viewer; wherein the server is further configured to track usage of items included in the viewer-customized production, the items comprising the programming content and music selected with the first viewer input, and the desired commentary selected with the second viewer input; wherein the server is further configured to track which of the different providers provided the programming content, which of the different providers provided the desired commentary, and which of the different providers provided the desired music included in the viewer-customized production; and wherein the server is further configured to pay the different providers that provided the programming content, the desired music and the desired commentary a share of revenues associated with the viewer-customized production. | 10. An interactive television network comprising: a plurality of programming content, the plurality of programming content provided by a plurality of content from different providers, the plurality of programming content received from multiple video cameras positioned at different locations; at least one server at a production facility that receives the plurality of programming content from the Internet, wherein the production facility manipulates the programming content to create a viewer-customized production; first viewer input received from user computers that are remotely located from the production facility, the first viewer input submitted by multiple first viewers over the Internet to the server at the production facility, wherein the multiple first viewers vote on different portions of the programming content received from the multiple video cameras to select different portions of the programming content received from the multiple video cameras; wherein the multiple first viewers vote on different portions of the music to select desired music from different music from different providers, wherein the different music is composed by the different providers; different audio commentaries about the programming content from different providers, wherein the different audio commentaries represent different points of view; second viewer input that selects a desired commentary from the different audio commentaries, wherein the server is configured to combine the selected different portions of the programming content from the multiple video cameras and the desired music based on the first viewer input with the desired commentary based on the second viewer input , and wherein the viewer-customized production is viewed over the Internet by at least the second viewer; wherein the server is further configured to track usage of items included in the viewer-customized production, the items comprising the programming content and music selected with the first viewer input, and the desired commentary selected with the second viewer input; wherein the server is further configured to track which of the different providers provided the programming content, which of the different providers provided the desired commentary, and which of the different providers provided the desired music included in the viewer-customized production; and wherein the server is further configured to pay the different providers that provided the programming content, the desired music and the desired commentary a share of revenues associated with the viewer-customized production. 11. The network of claim 10 , wherein the first viewer input comprises at least one of a vote, survey results, talent scouting, sharing the customized production, recommending, critiquing, requesting similar programming, responding to advertising, pausing, rewinding, fast forwarding, blocking, and an Internet Protocol address of the viewer. | 0.875817 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.