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9,667,627 | 11 | 17 | 11. A method for decrypting user information encrypted on a storage device associated with an identity document of a user, the method comprising: collecting, at a server, user identity document data from the user; constructing, at the server, a token comprising the user identity document data; reading, at a mobile device comprising a reader, the user identity document data from the token by radio frequency identification communication, using the user identity document data read from the token to decrypt the user information stored on said storage device and reading, by radio frequency identification communication, a user identity document biometric facial image from said storage device using the user identity document data; capturing, at a camera, an image of the user's face; comparing, at a comparator, the captured image of the user's face with the user identity document biometric facial image read from the user identity document; and authenticating, at an authentication means, the user depending upon the result of the comparison. | 11. A method for decrypting user information encrypted on a storage device associated with an identity document of a user, the method comprising: collecting, at a server, user identity document data from the user; constructing, at the server, a token comprising the user identity document data; reading, at a mobile device comprising a reader, the user identity document data from the token by radio frequency identification communication, using the user identity document data read from the token to decrypt the user information stored on said storage device and reading, by radio frequency identification communication, a user identity document biometric facial image from said storage device using the user identity document data; capturing, at a camera, an image of the user's face; comparing, at a comparator, the captured image of the user's face with the user identity document biometric facial image read from the user identity document; and authenticating, at an authentication means, the user depending upon the result of the comparison. 17. The method according to claim 11 wherein constructing the token comprises constructing a boarding pass. | 0.788538 |
9,142,213 | 1 | 4 | 1. A method executed on a computer for generating a vocal interface code for a software application, said method comprising: receiving in a computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyzing the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model. | 1. A method executed on a computer for generating a vocal interface code for a software application, said method comprising: receiving in a computer system an entity-relationship data model of said software application, said entity-relationship data model describing data of said software application and including classes, class attributes, and relations between classes; and analyzing the entity-relationship data model to automatically produce code of a voice-enabled wizard for acquiring by user interaction one or more values of respective class attributes of classes described in said entity-relationship data model, said code of the voice-enabled wizard being expressed in a dialog-oriented language, said code of the voice-enabled wizard being produced by: collect all the classes in the data model and loop on all the classes collected; and for each class read from the entity-relationship model, identified as being neither a class used for an interface of the software application nor an abstract class, creating, from the class descriptions of the entity-relationship model, a structure of a dialog unit code as a respective form in said dialog-oriented language for acquisition of values for the corresponding attributes of the respective class; collect all the attributes of the current class and its ancestors and loops on all the attributes; and for each attribute of an identified class read from the entity-relationship model, if the identified class has a single relationship to one other class or if the identified class has a multiple relationship to other classes but the multiple relation does not apply to the respective attribute, creating in the dialog unit code corresponding to the identified class, code in said dialog-oriented language for a direct acquisition of value for the respective attribute else, creating in the dialog unit code, a sub-dialog code in said dialog-oriented language for enabling selection of a dialog unit code of the other classes; and for each form created in said dialog-oriented language, identifying whether the created form is an entry form or an internal form by reading the relationships associated to the corresponding class in the entity-relationship model, and adding the created form to the voice-enabled wizard as an entry form or as an internal form according to the identification; wherein creating in the dialog unit code, code for a direct acquisition of value for the attribute comprises: create a prompt code for direct acquisition fo value for the attribute; read the attribute type form the entity-relationship model. 4. The method of claim 1 , wherein the acts are executed reading an entity-relationship model which is a UML class diagram. | 0.919185 |
10,146,421 | 1 | 7 | 1. A method comprising: displaying, on a web browser interface of a client device, a first web page representing a first document, wherein the first document as displayed includes a transporter component, the transporter component comprising references to a plurality of additional documents; determining that a particular reference to one of the additional documents has been selected; in response to determining that the particular reference has been selected, requesting and receiving a second document from a server device, wherein the second document is associated with the particular reference; and displaying, on the web browser interface of the client device, a representation of the second document, wherein when the second document is associated with the first document by a continuous scrolling feature, the web browser interface displays a modified version of the first web page with the first document followed by the second document, and wherein when the second document is not associated with the first document by the continuous scrolling feature, the web browser interface displays a second web page including the second document but not including the first document. | 1. A method comprising: displaying, on a web browser interface of a client device, a first web page representing a first document, wherein the first document as displayed includes a transporter component, the transporter component comprising references to a plurality of additional documents; determining that a particular reference to one of the additional documents has been selected; in response to determining that the particular reference has been selected, requesting and receiving a second document from a server device, wherein the second document is associated with the particular reference; and displaying, on the web browser interface of the client device, a representation of the second document, wherein when the second document is associated with the first document by a continuous scrolling feature, the web browser interface displays a modified version of the first web page with the first document followed by the second document, and wherein when the second document is not associated with the first document by the continuous scrolling feature, the web browser interface displays a second web page including the second document but not including the first document. 7. The method of claim 1 , wherein displaying the first web page comprises constructing a document object model representation of the first document, and wherein displaying the modified version of the first web page comprises modifying the document object model to represent at least some of the second document. | 0.871605 |
7,912,848 | 5 | 6 | 5. An apparatus, comprising: a processor; and program code configured to be executed by the processor to manage a statement pool by identifying, from among a plurality of statements in a statement pool utilized by a database, a statement that requests data in a first format from a field in the database that stores the data in a second format, and modifying the identified statement in the statement pool to instruct the database to convert the data to the first format prior to returning the data, wherein the program code is further configured to track usage of at least a subset of the plurality of statements, and to modify the identified statement based upon the tracked usage, and wherein the program code is configured to track usage by tracking at least one of a number of times and a last time that each of the subset of statements is used. | 5. An apparatus, comprising: a processor; and program code configured to be executed by the processor to manage a statement pool by identifying, from among a plurality of statements in a statement pool utilized by a database, a statement that requests data in a first format from a field in the database that stores the data in a second format, and modifying the identified statement in the statement pool to instruct the database to convert the data to the first format prior to returning the data, wherein the program code is further configured to track usage of at least a subset of the plurality of statements, and to modify the identified statement based upon the tracked usage, and wherein the program code is configured to track usage by tracking at least one of a number of times and a last time that each of the subset of statements is used. 6. The apparatus of claim 5 , wherein the program code is further configured to associate with the modified statement a usage statistic generated for the statement. | 0.753012 |
8,533,177 | 1 | 5 | 1. A system for retrieving data from a plurality of data sources, said system comprising: a first data source for storing first data; a second data source for storing second data; and a server computing device in communication with the first data source and the second data source, the server computing device programmed to: receive a query execution request comprising a query definition reference and a query parameter definition, wherein the query definition reference corresponds to a query definition that includes a first query block and a second query block; create a first executable query based on the first query block and the query parameter definition; create a second executable query based on the second query block and the query parameter definition; determine an amount of data each of the first executable query and the second executable query are known to access; assign a priority level to each of the first executable query and the second executable query based on the determined amount of data each of the first executable query and the second executable query are known to access; and concurrently execute the first executable query at the first data source to create first query results and the second executable query at the second data source to create second query results based on the assigned priority level of the first executable query and the second executable query. | 1. A system for retrieving data from a plurality of data sources, said system comprising: a first data source for storing first data; a second data source for storing second data; and a server computing device in communication with the first data source and the second data source, the server computing device programmed to: receive a query execution request comprising a query definition reference and a query parameter definition, wherein the query definition reference corresponds to a query definition that includes a first query block and a second query block; create a first executable query based on the first query block and the query parameter definition; create a second executable query based on the second query block and the query parameter definition; determine an amount of data each of the first executable query and the second executable query are known to access; assign a priority level to each of the first executable query and the second executable query based on the determined amount of data each of the first executable query and the second executable query are known to access; and concurrently execute the first executable query at the first data source to create first query results and the second executable query at the second data source to create second query results based on the assigned priority level of the first executable query and the second executable query. 5. The system of claim 1 , wherein the query execution request further comprises an execution schedule that includes a plurality of execution times, and the server computing device is further programmed to execute the first executable query and the second executable query at a first execution time of the plurality of execution times. | 0.860533 |
9,208,236 | 1 | 2 | 1. A method for identifying queries having version-intents and presenting relevant search results in accordance with such version-intents, the method comprising: receiving a search query; determining that at least a portion of the search query has a version-intent indicative of a particular subject-version associated with a subject of the search query, the determining comprising: comparing terms of the search query with information stored in a query store; determining that that the compared terms of the search query has a version-intent stored in the query store; and identifying the particular subject version for the version-intent stored in the query store; presenting a plurality of search results that are ranked for presentation, at least in part, based on the particular subject-version indicated by the version-intent, the presenting comprising ranking the plurality of search results based on subject-version tags associated with the particular subject-version; and presenting a user-manipulatable tool, manipulation of which permits a user to change the version-intent to be indicative of a subject-version associated with the subject of the search query other than the particular subject-version. | 1. A method for identifying queries having version-intents and presenting relevant search results in accordance with such version-intents, the method comprising: receiving a search query; determining that at least a portion of the search query has a version-intent indicative of a particular subject-version associated with a subject of the search query, the determining comprising: comparing terms of the search query with information stored in a query store; determining that that the compared terms of the search query has a version-intent stored in the query store; and identifying the particular subject version for the version-intent stored in the query store; presenting a plurality of search results that are ranked for presentation, at least in part, based on the particular subject-version indicated by the version-intent, the presenting comprising ranking the plurality of search results based on subject-version tags associated with the particular subject-version; and presenting a user-manipulatable tool, manipulation of which permits a user to change the version-intent to be indicative of a subject-version associated with the subject of the search query other than the particular subject-version. 2. The method of claim 1 , wherein determining that the at least a portion of the search query has the version-intent indicative of the particular subject-version associated with the subject of the search query comprises determining that the search query contains at least one query string that explicitly indicates the particular subject-version. | 0.635504 |
8,078,629 | 19 | 25 | 19. A computer system comprising: one or more memories configured for storing executable instructions; and one or more processors configured for executing the instructions, wherein the instructions include instructions to: determine, for a document that contains a first phrase, an expected number of related phrases that are related to the first phrase and are expected to be present in the document; determine for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identify the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the expected number of related phrases includes: traversing an index of a plurality of documents; for each of the indexed documents, determining a set of phrases in the document, and for each phrase in the set, determining a number of related phrases also in the document; and determining the expected number of related phrases based on the determined number of related phrases across the traversed documents. | 19. A computer system comprising: one or more memories configured for storing executable instructions; and one or more processors configured for executing the instructions, wherein the instructions include instructions to: determine, for a document that contains a first phrase, an expected number of related phrases that are related to the first phrase and are expected to be present in the document; determine for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identify the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the expected number of related phrases includes: traversing an index of a plurality of documents; for each of the indexed documents, determining a set of phrases in the document, and for each phrase in the set, determining a number of related phrases also in the document; and determining the expected number of related phrases based on the determined number of related phrases across the traversed documents. 25. The computer system of claim 19 , wherein the instructions to identify the document as a spam document include instructions to: identify the document as a spam document when the actual number of related phrases present in the document exceeds a predetermined maximum expected number of related phrases. | 0.853589 |
8,396,883 | 10 | 13 | 10. A data warehouse that includes a non-transitory computer readable medium on which is encoded computer programming code executed by a computer processor to receive a spatial query and return a spatial result for the spatial query, the data warehouse comprises: a regular database operating to receive and process a regular query and return a query result in response to the regular query; and an interface layer implemented external to the regular database and operating to intercept the spatial query and translate the spatial query into the regular query for processing by the regular database, wherein the translating the spatial query into the regular query comprises: mapping a virtual feature table (VFT) to regular tables, wherein the VFT includes at least one spatial data type found in the spatial query, and the regular tables include at least one regular data type that corresponds with the at least one spatial data type in the VFT; wherein the regular database includes at least one spatial index that is accessed by the interface layer to translate the spatial query into the regular query for processing by the regular database and wherein the interface layer organizes and translates the query result into a geometric data type if the query result was from the intercepted spatial query. | 10. A data warehouse that includes a non-transitory computer readable medium on which is encoded computer programming code executed by a computer processor to receive a spatial query and return a spatial result for the spatial query, the data warehouse comprises: a regular database operating to receive and process a regular query and return a query result in response to the regular query; and an interface layer implemented external to the regular database and operating to intercept the spatial query and translate the spatial query into the regular query for processing by the regular database, wherein the translating the spatial query into the regular query comprises: mapping a virtual feature table (VFT) to regular tables, wherein the VFT includes at least one spatial data type found in the spatial query, and the regular tables include at least one regular data type that corresponds with the at least one spatial data type in the VFT; wherein the regular database includes at least one spatial index that is accessed by the interface layer to translate the spatial query into the regular query for processing by the regular database and wherein the interface layer organizes and translates the query result into a geometric data type if the query result was from the intercepted spatial query. 13. The data warehouse of claim 10 , wherein the regular database is a parallel database that provides a partitioning of regular data for use to provide the regular result and index data of the spatial index such that each portion of the regular data and said each portion's corresponding index data is partition to a same node in the parallel database. | 0.530585 |
9,069,861 | 2 | 8 | 2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. | 2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. 8. The query generation system of claim 2 , wherein the query generation system is further operable to store the generated query in a memory for use at a later time. | 0.721284 |
8,533,194 | 2 | 3 | 2. An electronic document analysis method using a processor for analyzing N electronic documents, the method comprising: performing at least a portion of a first computerized text-classifier based document categorization process on the N electronic documents, using a first computerized text-classifier, thereby to generate at least one output; and using said at least one output to perform at least a second computerized text-classifier based document categorization process on at least M additional electronic documents, wherein said using comprises applying the first computerized text-classifier based document categorization process to at least the M additional electronic documents, only if the processor has determined that the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and otherwise, applying a document categorization process which is not based on the first computerized text-classifier based document categorization process, to at least the M additional electronic documents, wherein a single set, X, of control documents is used: both to make a first determination of whether or not the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and also to make a second determination of whether or not said document categorization process which is applied to said M additional electronic documents and which is not based on the first computerized text-classifier based document, satisfies a predetermined categorization quality criterion, thereby to utilize a single categorization process applied to said single set X rather than conducting separate, first and second, categorization processes on separate, first and second, control sets to be used when making said first and second determinations respectively. | 2. An electronic document analysis method using a processor for analyzing N electronic documents, the method comprising: performing at least a portion of a first computerized text-classifier based document categorization process on the N electronic documents, using a first computerized text-classifier, thereby to generate at least one output; and using said at least one output to perform at least a second computerized text-classifier based document categorization process on at least M additional electronic documents, wherein said using comprises applying the first computerized text-classifier based document categorization process to at least the M additional electronic documents, only if the processor has determined that the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and otherwise, applying a document categorization process which is not based on the first computerized text-classifier based document categorization process, to at least the M additional electronic documents, wherein a single set, X, of control documents is used: both to make a first determination of whether or not the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and also to make a second determination of whether or not said document categorization process which is applied to said M additional electronic documents and which is not based on the first computerized text-classifier based document, satisfies a predetermined categorization quality criterion, thereby to utilize a single categorization process applied to said single set X rather than conducting separate, first and second, categorization processes on separate, first and second, control sets to be used when making said first and second determinations respectively. 3. A method according to claim 2 wherein said performing includes completing the first computerized text-classifier based document categorization process on the N electronic documents and only subsequently performing said second computerized text-classifier based document categorization process on the N+M electronic documents. | 0.761281 |
9,116,548 | 2 | 4 | 2. A computer-implemented method, comprising: storing, at an input method editor server, one or more user profiles for an input method editor, each of the one or more user profiles corresponding to a particular user and including user composition data utilized to modify behavior of the input method editor for the particular user, wherein the user composition data for the particular user comprises data defined by behavior of the particular user including at least one of (i) user-generated words associated with the particular user and (ii) typing patterns associated with the particular user; receiving, at the input method editor server, a notification of an input method editor user instantiation from a client computer device associated with a first user, the notification of the input method editor user instantiation including a user identifier corresponding to the first user; identifying, at the input method editor server, a first user profile of the one or more user profiles corresponding to the first user based on the input method editor user instantiation; providing, from the input method editor server, the first user profile to the input method editor user instantiation on the client device, wherein user composition data of the first user profile is usable by the input method editor user instantiation on the client device to modify behavior of the input method editor user instantiation to be tailored for the first user; receiving, at the input method editor server, an updated first user profile for the first user from the client computer device, the updated first user profile including updated user composition data related to behavior of the first user and the input method editor user instantiation; and storing, at the input method editor server, the updated first user profile as the first user profile. | 2. A computer-implemented method, comprising: storing, at an input method editor server, one or more user profiles for an input method editor, each of the one or more user profiles corresponding to a particular user and including user composition data utilized to modify behavior of the input method editor for the particular user, wherein the user composition data for the particular user comprises data defined by behavior of the particular user including at least one of (i) user-generated words associated with the particular user and (ii) typing patterns associated with the particular user; receiving, at the input method editor server, a notification of an input method editor user instantiation from a client computer device associated with a first user, the notification of the input method editor user instantiation including a user identifier corresponding to the first user; identifying, at the input method editor server, a first user profile of the one or more user profiles corresponding to the first user based on the input method editor user instantiation; providing, from the input method editor server, the first user profile to the input method editor user instantiation on the client device, wherein user composition data of the first user profile is usable by the input method editor user instantiation on the client device to modify behavior of the input method editor user instantiation to be tailored for the first user; receiving, at the input method editor server, an updated first user profile for the first user from the client computer device, the updated first user profile including updated user composition data related to behavior of the first user and the input method editor user instantiation; and storing, at the input method editor server, the updated first user profile as the first user profile. 4. The computer-implemented method of claim 2 , wherein receiving a notification of an input method editor user instantiation comprises receiving an input method editor profile synchronization request. | 0.549327 |
7,672,952 | 9 | 10 | 9. A system according to claim 1 , further comprising a preferred semantic abstract storage to store the first semantic abstract for the content of interest. | 9. A system according to claim 1 , further comprising a preferred semantic abstract storage to store the first semantic abstract for the content of interest. 10. A system according to claim 9 , wherein the preferred semantic abstract storage includes a preferred semantic abstract storage for a community of users. | 0.5 |
9,165,061 | 8 | 11 | 8. The system of claim 1 , wherein the data matrix includes a plurality of numeric values, wherein the plurality of numeric values includes a first numeric value representing terms not associated with the one or more search terms. | 8. The system of claim 1 , wherein the data matrix includes a plurality of numeric values, wherein the plurality of numeric values includes a first numeric value representing terms not associated with the one or more search terms. 11. The system of claim 8 , wherein the first numeric value is zero. | 0.760563 |
7,966,603 | 10 | 11 | 10. A system comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory provide operations comprising: selecting a context from a plurality of contexts associated with a plurality of hierarchical software constructs, the context defining a class of content modules included in a construct of the plurality of hierarchical software constructs; retrieving context data for each content module of a plurality of content modules for each software construct of a plurality of hierarchical software constructs, the context data including a primary context identifier identifying a primary context in which the content module was created or modified, at least one secondary context identifier identifying additional secondary contexts in which the content module is permitted to be included, a restriction identifier identifying a class of contexts in which the content module may be used, and a reference count value indicating a number of times the content module is referenced in the plurality of hierarchical software constructs; determining, based on the primary and the at least one secondary context identifiers, whether each content module is permitted in the selected context; determining the reference count value as the number of times the content module is used in the plurality of hierarchical software constructs; storing the reference count value in association with the context data; identifying the content of the content module as valuable content if the reference count value exceeds a threshold value; generating a collection of content modules from the class of content modules based on the selected context, the collection including the plurality of content modules permitted in the selected context based on the determination; and storing the collection. | 10. A system comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory provide operations comprising: selecting a context from a plurality of contexts associated with a plurality of hierarchical software constructs, the context defining a class of content modules included in a construct of the plurality of hierarchical software constructs; retrieving context data for each content module of a plurality of content modules for each software construct of a plurality of hierarchical software constructs, the context data including a primary context identifier identifying a primary context in which the content module was created or modified, at least one secondary context identifier identifying additional secondary contexts in which the content module is permitted to be included, a restriction identifier identifying a class of contexts in which the content module may be used, and a reference count value indicating a number of times the content module is referenced in the plurality of hierarchical software constructs; determining, based on the primary and the at least one secondary context identifiers, whether each content module is permitted in the selected context; determining the reference count value as the number of times the content module is used in the plurality of hierarchical software constructs; storing the reference count value in association with the context data; identifying the content of the content module as valuable content if the reference count value exceeds a threshold value; generating a collection of content modules from the class of content modules based on the selected context, the collection including the plurality of content modules permitted in the selected context based on the determination; and storing the collection. 11. The system of claim 10 , wherein inclusion of a content module in a secondary context of the additional secondary contexts is dependent upon the primary context. | 0.753731 |
8,655,654 | 3 | 5 | 3. The method of claim 1 , further comprising associating the conversation path with auxiliary data. | 3. The method of claim 1 , further comprising associating the conversation path with auxiliary data. 5. The method of claim 3 , wherein the auxiliary data is a document. | 0.736434 |
8,146,111 | 1 | 6 | 1. A method for making a service implementation accessible for a client application in a service oriented architecture, the method comprising: utilizing a computer to perform: extracting and storing an interface definition language (IDL) file from the service implementation, wherein the service implementation is a pre-existing server program in the service oriented architecture, wherein the IDL file defines interface information to be provided by the client application to access the service implementation during runtime; and extracting and storing a server-side mapping file from the service implementation, wherein the server-side mapping file defines how the interface information provided by the client application is mapped when accessing the service implementation during runtime; wherein the IDL file and the server-side mapping file are used to perform client communication with the service implementation without requiring changes to the pre-existing server program; and wherein said extracting the IDL file and/or extracting the server-side mapping file from the service implementation comprises using an extractor wizard for extracting necessary information for generating the interface definition language file and/or the server-side mapping file, wherein said using the extractor wizard comprises presenting a mapping editor to a user. | 1. A method for making a service implementation accessible for a client application in a service oriented architecture, the method comprising: utilizing a computer to perform: extracting and storing an interface definition language (IDL) file from the service implementation, wherein the service implementation is a pre-existing server program in the service oriented architecture, wherein the IDL file defines interface information to be provided by the client application to access the service implementation during runtime; and extracting and storing a server-side mapping file from the service implementation, wherein the server-side mapping file defines how the interface information provided by the client application is mapped when accessing the service implementation during runtime; wherein the IDL file and the server-side mapping file are used to perform client communication with the service implementation without requiring changes to the pre-existing server program; and wherein said extracting the IDL file and/or extracting the server-side mapping file from the service implementation comprises using an extractor wizard for extracting necessary information for generating the interface definition language file and/or the server-side mapping file, wherein said using the extractor wizard comprises presenting a mapping editor to a user. 6. The method of claim 1 , wherein a remote procedure call server has access to the server-side mapping file in order to call the service implementation using the server-side mapping file during runtime. | 0.773942 |
8,942,488 | 11 | 19 | 11. A system for placing spine groups within a display, comprising: a shape defined within a display; a unique placement module to place groups of cluster spines circumferentially around the defined shape; an overlap module to identify overlap between at least two of the spine groups; a rotation module to rotate one of the overlapping spine groups in one of a clockwise and anticlockwise direction away from the other overlapping spine group; a further overlap module to determine that overlap exists between the rotated spine group and at least one of the other overlapping spine group and another placed spine group; a translation module to move the rotated overlapping spine group in an outward direction away from the shape; and a processor to execute the modules. | 11. A system for placing spine groups within a display, comprising: a shape defined within a display; a unique placement module to place groups of cluster spines circumferentially around the defined shape; an overlap module to identify overlap between at least two of the spine groups; a rotation module to rotate one of the overlapping spine groups in one of a clockwise and anticlockwise direction away from the other overlapping spine group; a further overlap module to determine that overlap exists between the rotated spine group and at least one of the other overlapping spine group and another placed spine group; a translation module to move the rotated overlapping spine group in an outward direction away from the shape; and a processor to execute the modules. 19. A system according to claim 11 , wherein the translation module translates each of the spine groups placed circumferentially around the defined shape to an x-axis where x=0.5×radius r and y=0.0. | 0.813208 |
8,949,359 | 9 | 11 | 9. A computer system, the computer system including: one or more processors; memory; and one or more programs, stored in the memory, for execution by the one or more processors, the one or more programs including instructions for: maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; responding to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. | 9. A computer system, the computer system including: one or more processors; memory; and one or more programs, stored in the memory, for execution by the one or more processors, the one or more programs including instructions for: maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; responding to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. 11. The computer system of claim 9 , the one or more programs further including instructions for maintaining for a subscriber of the computer system a list of conversations to in which the subscriber is a participant, updating a status of each such conversation in the list when a state of the respective conversation changes, and sending to the subscriber a list that comprises at least a portion of the list of conversations in which the subscriber is a participant, the list sent to the subscriber including status information for the listed conversations. | 0.509649 |
8,310,505 | 3 | 5 | 3. The dynamic English graphic playing method of claim 1 , further comprising an executing Step, wherein when the execution Step is defined as Step (B), prior to performing Step (B), a sentence recognition Step (A) is performed, Step (A) comprising Step (A-1) of converting an input sentence into a space and a separate language element, and Step (A-2) of recognizing the converted space and separate language element, comparing the recognized space and separate language element against a data storage unit, separating the compared space and separate language element into a meaningful language element region and a space region surrounding the meaningful language element region, and storing the meaningful language element region and space region, and after the execution of Step B, a sentence reference position moving Step (C) is performed, Step (C) comprising Step (C-) of deleting recognition information on a preceding sentence, and stopping a dynamic graphic conversion, and Step (C-2) of moving reference points of a recognition region and a screen display region such that Step (A) is repetitively performed on a next sentence or a sentence on a next line. | 3. The dynamic English graphic playing method of claim 1 , further comprising an executing Step, wherein when the execution Step is defined as Step (B), prior to performing Step (B), a sentence recognition Step (A) is performed, Step (A) comprising Step (A-1) of converting an input sentence into a space and a separate language element, and Step (A-2) of recognizing the converted space and separate language element, comparing the recognized space and separate language element against a data storage unit, separating the compared space and separate language element into a meaningful language element region and a space region surrounding the meaningful language element region, and storing the meaningful language element region and space region, and after the execution of Step B, a sentence reference position moving Step (C) is performed, Step (C) comprising Step (C-) of deleting recognition information on a preceding sentence, and stopping a dynamic graphic conversion, and Step (C-2) of moving reference points of a recognition region and a screen display region such that Step (A) is repetitively performed on a next sentence or a sentence on a next line. 5. The dynamic English graphic playing method of claim 3 , further comprising converting an image represented on a computer-based display device to a file format capable of being stored in a state of storage at a certain time or in a certain represented state. | 0.813754 |
8,924,415 | 14 | 15 | 14. The apparatus of claim 11 , wherein at least one of the source model, the target model, or the conceptual model are associated with a business object. | 14. The apparatus of claim 11 , wherein at least one of the source model, the target model, or the conceptual model are associated with a business object. 15. The apparatus of claim 14 , wherein the processor is further configured to: receive information indicative of a triggering incident associated with the business object; and in response to the triggering incident, at least one of (i) map the source attribute to the conceptual attribute using the first mapping data, or (ii) map the conceptual attribute to the target attribute using the second mapping data. | 0.5 |
4,829,423 | 3 | 5 | 3. A method for providing executable machine commands to a computer system in accordance with natural language inputs in a predefined natural language subset which has a predefined correspondence to a set of executable machine commands, received from an unskilled user, comprising the steps of: presenting to the user the set of permissible next inputs, which can provide a next word in a permissible natural-language input; repeatedly, as soon as the user designates one of the permissible next inputs presented, cumulatively parsing all words in a current sequence which have been entered by said user, and displaying to said user the set of all possible next words which could form a continuation of a legal input, in accordance with said predefined natural language subset, whereby said unskilled user's choices are constrained to include selection of only legal successive sentence elements, until said user has entered a completed sentence; and then translating said completed sentence into executable machine commands, in accordance with said correspondence therebetween. | 3. A method for providing executable machine commands to a computer system in accordance with natural language inputs in a predefined natural language subset which has a predefined correspondence to a set of executable machine commands, received from an unskilled user, comprising the steps of: presenting to the user the set of permissible next inputs, which can provide a next word in a permissible natural-language input; repeatedly, as soon as the user designates one of the permissible next inputs presented, cumulatively parsing all words in a current sequence which have been entered by said user, and displaying to said user the set of all possible next words which could form a continuation of a legal input, in accordance with said predefined natural language subset, whereby said unskilled user's choices are constrained to include selection of only legal successive sentence elements, until said user has entered a completed sentence; and then translating said completed sentence into executable machine commands, in accordance with said correspondence therebetween. 5. The method of claim 3, further comprising the additional substep, after said user has entered a completed sentence but before said completed sentence in translated into executable machine commands, of: checking said completed sentence, to ascertain whether more than one legal parse of said completed sentence exists, and displaying alternative parses of said sentence to said user for choice therebetween; and then translating said completed sentence into executable machine commands, in accordance with the one of said alternative parses which has been selected by said user. | 0.5 |
9,324,321 | 1 | 3 | 1. A method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), comprising: receiving, by a computing device, at least one utterance comprising a plurality of speech features for one or more speakers from one or more ASR tasks; applying, by the computing device, a decomposition process to two or more matrices in the DNN model; in response to applying the decomposition process, adapting the DNN model to include a decomposed matrix that is generated from decomposition processing of the two or more matrices; and exposing the adapted DNN model as a service. | 1. A method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), comprising: receiving, by a computing device, at least one utterance comprising a plurality of speech features for one or more speakers from one or more ASR tasks; applying, by the computing device, a decomposition process to two or more matrices in the DNN model; in response to applying the decomposition process, adapting the DNN model to include a decomposed matrix that is generated from decomposition processing of the two or more matrices; and exposing the adapted DNN model as a service. 3. The method of claim 1 , wherein the adapting of the DNN model further comprises adding a new layer into the DNN model, wherein the new layer comprises the decomposed matrix a non-linear layer. | 0.627863 |
9,760,622 | 17 | 18 | 17. The method according to claim 12 , further comprising: filling batches, separately for each clusters, including combining first keep-together sets other than small keep-together subsets into batches; and subsequently passing over the batches in an order determined by known urgency and enlarging at least some of the batches by adding the small keep-together subsets thereto, in the order determined by the known urgency. | 17. The method according to claim 12 , further comprising: filling batches, separately for each clusters, including combining first keep-together sets other than small keep-together subsets into batches; and subsequently passing over the batches in an order determined by known urgency and enlarging at least some of the batches by adding the small keep-together subsets thereto, in the order determined by the known urgency. 18. The method according to claim 17 , wherein a small keep-together subset comprises only a single document. | 0.5 |
8,473,489 | 24 | 26 | 24. The computer storage medium of claim 16 , the operations further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. | 24. The computer storage medium of claim 16 , the operations further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. 26. The computer storage medium of claim 24 , the operations further comprising: analyzing contents of each search result resource to identify references to attributes associated with entities of the particular type in the contents of the resource. | 0.73673 |
9,165,086 | 1 | 18 | 1. A method for storing an XML document of a plurality of documents, the method comprising steps of: storing in a persistent repository a persistent representation of the XML document that includes a navigable representation and a streamable representation that is separate from said navigable representation, wherein the XML document includes a tree of nodes in a hierarchical relationship, each node of the tree of nodes having an immediate hierarchical relationship with at least one other node in the tree of nodes, wherein the streamable representation contains nodes of the tree of nodes that are in document order, wherein the navigable representation contains a subset of nodes of the tree of nodes, the subset of nodes including less than all nodes of the tree of nodes, and wherein each particular node of the subset of nodes in the navigable representation includes at least one pointer to content, of said each particular node, that is contained in the streamable representation, and at least one pointer to another node of the subset of nodes in the navigable representation, said at least one pointer to the other node in the navigable representation being one of: a pointer to a parent node of said each particular node, a pointer to a child node of said each particular node, a pointer to a sibling node of said each particular node, or a pointer to a previous sibling node of said each particular node; wherein the steps are performed by one or more computing devices. | 1. A method for storing an XML document of a plurality of documents, the method comprising steps of: storing in a persistent repository a persistent representation of the XML document that includes a navigable representation and a streamable representation that is separate from said navigable representation, wherein the XML document includes a tree of nodes in a hierarchical relationship, each node of the tree of nodes having an immediate hierarchical relationship with at least one other node in the tree of nodes, wherein the streamable representation contains nodes of the tree of nodes that are in document order, wherein the navigable representation contains a subset of nodes of the tree of nodes, the subset of nodes including less than all nodes of the tree of nodes, and wherein each particular node of the subset of nodes in the navigable representation includes at least one pointer to content, of said each particular node, that is contained in the streamable representation, and at least one pointer to another node of the subset of nodes in the navigable representation, said at least one pointer to the other node in the navigable representation being one of: a pointer to a parent node of said each particular node, a pointer to a child node of said each particular node, a pointer to a sibling node of said each particular node, or a pointer to a previous sibling node of said each particular node; wherein the steps are performed by one or more computing devices. 18. The method of claim 1 , wherein said each particular node satisfies a criterion inclusion in the navigable representation. | 0.885246 |
9,215,212 | 11 | 20 | 11. A system of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, comprising: a learning engine of an application firewall, determining a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string, each URL string comprising a path to a resource; and a visualizer executing on a device, categorizing a subset of the plurality of learned rules under a first check type of a plurality of check types, generating a first tree representation of URL strings of the subset of learned rules, each node of the first tree representation corresponding to a segment of the URL strings identified based on application of a first delimiter to the URL strings to segment the URL strings into a first plurality of segments, each of the first plurality of URL strings comprising multiple segments identified based on application of the first selected delimiter, and generating, responsive to changing the first delimiter to a second selected delimiter for the same URL strings via the visualizer responsive to a user operating the visualizer, a second tree representation of the same URL strings of the subset of learned rules change, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments. | 11. A system of generating a representation of a plurality of learned rules from a learning engine of an application firewall based on a history of uniform resource locator (URL) communications with a web server, comprising: a learning engine of an application firewall, determining a plurality of learned rules based on a history of URL communications with a web server, each of the plurality of learned rules assigned a URL string, each URL string comprising a path to a resource; and a visualizer executing on a device, categorizing a subset of the plurality of learned rules under a first check type of a plurality of check types, generating a first tree representation of URL strings of the subset of learned rules, each node of the first tree representation corresponding to a segment of the URL strings identified based on application of a first delimiter to the URL strings to segment the URL strings into a first plurality of segments, each of the first plurality of URL strings comprising multiple segments identified based on application of the first selected delimiter, and generating, responsive to changing the first delimiter to a second selected delimiter for the same URL strings via the visualizer responsive to a user operating the visualizer, a second tree representation of the same URL strings of the subset of learned rules change, each node of the second tree corresponding to a segment of the URL strings identified based on application of the second selected delimiter to the URL strings to segment the URL strings into a second plurality of segments, the change allowing a visual comparison of hierarchical distributions of the first plurality of segments and the second plurality of segments between the first tree and the second tree, and distributions of the subset of learned rules corresponding to the first plurality of segments and the second plurality of segments. 20. The system of claim 11 , wherein the visualizer generates the second tree representation of the URL strings responsive to changing the first delimiter to the second delimiter, the second delimiter selected based on one or more of: the first check type, an attribute of the first tree representation, and a characteristic of the URL strings. | 0.5 |
9,195,947 | 1 | 9 | 1. A method for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system, wherein the representative data is associated with one or more classes in the plurality of classes; further updating the RDS such that a number of classes with which the representative data is associated and the number of representative data in each class is adjusted to maintain a balanced inclusion of representative data in each class; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events. | 1. A method for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system, wherein the representative data is associated with one or more classes in the plurality of classes; further updating the RDS such that a number of classes with which the representative data is associated and the number of representative data in each class is adjusted to maintain a balanced inclusion of representative data in each class; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events. 9. The method of claim 1 , wherein the updating of the RDS is performed, in response to determining that a number of representative data in the RDS has fallen below a fourth threshold. | 0.603448 |
9,836,579 | 13 | 16 | 13. The hybrid electronic medical record system of claim 1 wherein the search engine further includes a query expander processing medical words from the text query to add additional medical words corresponding to the medical words of the query. | 13. The hybrid electronic medical record system of claim 1 wherein the search engine further includes a query expander processing medical words from the text query to add additional medical words corresponding to the medical words of the query. 16. The hybrid electronic medical record system of claim 13 wherein the additional medical words are words related as co-symptoms. | 0.503817 |
8,326,627 | 1 | 2 | 1. A method for dynamically generating a recognition grammar in an integrated voice navigation services environment, comprising: receiving a natural language utterance from an input device coupled to a navigation device, wherein the natural language utterance relates to a navigation context; identifying a current location associated with the navigation device using a location detection system coupled to the navigation device; generating, at a conversational language processor, a dynamic recognition grammar that organizes grammar information based on one or more topological domains associated with the current location associated with the navigation device; and determining one or more affinities between a user that spoke the natural language utterance and one or more peers associated with the user, wherein the dynamic recognition grammar further organizes the grammar information according to the one or more determined affinities; generating, at a speech recognition engine, one or more interpretations associated with the natural language utterance using the dynamic recognition grammar. | 1. A method for dynamically generating a recognition grammar in an integrated voice navigation services environment, comprising: receiving a natural language utterance from an input device coupled to a navigation device, wherein the natural language utterance relates to a navigation context; identifying a current location associated with the navigation device using a location detection system coupled to the navigation device; generating, at a conversational language processor, a dynamic recognition grammar that organizes grammar information based on one or more topological domains associated with the current location associated with the navigation device; and determining one or more affinities between a user that spoke the natural language utterance and one or more peers associated with the user, wherein the dynamic recognition grammar further organizes the grammar information according to the one or more determined affinities; generating, at a speech recognition engine, one or more interpretations associated with the natural language utterance using the dynamic recognition grammar. 2. The method of claim 1 , wherein generating the dynamic recognition grammar includes: recognizing, at a multi-pass speech recognition module associated with the speech recognition engine, one or more command words in the natural language utterance that define a command in the navigation context; recognizing, at the multi-pass speech recognition module, one or more location words in the natural language utterance that define a state associated with the command in the navigation context; wherein the dynamic recognition grammar further organizes the grammar information according to the state associated with the command in the navigation context; and recognizing, at the multi-pass speech recognition module, one or more additional location words in the natural language utterance that define a city within the state associated with the command in the navigation context, wherein the dynamic recognition grammar further organizes the grammar information according to multiple street addresses in the city within the state associated with the command in the navigation context. | 0.5 |
7,774,746 | 1 | 13 | 1. A method of generating code, comprising: receiving a specification of one or more translation patterns; using at least one of the one or more translation patterns to generate using a processor at least a portion of a first code associated with a first translator, wherein the first translator is configured to create a target object model, including by populating one or more elements of the target object model in a processing order at least in part associated with an order of elements in at least one of the one or more translation patterns; using at least one of the one or more translation patterns to generate at least a portion of a second code associated with a second translator; and connecting together the first translator and the second translator to form at least a portion of a converter. | 1. A method of generating code, comprising: receiving a specification of one or more translation patterns; using at least one of the one or more translation patterns to generate using a processor at least a portion of a first code associated with a first translator, wherein the first translator is configured to create a target object model, including by populating one or more elements of the target object model in a processing order at least in part associated with an order of elements in at least one of the one or more translation patterns; using at least one of the one or more translation patterns to generate at least a portion of a second code associated with a second translator; and connecting together the first translator and the second translator to form at least a portion of a converter. 13. A method as recited in claim 1 , wherein each of the one or more translation patterns is associated with a schema for the generated code. | 0.805249 |
8,131,714 | 1 | 2 | 1. A method for determining a linguistic preference between two or more phrases each of the two or more phrases including a plurality of words, comprising: submitting each of the two or more phrases simultaneously, and one or more linguistic categories, as a search string to at least one search engine, wherein a search performed by the at least one search engine is restricted to the one or more linguistic categories; receiving search results from each instance of the at least one search engine for each submitted search string; comparing total hit values of each search result with each other; and displaying, to a user, one of the phrases associated with a greatest total hit value as a preferred phrase, wherein the step of displaying comprises displaying, to the user, two or more of display phrases where a difference between the total hit values of the two or more phrases is less than a predefined percentage. | 1. A method for determining a linguistic preference between two or more phrases each of the two or more phrases including a plurality of words, comprising: submitting each of the two or more phrases simultaneously, and one or more linguistic categories, as a search string to at least one search engine, wherein a search performed by the at least one search engine is restricted to the one or more linguistic categories; receiving search results from each instance of the at least one search engine for each submitted search string; comparing total hit values of each search result with each other; and displaying, to a user, one of the phrases associated with a greatest total hit value as a preferred phrase, wherein the step of displaying comprises displaying, to the user, two or more of display phrases where a difference between the total hit values of the two or more phrases is less than a predefined percentage. 2. The method of claim 1 , the one or more linguistic categories comprising at least two distinct linguistic categories. | 0.602649 |
8,856,160 | 11 | 15 | 11. One or more non-transitory computer-readable media storing one or more sequences of instructions which, when executed, cause performance of: receiving, from a user that is customizing a custom product, a first attribute value that defines an attribute of the custom product; in response to receiving the first attribute value, generating, based at least in part on the first attribute value and one or more other attributes of the custom product, a particular key-value expression that includes a plurality of key attributes and values; matching the particular key-value expression to a set of one or more filters; determining, from the set of one or more filters, a legal set of attribute values for a second attribute of at least one of the custom product or an accessory product; wherein the legal set of attribute values identifies one or more attribute values of the second attribute of the custom product or the accessory product that are compatible with the first attribute value and the one or more other attributes of the custom product. | 11. One or more non-transitory computer-readable media storing one or more sequences of instructions which, when executed, cause performance of: receiving, from a user that is customizing a custom product, a first attribute value that defines an attribute of the custom product; in response to receiving the first attribute value, generating, based at least in part on the first attribute value and one or more other attributes of the custom product, a particular key-value expression that includes a plurality of key attributes and values; matching the particular key-value expression to a set of one or more filters; determining, from the set of one or more filters, a legal set of attribute values for a second attribute of at least one of the custom product or an accessory product; wherein the legal set of attribute values identifies one or more attribute values of the second attribute of the custom product or the accessory product that are compatible with the first attribute value and the one or more other attributes of the custom product. 15. The one or more non-transitory computer-readable media of claim 11 , further comprising identifying a particular accessory product that has an attribute value within the legal set of attribute values; identifying a third attribute value defining a third attribute of the particular accessory product; determining whether the custom product is compatible with the third attribute value; in response to determining that the custom product is not compatible with the third attribute value, preventing recommendation of the particular accessory product to the user. | 0.611951 |
9,620,104 | 11 | 12 | 11. The computer readable storage medium of claim 10 , further comprising instructions for causing the device to perform, prior to receiving the first speech input, providing the text string. | 11. The computer readable storage medium of claim 10 , further comprising instructions for causing the device to perform, prior to receiving the first speech input, providing the text string. 12. The computer readable storage medium of claim 11 , wherein the text string is a name in a contact list associated with a user. | 0.507576 |
8,423,555 | 6 | 8 | 6. The method of claim 5 , further comprising: determining a segment of the content item based on the segment boundary. | 6. The method of claim 5 , further comprising: determining a segment of the content item based on the segment boundary. 8. The method of claim 6 , further comprising: determining a topic for the segment of the content item based on at least one of the first set of nodes, the second set of nodes, or the text. | 0.5 |
7,523,318 | 5 | 8 | 5. A system for automated password generation, said system comprising: memory for storing a known valid multi-character password string for a target data processing system; means for automatically determining a character type for each character in said known valid multi-character password string; means for automatically assigning a random character of identical type to replace each character in said known valid multi-character password string to create a randomly generated password, which will comply with specified password rules, and syntax for said target data processing system; means for submitting said randomly generated password to said target data processing system; and means for generating an alert message in the event said randomly generated password is rejected by said target data proceeding system “N” times; and means for permitting a user to define “N”. | 5. A system for automated password generation, said system comprising: memory for storing a known valid multi-character password string for a target data processing system; means for automatically determining a character type for each character in said known valid multi-character password string; means for automatically assigning a random character of identical type to replace each character in said known valid multi-character password string to create a randomly generated password, which will comply with specified password rules, and syntax for said target data processing system; means for submitting said randomly generated password to said target data processing system; and means for generating an alert message in the event said randomly generated password is rejected by said target data proceeding system “N” times; and means for permitting a user to define “N”. 8. The system for automated password generation in a data processing system according to claim 5 , wherein said means for automatically determining a character type for each character in said known valid multi-character password string comprises means for automatically determining whether each character in said known valid multi-character password string is a numeric character, a punctuation character, a lower-case alphabetic character, or an upper-case alphabetic character. | 0.5 |
9,323,832 | 1 | 10 | 1. A method comprising: providing a user device with a first search result including one or more item listings in response to a first query received from the user device, each item listing including a plurality of keywords and being associated with a sale format; tracking a plurality of transactions performed on the one or more item listings via the user device; assigning, using one or more processors, for each transaction, a first numerical value to one or more keywords included in a selected item listing and a second numerical value to one or more keywords included in non-selected item listings, the first numerical value being determined based upon the sale format associated with the selected item listing, the assigning including determining the first numerical value based at least in part on whether the sale format associated with the selected item listing is a fixed price sale or a non-fixed price sale; and building a desirability index using one or more numerical values including the first and second numerical values, the desirability index including a desirability value for each keyword, the desirability value being determined based on one or more first numerical values assigned to the keyword, and the desirability value indicating an accumulative frequency of a corresponding keyword being selected throughout the plurality of transactions; wherein the desirability index is accessed to sort item listings in a second search result identified in response to a second query. | 1. A method comprising: providing a user device with a first search result including one or more item listings in response to a first query received from the user device, each item listing including a plurality of keywords and being associated with a sale format; tracking a plurality of transactions performed on the one or more item listings via the user device; assigning, using one or more processors, for each transaction, a first numerical value to one or more keywords included in a selected item listing and a second numerical value to one or more keywords included in non-selected item listings, the first numerical value being determined based upon the sale format associated with the selected item listing, the assigning including determining the first numerical value based at least in part on whether the sale format associated with the selected item listing is a fixed price sale or a non-fixed price sale; and building a desirability index using one or more numerical values including the first and second numerical values, the desirability index including a desirability value for each keyword, the desirability value being determined based on one or more first numerical values assigned to the keyword, and the desirability value indicating an accumulative frequency of a corresponding keyword being selected throughout the plurality of transactions; wherein the desirability index is accessed to sort item listings in a second search result identified in response to a second query. 10. The method of claim 1 , wherein the first numerical value is not assigned to a keyword upon determination of the keyword being included in the first query. | 0.827549 |
7,725,923 | 13 | 15 | 13. The structured document processing method according to claim 11 , further comprising the step of: selecting out of the plurality of source structured documents, as the most approximate structured document, a source structured document whose source contents are the most approximate to contents of the new structured document; wherein the step of storing stores source content and source parsed partitions concerning a plurality of source structured documents which are different from one another; and wherein the step of performing the match check turns the source structured document concerning the matching check into the most approximate structured document. | 13. The structured document processing method according to claim 11 , further comprising the step of: selecting out of the plurality of source structured documents, as the most approximate structured document, a source structured document whose source contents are the most approximate to contents of the new structured document; wherein the step of storing stores source content and source parsed partitions concerning a plurality of source structured documents which are different from one another; and wherein the step of performing the match check turns the source structured document concerning the matching check into the most approximate structured document. 15. The structured document processing method according to claim 13 , further comprising the steps of: detecting a UIRL to which a request for a Web service is going to be sent, wherein the structured document is concerned with the request for the Web service; and selecting a most approximate structured document on the basis of the URL detected. | 0.5 |
8,275,776 | 1 | 21 | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) establishing a format for an automated search request; b) accepting an automated search request in said format for additional information related to a concept represented within at least one text section of electronic text, wherein: i. said search request is initiated by execution of computer-executable code packaged with said electronic text; and ii. said computer-executable code is formatted and designed to be executed in real-time without user action when said accompanying electronic text is displayed: c) in response to said automated search request searching an index, said search of an index identifying additional material related to said concept; and d) providing an indicator of said additional material for display in the same presentation as said electronic text, wherein said indicator comprises display material not directly derived from said electronic text; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) establishing a format for an automated search request; b) accepting an automated search request in said format for additional information related to a concept represented within at least one text section of electronic text, wherein: i. said search request is initiated by execution of computer-executable code packaged with said electronic text; and ii. said computer-executable code is formatted and designed to be executed in real-time without user action when said accompanying electronic text is displayed: c) in response to said automated search request searching an index, said search of an index identifying additional material related to said concept; and d) providing an indicator of said additional material for display in the same presentation as said electronic text, wherein said indicator comprises display material not directly derived from said electronic text; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. 21. The method of claim 1 , wherein said indicator of related material comprises an advertisement. | 0.736559 |
9,881,055 | 1 | 4 | 1. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes: converting a SQL expression into an S-expression tabular structure, wherein said S-expression comprises a nested list; generating a function table based on said S-expression tabular structure, wherein said function table comprises a plurality of functions associated with said S expression tabular structure tabulated against at least one of a function name, a derived column and a derived table; generating an argument table based on said S-expression tabular structure, wherein said argument table comprises a plurality of arguments associated with said S expression tabular structure tabulated against at least one of an argument type, a function identification, a computed from function, a reference to entity or a literal value; and converting at least one function associated with said S-expression tabular structure to a pre-determined language, based on a language map of said pre-determined language and said function table and said argument table. | 1. One or more non-transitory computer readable storage mediums storing one or more sequences of instructions, which when executed by one or more processors, causes: converting a SQL expression into an S-expression tabular structure, wherein said S-expression comprises a nested list; generating a function table based on said S-expression tabular structure, wherein said function table comprises a plurality of functions associated with said S expression tabular structure tabulated against at least one of a function name, a derived column and a derived table; generating an argument table based on said S-expression tabular structure, wherein said argument table comprises a plurality of arguments associated with said S expression tabular structure tabulated against at least one of an argument type, a function identification, a computed from function, a reference to entity or a literal value; and converting at least one function associated with said S-expression tabular structure to a pre-determined language, based on a language map of said pre-determined language and said function table and said argument table. 4. The one or more non-transitory computer readable storage mediums of claim 1 , wherein said transforming comprises: changing at least one of one or more function names, one or more arguments, a syntax and one or more keywords of each list in a reconstructed S-expression string to be in compliance with said language map of said pre-determined language. | 0.873845 |
8,780,077 | 9 | 12 | 9. A mobile device configured to present a user interface for presenting recognition and prediction candidates associated with a received handwriting input, the mobile device comprising: a processor; a memory; and a display component with an associated touch interface, the display component being configured to present a user interface that includes a candidate window, the candidate window displaying a plurality of recognition candidates that are identified by a recognition engine executed by the processor and based on a handwriting input received via the touch interface, the candidate window also displaying a plurality of combination candidates that include a first recognition candidate of the plurality of recognition candidates followed by a respective prediction candidate, one or more of the respective prediction candidates being determined base at least in part on phrases previously input to the mobile device, and an edit field that displays the first recognition candidate as determined text. | 9. A mobile device configured to present a user interface for presenting recognition and prediction candidates associated with a received handwriting input, the mobile device comprising: a processor; a memory; and a display component with an associated touch interface, the display component being configured to present a user interface that includes a candidate window, the candidate window displaying a plurality of recognition candidates that are identified by a recognition engine executed by the processor and based on a handwriting input received via the touch interface, the candidate window also displaying a plurality of combination candidates that include a first recognition candidate of the plurality of recognition candidates followed by a respective prediction candidate, one or more of the respective prediction candidates being determined base at least in part on phrases previously input to the mobile device, and an edit field that displays the first recognition candidate as determined text. 12. The mobile device of claim 9 , wherein when a selection of a second recognition candidate of the plurality of recognition candidates or a selection of a first combination candidate of the plurality of combination candidates is received via the touch interface the candidate window displays one or more second prediction candidates that are determined to be associated with the second recognition candidate or the first combination candidate based at least in part on phrases previously input to the mobile device. | 0.5 |
9,754,046 | 8 | 9 | 8. A computer storage device encoding computer executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method to generate a webpage using one or more terms in a hierarchical taxonomy of a content management system, the method comprising: accessing a term set having a hierarchical structure, wherein the term set comprises a first and second term; generating a first friendly uniform resource locator for the webpage using the first term, wherein the first term and the first friendly uniform resource locator are associated such that a change to the first term is automatically applied to the first friendly uniform resource locator, and wherein the first friendly uniform resource locator is mapped to a first physical uniform resource locator; generating a second friendly uniform resource locator for the webpage using the second term, wherein the second term and the second friendly uniform resource locator are associated such that a change to the second term is automatically applied to the second friendly uniform resource locator, and wherein the second friendly uniform resource locator is mapped to the first physical uniform resource locator; using the first physical uniform resource locator to generate a second physical uniform resource locator comprising a first set of term context parameters, the first set of term context parameters comprising a first set of term identifiers associated with the first term, wherein the first set of term identifiers are appended to the second physical uniform resource locator; and using the first physical uniform resource locator to generate a third physical uniform resource locator comprising a second set of term context parameters, the second set of term context parameters comprising a second set of term identifiers associated with the second term, wherein the second set of term identifiers are appended to the third physical uniform resource locator. | 8. A computer storage device encoding computer executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method to generate a webpage using one or more terms in a hierarchical taxonomy of a content management system, the method comprising: accessing a term set having a hierarchical structure, wherein the term set comprises a first and second term; generating a first friendly uniform resource locator for the webpage using the first term, wherein the first term and the first friendly uniform resource locator are associated such that a change to the first term is automatically applied to the first friendly uniform resource locator, and wherein the first friendly uniform resource locator is mapped to a first physical uniform resource locator; generating a second friendly uniform resource locator for the webpage using the second term, wherein the second term and the second friendly uniform resource locator are associated such that a change to the second term is automatically applied to the second friendly uniform resource locator, and wherein the second friendly uniform resource locator is mapped to the first physical uniform resource locator; using the first physical uniform resource locator to generate a second physical uniform resource locator comprising a first set of term context parameters, the first set of term context parameters comprising a first set of term identifiers associated with the first term, wherein the first set of term identifiers are appended to the second physical uniform resource locator; and using the first physical uniform resource locator to generate a third physical uniform resource locator comprising a second set of term context parameters, the second set of term context parameters comprising a second set of term identifiers associated with the second term, wherein the second set of term identifiers are appended to the third physical uniform resource locator. 9. The computer storage device of claim 8 , wherein the first friendly uniform resource locator is a concise representation of the first physical uniform resource locator. | 0.611364 |
7,895,573 | 14 | 22 | 14. A method of managing a system of containers accessible to a computer system by using an inventory of a plurality of protected containers in the system of containers, the plurality of protected containers being accessible to the computer system from at least one of a locally-accessible storage device, a remotely-accessible file storage system, or a storage repository, wherein each of the protected containers is executable in at least one of a plurality of execution environments characterizing the computer system, the method comprising: providing the inventory of the plurality of protected containers, the inventory including a plurality of identifiers corresponding respectively to each of the plurality of protected containers, wherein each identifier includes information specific to accessing or locating the contents of the corresponding protected container, information uniquely representing the corresponding protected container, or a combination thereof, wherein the inventory is maintained by container management and protection software including an interception module, the inventory for use by the interception module; dynamically intercepting, by the interception module, an operation request on the computer system for a targeted container, the operation request selected from a group consisting of a user-initiated request and a software process initiated request; identifying the targeted container of the intercepted operation request; analyzing the inventory of the plurality of protected containers to determine if an identifier corresponding to one of the plurality of protected containers matches that of the targeted container; allowing the operation request if the operation request is a change request and if it is determined that none of the identifiers corresponding to the plurality of protected containers matches that of the targeted container; and evaluating, if the operation request is allowed, whether an operation resulting from the operation request creates a new container that is executable in at least one of the plurality of execution environments characterizing the computer system, wherein if the new container is created then a new identifier corresponding to the new container is added to the inventory if the operation is authorized. | 14. A method of managing a system of containers accessible to a computer system by using an inventory of a plurality of protected containers in the system of containers, the plurality of protected containers being accessible to the computer system from at least one of a locally-accessible storage device, a remotely-accessible file storage system, or a storage repository, wherein each of the protected containers is executable in at least one of a plurality of execution environments characterizing the computer system, the method comprising: providing the inventory of the plurality of protected containers, the inventory including a plurality of identifiers corresponding respectively to each of the plurality of protected containers, wherein each identifier includes information specific to accessing or locating the contents of the corresponding protected container, information uniquely representing the corresponding protected container, or a combination thereof, wherein the inventory is maintained by container management and protection software including an interception module, the inventory for use by the interception module; dynamically intercepting, by the interception module, an operation request on the computer system for a targeted container, the operation request selected from a group consisting of a user-initiated request and a software process initiated request; identifying the targeted container of the intercepted operation request; analyzing the inventory of the plurality of protected containers to determine if an identifier corresponding to one of the plurality of protected containers matches that of the targeted container; allowing the operation request if the operation request is a change request and if it is determined that none of the identifiers corresponding to the plurality of protected containers matches that of the targeted container; and evaluating, if the operation request is allowed, whether an operation resulting from the operation request creates a new container that is executable in at least one of the plurality of execution environments characterizing the computer system, wherein if the new container is created then a new identifier corresponding to the new container is added to the inventory if the operation is authorized. 22. The method of claim 14 , wherein the inventory of the plurality of protected containers is aggregated with one or more inventories corresponding to a plurality of host computers to create an aggregate inventory of a plurality of protected containers executable in at least one execution environment of the plurality of host computers, and wherein the computer system is one of the plurality of host computers. | 0.5 |
9,767,092 | 1 | 4 | 1. A method of extracting information from a text input received by a natural language understanding system, comprising: parsing the text input to extract a plurality of features from the text input; identifying a plurality of pre-existing statistical models; processing, through the plurality of statistical models, each of the plurality of features to generate at least one value; combining, via a processor, one value for each of the plurality of features to create a complex information target; and outputting the complex information target, wherein the complex information target indicates a meaning for the text input. | 1. A method of extracting information from a text input received by a natural language understanding system, comprising: parsing the text input to extract a plurality of features from the text input; identifying a plurality of pre-existing statistical models; processing, through the plurality of statistical models, each of the plurality of features to generate at least one value; combining, via a processor, one value for each of the plurality of features to create a complex information target; and outputting the complex information target, wherein the complex information target indicates a meaning for the text input. 4. The method of claim 1 , further comprising: determining a value for a first feature in the text input; and selecting one of the plurality of statistical models based upon the value determined for the first feature. | 0.729426 |
7,493,247 | 5 | 9 | 5. A system according to claim 1 wherein said model checker engine includes means for determining whether a model checker-based trace is a reproduction of said ICUT-based trace. | 5. A system according to claim 1 wherein said model checker engine includes means for determining whether a model checker-based trace is a reproduction of said ICUT-based trace. 9. A system according to claim 5 wherein said model checker engine includes means responsive to said determination, for generating a new initial state and a new assertion, and for applying said new initial state and said new assertion to said Controller, and wherein said Controller includes means responsive to said applied new initial state and said new assertion for generating a new configuration signals and for applying said new configuration signals to said DL region of said ICUT. | 0.5 |
9,324,070 | 15 | 20 | 15. A Non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for reducing a number of user corrections entered to obtain a correct account number of a financial transaction card, the operations comprising: receiving from a server multiple versions of text recognition results, each version comprising multiple character positions with one or more corresponding recognized characters; identifying a best guess from the multiple versions of text recognition results; displaying a textual representation of the best guess; receiving a correction character corresponding to a character of the textual representation, the correction character indicating a difference between the best guess and the correct account number; eliminating, based on the correction character, one or more of the multiple versions of text recognition results to create one or more remaining versions; identifying a new best guess from the remaining versions; and updating the textual representation with the new best guess showing at least: a first difference indicating the correction character; and a second difference indicating a difference between the best guess and the correct account number other than the correction character. | 15. A Non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for reducing a number of user corrections entered to obtain a correct account number of a financial transaction card, the operations comprising: receiving from a server multiple versions of text recognition results, each version comprising multiple character positions with one or more corresponding recognized characters; identifying a best guess from the multiple versions of text recognition results; displaying a textual representation of the best guess; receiving a correction character corresponding to a character of the textual representation, the correction character indicating a difference between the best guess and the correct account number; eliminating, based on the correction character, one or more of the multiple versions of text recognition results to create one or more remaining versions; identifying a new best guess from the remaining versions; and updating the textual representation with the new best guess showing at least: a first difference indicating the correction character; and a second difference indicating a difference between the best guess and the correct account number other than the correction character. 20. The computer-readable storage medium of claim 15 further comprising: verifying the new best guess as the correct account number by: sending the new best guess to a financial institution; and receiving, from the financial institution, a confirmation that the new best guess indicates valid account data. | 0.702913 |
8,005,782 | 13 | 17 | 13. A computer program product comprising a computer storage medium having computer program logic stored thereon for enabling a processor-based system to classify a domain name, the computer program product comprising: a first program logic module for enabling the processor-based system to identify a dictionary set of character-based n-grams, wherein each character-based n-gram in the dictionary set of character-based n-grams is associated with a pre-established first classification probability value and a pre-established second classification probability value, wherein the pre-established first classification probability value is indicative of whether a corresponding character-based n-gram of the dictionary set is likely to be in a first domain name category, wherein the pre-established second classification probability value is indicative of whether the corresponding character-based n-gram of the dictionary set is likely to be in a second domain name category; a second program logic module for enabling the processor-based system to identify a domain set of character-based n-grams corresponding to a domain name string, the domain name string being associated with a domain name; a third program logic module for enabling the processor-based system to classify the domain name in the first domain name category in response to at least one of the pre-established first classification probability value of a first character-based n-gram in the dictionary set corresponding to a first selected character-based n-gram in the domain set or the pre-established first classification probability value of a second character-based n-gram in the dictionary set corresponding to a second selected character-based n-gram in the domain set being higher than a first classification predetermined threshold and for enabling the processor-based system to further classify the domain name in the second domain name category in response to at least one of the pre-established second classification probability value of the first character-based n-gram in the dictionary set corresponding to the first selected character-based n-gram in the domain set or the pre-established second classification probability value of the second character-based n-gram in the dictionary set corresponding to the second selected character-based n-gram in the domain set being higher than a second classification predetermined threshold. | 13. A computer program product comprising a computer storage medium having computer program logic stored thereon for enabling a processor-based system to classify a domain name, the computer program product comprising: a first program logic module for enabling the processor-based system to identify a dictionary set of character-based n-grams, wherein each character-based n-gram in the dictionary set of character-based n-grams is associated with a pre-established first classification probability value and a pre-established second classification probability value, wherein the pre-established first classification probability value is indicative of whether a corresponding character-based n-gram of the dictionary set is likely to be in a first domain name category, wherein the pre-established second classification probability value is indicative of whether the corresponding character-based n-gram of the dictionary set is likely to be in a second domain name category; a second program logic module for enabling the processor-based system to identify a domain set of character-based n-grams corresponding to a domain name string, the domain name string being associated with a domain name; a third program logic module for enabling the processor-based system to classify the domain name in the first domain name category in response to at least one of the pre-established first classification probability value of a first character-based n-gram in the dictionary set corresponding to a first selected character-based n-gram in the domain set or the pre-established first classification probability value of a second character-based n-gram in the dictionary set corresponding to a second selected character-based n-gram in the domain set being higher than a first classification predetermined threshold and for enabling the processor-based system to further classify the domain name in the second domain name category in response to at least one of the pre-established second classification probability value of the first character-based n-gram in the dictionary set corresponding to the first selected character-based n-gram in the domain set or the pre-established second classification probability value of the second character-based n-gram in the dictionary set corresponding to the second selected character-based n-gram in the domain set being higher than a second classification predetermined threshold. 17. The computer program product of claim 13 , further comprising: a fourth program logic module for enabling the processor-based system to determine the pre-established first classification probability value with a Bayesian formula that uses a number of occurrences of a character-based n-gram and the number of domain name samples in the first domain name category. | 0.5 |
8,676,582 | 2 | 3 | 2. The speech recognition system as claimed in claim 1 , wherein the reduced user dictionary is a dictionary in which a word having a possibility of being included in the input speech is selected from the words in the user dictionary. | 2. The speech recognition system as claimed in claim 1 , wherein the reduced user dictionary is a dictionary in which a word having a possibility of being included in the input speech is selected from the words in the user dictionary. 3. The speech recognition system as claimed in claim 2 , wherein the reduced user dictionary creation unit compares a word in the user dictionary and the input speech, calculates a likelihood that the word appears in the input speech, and based on a calculation result, selects a word having a high likelihood to thereby create the reduced user dictionary. | 0.5 |
9,928,231 | 13 | 14 | 13. A message topic trend alert system of a communications network, comprising: at least one interface to the communications network configured for receiving short text messages transmitted within the communications network; at least one processor; and at least one computer readable storage device having stored thereon computer readable instructions that, when executed by the at least one processor, cause the at least a one processor to perform operations for generating an alert based on a message topic trend, comprising: obtaining distributed vector representations of words in a vocabulary identified in a corpus comprising a plurality of training short text messages, the distributed vector representations being obtained by processing windows of the corpus having a context window fixed length using a continuous bag of words model; estimating a plurality of Gaussian components of a Gaussian mixture model of the corpus using the distributed vector representations and using bottleneck features obtained using neural networks, the Gaussian components representing corpus topics; receiving a plurality of sample short text messages comprising a subset of the words in the vocabulary; determining topics of the sample short text messages based on a posterior distribution over the corpus topics for the sample short text messages, the posterior distribution obtained using the Gaussian mixture model; identifying a trend in topics of the short text messages; and generating an alert based on the trend. | 13. A message topic trend alert system of a communications network, comprising: at least one interface to the communications network configured for receiving short text messages transmitted within the communications network; at least one processor; and at least one computer readable storage device having stored thereon computer readable instructions that, when executed by the at least one processor, cause the at least a one processor to perform operations for generating an alert based on a message topic trend, comprising: obtaining distributed vector representations of words in a vocabulary identified in a corpus comprising a plurality of training short text messages, the distributed vector representations being obtained by processing windows of the corpus having a context window fixed length using a continuous bag of words model; estimating a plurality of Gaussian components of a Gaussian mixture model of the corpus using the distributed vector representations and using bottleneck features obtained using neural networks, the Gaussian components representing corpus topics; receiving a plurality of sample short text messages comprising a subset of the words in the vocabulary; determining topics of the sample short text messages based on a posterior distribution over the corpus topics for the sample short text messages, the posterior distribution obtained using the Gaussian mixture model; identifying a trend in topics of the short text messages; and generating an alert based on the trend. 14. The system of claim 13 , wherein the short text messages have a maximum message length, and the context window fixed length is greater than or equal to the maximum message length. | 0.589686 |
8,090,157 | 1 | 7 | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. 7. The system of claim 1 , wherein an adaptive threshold is computed adaptively based upon a pupil size and a contrast distribution of an image region having a pupil and its surrounding area. | 0.8472 |
9,953,013 | 15 | 18 | 15. A method comprising: locating, via a processor, a first alphanumeric string in a figure; locating, via the processor, a second alphanumeric string in a text; associating, via the processor, the first alphanumeric string with the second alphanumeric string based at least in part on the first alphanumeric string corresponding to the second alphanumeric string; identifying, via the processor, a characteristic associated with the processor; and taking, via the processor, an action based at least in part on the associating and the characteristic with respect to at least one of the text or the figure. | 15. A method comprising: locating, via a processor, a first alphanumeric string in a figure; locating, via the processor, a second alphanumeric string in a text; associating, via the processor, the first alphanumeric string with the second alphanumeric string based at least in part on the first alphanumeric string corresponding to the second alphanumeric string; identifying, via the processor, a characteristic associated with the processor; and taking, via the processor, an action based at least in part on the associating and the characteristic with respect to at least one of the text or the figure. 18. The method of claim 15 , wherein the action includes at least one of: copying, via the processor, an alphabetic string positioned adjacent to the first alphanumeric string, performing, via the processor, a mode analysis for an alphabetic string positioned adjacent to the first alphanumeric string, performing, via the processor, a frequency analysis for an alphabetic string positioned adjacent to the first alphanumeric string, hyperlinking, via the processor, an alphabetic string positioned adjacent to the first alphanumeric string, making, via the processor, an alphabetic string positioned adjacent to the first alphanumeric string visually distinct, highlighting, via the processor, an alphabetic string positioned adjacent to the first alphanumeric string, determining, via the processor, how to edit the figure, or translating, via the processor, an alphabetic string positioned adjacent to the first alphanumeric string. | 0.5 |
8,909,642 | 3 | 21 | 3. A processor readable non-transitive storage media that includes instructions for generating extraction rules over a network, wherein execution of the instructions by a processor device enables actions, comprising: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data from machine data; transmitting for display a user interface including a first event and a plurality of second events of the set of events; receiving data indicating a selection of a portion of text within the first event; automatically determining a field extraction rule that extracts as a value of a field the selection of the portion of text within the first event when the field extraction rule is applied to the first event; and transmitting for display an updated user interface that includes the second events and that indicates, for each of the second events, a value of the field for each second event that would be extracted by applying the extraction rule to the second event. | 3. A processor readable non-transitive storage media that includes instructions for generating extraction rules over a network, wherein execution of the instructions by a processor device enables actions, comprising: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data from machine data; transmitting for display a user interface including a first event and a plurality of second events of the set of events; receiving data indicating a selection of a portion of text within the first event; automatically determining a field extraction rule that extracts as a value of a field the selection of the portion of text within the first event when the field extraction rule is applied to the first event; and transmitting for display an updated user interface that includes the second events and that indicates, for each of the second events, a value of the field for each second event that would be extracted by applying the extraction rule to the second event. 21. The media of claim 3 , wherein the first event includes machine data. | 0.941786 |
8,600,995 | 1 | 9 | 1. A computer implemented method for automatically determining a role of a user within an organization based on classification of applications and content, the method comprising the steps, executed by at least one processor, of: identifying applications and files installed on a user's computer; filtering out identified applications and identified files that are not indicative of the role of the user within the organization; functionally classifying non-filtered out identified applications and files according to associated roles within the organization, based on predetermined functional classification information; functionally classifying at least one specific identified type of file installed on the user's computer as being indicative of a specific role of the user within the organization; determining the role of the user within the organization based on at least the functional classification of the non-filtered out identified applications and files; and utilizing the functional classification of the at least one file based on the specific identified file type in the determining of the role of the user within the organization. | 1. A computer implemented method for automatically determining a role of a user within an organization based on classification of applications and content, the method comprising the steps, executed by at least one processor, of: identifying applications and files installed on a user's computer; filtering out identified applications and identified files that are not indicative of the role of the user within the organization; functionally classifying non-filtered out identified applications and files according to associated roles within the organization, based on predetermined functional classification information; functionally classifying at least one specific identified type of file installed on the user's computer as being indicative of a specific role of the user within the organization; determining the role of the user within the organization based on at least the functional classification of the non-filtered out identified applications and files; and utilizing the functional classification of the at least one file based on the specific identified file type in the determining of the role of the user within the organization. 9. The method of claim 1 further comprising: monitoring access of external sites by the user of the computer in real time; filtering out monitored accessed external sites that are not indicative of the role of the user within the organization; functionally classifying the non-filtered out monitored accessed external sites as being indicative of a specific role of the user within the organization; and updating the determination of the role of the user within the organization, based on the functional classification of the non-filtered out monitored accessed external sites. | 0.610135 |
7,840,934 | 1 | 2 | 1. A method for supporting workflow design comprising the steps of: a) receiving a description of a business-to-business interaction standard; b) converting the description of business-to-business interaction standard to a structured representation of the business-to-business interaction standard; c) automatically generating at least one process template based on the structured representation of the business-to-business interaction standard; and d) using the process template to design a workflow. | 1. A method for supporting workflow design comprising the steps of: a) receiving a description of a business-to-business interaction standard; b) converting the description of business-to-business interaction standard to a structured representation of the business-to-business interaction standard; c) automatically generating at least one process template based on the structured representation of the business-to-business interaction standard; and d) using the process template to design a workflow. 2. The method of claim 1 wherein the description of an electronic business-to-business interaction standard includes a description of one of RosettaNet, CBL, EDI, OSI, and cXML. | 0.750704 |
9,552,341 | 1 | 3 | 1. A system comprising: one or more processors communicatively coupled to one or more memories and configured to provide: a web-based application constructor to: create a specification for constructing a web display to contain page components that display data from heterogeneous data sources, the specification associating the page components with uniform resource locators assigned to the page components; store the specification in at least one memory of the one or more memories; retrieve the data from heterogeneous data sources to produce the web display; control display and/or update of the page components using the uniform resource locators, the web display to display at least some of the data from the heterogeneous data sources; facilitate an edit state for a page that provides one or more user-selectable options to change a page layout of the page components for the page and to associate a particular uniform resource locator for at least one of the page components with an insert target arranged according to the page layout; and associate one or more user-specific changes to the page components made via the one or more user-selectable options, the user-specific changes comprising a layout change to the page layout; a versioning system that keeps track of the one or more user-specific changes to the page components; and a change control system to allow users to dynamically undo at least some of the one or more user-specific changes to the page components while using the web-based application constructor. | 1. A system comprising: one or more processors communicatively coupled to one or more memories and configured to provide: a web-based application constructor to: create a specification for constructing a web display to contain page components that display data from heterogeneous data sources, the specification associating the page components with uniform resource locators assigned to the page components; store the specification in at least one memory of the one or more memories; retrieve the data from heterogeneous data sources to produce the web display; control display and/or update of the page components using the uniform resource locators, the web display to display at least some of the data from the heterogeneous data sources; facilitate an edit state for a page that provides one or more user-selectable options to change a page layout of the page components for the page and to associate a particular uniform resource locator for at least one of the page components with an insert target arranged according to the page layout; and associate one or more user-specific changes to the page components made via the one or more user-selectable options, the user-specific changes comprising a layout change to the page layout; a versioning system that keeps track of the one or more user-specific changes to the page components; and a change control system to allow users to dynamically undo at least some of the one or more user-specific changes to the page components while using the web-based application constructor. 3. The system of claim 1 , wherein page editing and/or the page layout is versioned. | 0.805556 |
9,477,767 | 3 | 4 | 3. The method of claim 2 , wherein: the first list of query completions are provided for display within a menu beneath the search field; and the demotion score for the particular identified query completion is based on whether the particular identified query completion was provided for display at or above a threshold position within the menu. | 3. The method of claim 2 , wherein: the first list of query completions are provided for display within a menu beneath the search field; and the demotion score for the particular identified query completion is based on whether the particular identified query completion was provided for display at or above a threshold position within the menu. 4. The method of claim 3 , wherein the threshold position is a second position beneath the search field. | 0.5 |
6,076,091 | 12 | 13 | 12. The computer system of claim 1 further comprising at least one system component for creating and editing semantic information about said product information. | 12. The computer system of claim 1 further comprising at least one system component for creating and editing semantic information about said product information. 13. The system of claim 12 wherein said system further comprises protocol means for gathering user-specific information from said user. | 0.618644 |
9,799,051 | 1 | 3 | 1. A method for uploading media onto a media sharing platform, the method comprising: generating a marketer channel on the media sharing platform; a marketer receiving media from a client, wherein the marketer is a third party to the client, and wherein the client is the source of the media either directly or via an advertisement agency; the marketer authoring a unique keyword, wherein the unique keyword is not associated with any media on the media sharing platform, and wherein the marketer performs an iterative search on a plurality of media sharing platforms with various potential keywords until a unique keyword is identified across all the plurality of media sharing platforms; uploading, using a processor, the media to the media sharing platform; including the unique keyword into at least one of a title and description fields for the uploaded media; the marketer ensuring that the tag field is empty; and incorporating the unique keyword into at least one marketing campaign discrete from the media sharing platform. | 1. A method for uploading media onto a media sharing platform, the method comprising: generating a marketer channel on the media sharing platform; a marketer receiving media from a client, wherein the marketer is a third party to the client, and wherein the client is the source of the media either directly or via an advertisement agency; the marketer authoring a unique keyword, wherein the unique keyword is not associated with any media on the media sharing platform, and wherein the marketer performs an iterative search on a plurality of media sharing platforms with various potential keywords until a unique keyword is identified across all the plurality of media sharing platforms; uploading, using a processor, the media to the media sharing platform; including the unique keyword into at least one of a title and description fields for the uploaded media; the marketer ensuring that the tag field is empty; and incorporating the unique keyword into at least one marketing campaign discrete from the media sharing platform. 3. The method of claim 1 , wherein the media is at least one of video content, image, audio, executable file, and text. | 0.809904 |
8,656,288 | 11 | 12 | 11. The computer-readable storage medium of claim 10 further comprising notifying a person associated with the word or phrase that the collaboration page contains the word or phrase. | 11. The computer-readable storage medium of claim 10 further comprising notifying a person associated with the word or phrase that the collaboration page contains the word or phrase. 12. The computer-readable storage medium of claim 11 further comprising sending an e-mail message to a person who added the word or phrase to the collaboration page to notify the person that the collaboration page contains a sensitive word or phrase. | 0.5 |
6,122,628 | 33 | 35 | 33. The program storage device of claim 32, for searching for k most similar records to specified data using the reduced dimensionality index, comprising the steps of: associating specified data to said one or more clusters, based on stored clustering information; projecting the specified data onto a subspace for an associated cluster based on stored dimensionality reduction information for the associated cluster; generating dimensionality reduction information including an orthogonal complement for projected specified data, in response to said projecting; searching, via the index, for the associated cluster having k most similar records to the projected specified data; determining if any other associated cluster can include any of k most similar records to the projected specified data; and repeating said searching on said any cluster that can include any of the k most similar records to the specified data. | 33. The program storage device of claim 32, for searching for k most similar records to specified data using the reduced dimensionality index, comprising the steps of: associating specified data to said one or more clusters, based on stored clustering information; projecting the specified data onto a subspace for an associated cluster based on stored dimensionality reduction information for the associated cluster; generating dimensionality reduction information including an orthogonal complement for projected specified data, in response to said projecting; searching, via the index, for the associated cluster having k most similar records to the projected specified data; determining if any other associated cluster can include any of k most similar records to the projected specified data; and repeating said searching on said any cluster that can include any of the k most similar records to the specified data. 35. The program storage device of claim 33, wherein the specified data includes a search template, further comprising the steps of: said projecting step further comprising the step of projecting the template, using the dimensionality reduction information, onto a subspace associated with the cluster to which it belongs; generating template dimensionality reduction information for a projected template; wherein said searching, via the index is based on the projected template and the template dimensionality reduction information; and updating a set of the k most similar records to the search template. | 0.5 |
8,073,835 | 9 | 10 | 9. The method of claim 1 , further comprising the steps of: categorizing the identified words into categories; and storing an indicator of the category of each identified word with the word and its corresponding weighting. | 9. The method of claim 1 , further comprising the steps of: categorizing the identified words into categories; and storing an indicator of the category of each identified word with the word and its corresponding weighting. 10. The method of claim 9 , wherein the categories are selected from the group consisting of: address, name, hyperlink, recurring word grouping, different language categories, and user added words. | 0.5 |
9,031,830 | 1 | 4 | 1. A computer-implemented input-method editor process comprising: receiving a request from a user of an electronic device for an application-independent input method editor having written and spoken input capabilities, wherein the application-independent input method editor is configured to receive input for a plurality of applications executable by the electronic device; identifying that the user is about to provide spoken input to the application-independent input method editor; receiving a spoken input from the user, wherein the spoken input corresponds to an input to an application from the plurality of applications; identifying, with the electronic device, an application from the plurality of applications to which the spoken input was addressed by (i) identifying an application type for the application that identifies an application category for the application, wherein each application category is capable of including a plurality of applications, and (ii) matching one or more utterances in the spoken input to one or more stored terms that are associated with the application type; providing the spoken input and information indicating the application type to a server, that is remote form the electronic device and includes a speech recognition system configured to access one or more language models for recognizing text based on the spoken input and the information indicating the application type; receiving text from the remote server, wherein the text represents a translation of the spoken input; selecting an application from the plurality of applications to receive the text, based on the identifying of the application; and providing the text as the input to the application. | 1. A computer-implemented input-method editor process comprising: receiving a request from a user of an electronic device for an application-independent input method editor having written and spoken input capabilities, wherein the application-independent input method editor is configured to receive input for a plurality of applications executable by the electronic device; identifying that the user is about to provide spoken input to the application-independent input method editor; receiving a spoken input from the user, wherein the spoken input corresponds to an input to an application from the plurality of applications; identifying, with the electronic device, an application from the plurality of applications to which the spoken input was addressed by (i) identifying an application type for the application that identifies an application category for the application, wherein each application category is capable of including a plurality of applications, and (ii) matching one or more utterances in the spoken input to one or more stored terms that are associated with the application type; providing the spoken input and information indicating the application type to a server, that is remote form the electronic device and includes a speech recognition system configured to access one or more language models for recognizing text based on the spoken input and the information indicating the application type; receiving text from the remote server, wherein the text represents a translation of the spoken input; selecting an application from the plurality of applications to receive the text, based on the identifying of the application; and providing the text as the input to the application. 4. The process of claim 1 , further comprising: providing a context indicator to the remote server such that the speech recognition system can select a language model from a plurality of language models based on the context indicator, where the context indicator specifies the context in which the user input is received. | 0.534783 |
8,117,540 | 9 | 10 | 9. Method according to claim 1 , wherein the candidate words are words and a group designator is a letter that the words in the group have in common, in particular initial word letters. | 9. Method according to claim 1 , wherein the candidate words are words and a group designator is a letter that the words in the group have in common, in particular initial word letters. 10. Method according to claim 9 , wherein the common letter is at a particular position in the words of the group. | 0.5 |
9,038,907 | 3 | 4 | 3. The scanning method of claim 1 , wherein said measurement of bleed-through comprises of calculating amount of illumination that passes through said one surface of said document. | 3. The scanning method of claim 1 , wherein said measurement of bleed-through comprises of calculating amount of illumination that passes through said one surface of said document. 4. The scanning method of claim 3 , wherein said amount of illumination depends upon the security features imprinted on said one surface of said document. | 0.5 |
6,031,174 | 1 | 15 | 1. A method of generating a musical tone signal, comprising the steps of: (a) selecting one of a plurality of phrases in response to a combination of simultaneous manipulations of phrase select operators by a user; and (b) reading performance data of the selected phrase from performance data pre-stored by phrase and generating musical tone signals of the read performance data in response to said manipulations. | 1. A method of generating a musical tone signal, comprising the steps of: (a) selecting one of a plurality of phrases in response to a combination of simultaneous manipulations of phrase select operators by a user; and (b) reading performance data of the selected phrase from performance data pre-stored by phrase and generating musical tone signals of the read performance data in response to said manipulations. 15. A method according to claim 1, further comprising the step of: (c) selecting a performance character before said step (b), in response to manipulation of a character select operator, wherein said step (b) reads performance data different for each selected character and generates the musical tone signal. | 0.52322 |
8,655,901 | 8 | 13 | 8. A system comprising: one or more processors configured to interact with a computer-readable medium in order to perform operations comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. | 8. A system comprising: one or more processors configured to interact with a computer-readable medium in order to perform operations comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. 13. The system of claim 8 , where annotating each query includes labeling portions of the query according to the first query pattern. | 0.70045 |
8,856,180 | 1 | 2 | 1. An electronic publication stored on a non-transitory tangible computer medium, the electronic publication comprising: at least one root level folder, wherein the root level folder is an Open eBook Publication Structure, OEBPS, folder; an image subfolder contained in the at least one root level folder, the image subfolder containing image files used in the electronic publication; an audio subfolder contained in the at least one root level folder, the audio subfolder containing audio files used in the electronic publication; a book subfolder contained in the at least one root level folder, the book subfolder containing a data file, the data file containing JavaScript Object Notation, JSON, data; a JavaScript subfolder contained in the at least one root level folder, the JavaScript subfolder containing JavaScript files, the JavaScript files providing interactivity functionality to the electronic publication; a Cascading Style Sheet subfolder contained in the at least one root level folder, the Cascading Style Sheet subfolder containing Cascading Style Sheet files; and a primary file contained in the at least one root level folder, the primary file containing instructions and, using data from the data file, JavaScript files from the JavaScript subfolder and Cascading Style Sheet files from the Cascading Style Sheet subfolder, is capable of operation on a device for rendering the electronic publication, the primary file linking to the audio files in the audio subfolder and linking to the image files in the image subfolder. | 1. An electronic publication stored on a non-transitory tangible computer medium, the electronic publication comprising: at least one root level folder, wherein the root level folder is an Open eBook Publication Structure, OEBPS, folder; an image subfolder contained in the at least one root level folder, the image subfolder containing image files used in the electronic publication; an audio subfolder contained in the at least one root level folder, the audio subfolder containing audio files used in the electronic publication; a book subfolder contained in the at least one root level folder, the book subfolder containing a data file, the data file containing JavaScript Object Notation, JSON, data; a JavaScript subfolder contained in the at least one root level folder, the JavaScript subfolder containing JavaScript files, the JavaScript files providing interactivity functionality to the electronic publication; a Cascading Style Sheet subfolder contained in the at least one root level folder, the Cascading Style Sheet subfolder containing Cascading Style Sheet files; and a primary file contained in the at least one root level folder, the primary file containing instructions and, using data from the data file, JavaScript files from the JavaScript subfolder and Cascading Style Sheet files from the Cascading Style Sheet subfolder, is capable of operation on a device for rendering the electronic publication, the primary file linking to the audio files in the audio subfolder and linking to the image files in the image subfolder. 2. The electronic publication according to claim 1 , wherein the data in the data file specifies at least one page layout for the electronic publication and containing links to the image files and the audio files. | 0.733083 |
9,064,244 | 1 | 13 | 1. A computer system having a graphical user interface including a display and a user interface selection device, the computer system performing a method of configuring an out of office message for a user's email account, the user being a member of a domain, the method comprising: receiving an indication to activate an out of office messaging function; receiving an indication of an out of office message in a setup window; receiving a first selection to send the out of office message only to a first group of recipients, wherein the first group of recipients are contacts of the user; upon exiting the setup window, displaying an indication that the out of office function is active; receiving an email from a first recipient who is not a member of the first group of recipients; and not sending the out of office message to the first recipient. | 1. A computer system having a graphical user interface including a display and a user interface selection device, the computer system performing a method of configuring an out of office message for a user's email account, the user being a member of a domain, the method comprising: receiving an indication to activate an out of office messaging function; receiving an indication of an out of office message in a setup window; receiving a first selection to send the out of office message only to a first group of recipients, wherein the first group of recipients are contacts of the user; upon exiting the setup window, displaying an indication that the out of office function is active; receiving an email from a first recipient who is not a member of the first group of recipients; and not sending the out of office message to the first recipient. 13. The computer system of claim 1 , further comprising: receiving at least one of a start time and an end time for sending the out of office message. | 0.715909 |
10,140,980 | 1 | 2 | 1. A computer-implemented method comprising: receiving, by one or more computers, audio data corresponding to an utterance; generating, by the one or more computers, frequency domain data using the audio data; processing, by the one or more computers, the frequency domain data using complex linear projection; providing, by the one or more computers, the processed frequency domain data to a neural network trained as an acoustic model; and generating, by the one or more computers, a transcription for the utterance that is determined based at least on output that the neural network provides in response to receiving the processed frequency domain data. | 1. A computer-implemented method comprising: receiving, by one or more computers, audio data corresponding to an utterance; generating, by the one or more computers, frequency domain data using the audio data; processing, by the one or more computers, the frequency domain data using complex linear projection; providing, by the one or more computers, the processed frequency domain data to a neural network trained as an acoustic model; and generating, by the one or more computers, a transcription for the utterance that is determined based at least on output that the neural network provides in response to receiving the processed frequency domain data. 2. The method of claim 1 , wherein processing the frequency domain data using complex linear projection comprises processing the frequency domain data for each input frame of audio data. | 0.747967 |
7,792,838 | 12 | 13 | 12. The method of claim 11 , wherein the virtual class is associated with a taxonomy defined based on a range of the at least one given ontology property. | 12. The method of claim 11 , wherein the virtual class is associated with a taxonomy defined based on a range of the at least one given ontology property. 13. The method of claim 12 , wherein information content of the description of the instance is a probability that a random individual belongs to the virtual class. | 0.5 |
10,157,055 | 16 | 17 | 16. The computing device of claim 15 , wherein the code-to-syntax tree converter includes: an await relaxer configured transform the asynchronous program code into await-relaxed program code; and the code-to-syntax tree converter is configured to convert the await-relaxed program code into the first syntax tree. | 16. The computing device of claim 15 , wherein the code-to-syntax tree converter includes: an await relaxer configured transform the asynchronous program code into await-relaxed program code; and the code-to-syntax tree converter is configured to convert the await-relaxed program code into the first syntax tree. 17. The computing device of claim 16 , wherein the await-relaxer is configured to convert any awaits on asynchronous method calls in the asynchronous program code to awaits on task variables. | 0.5 |
9,336,194 | 9 | 14 | 9. A system comprising: a hardware processor; and a memory storing machine readable instructions executable on the hardware processor to: receive an input string; receive a regular expression; convert the regular expression into a plurality of automata to extract submatches of substrings in the input string, wherein the extracting comprises: using a first automaton of the plurality of automata to determine whether the input string is in a language described by the regular expression, and to process the input string; and using states of the first automaton in a second automaton of the plurality of automata to extract the submatches; and identify a source of an issue in a network in response to the submatches. | 9. A system comprising: a hardware processor; and a memory storing machine readable instructions executable on the hardware processor to: receive an input string; receive a regular expression; convert the regular expression into a plurality of automata to extract submatches of substrings in the input string, wherein the extracting comprises: using a first automaton of the plurality of automata to determine whether the input string is in a language described by the regular expression, and to process the input string; and using states of the first automaton in a second automaton of the plurality of automata to extract the submatches; and identify a source of an issue in a network in response to the submatches. 14. The system of claim 9 , wherein each automaton of the plurality of automata includes a plurality of states and rules for traversing the plurality of states. | 0.659574 |
9,558,675 | 11 | 19 | 11. A method for analyzing student performance and learning activity in a learning environment, the method comprising: receiving, with a learning analysis system including at least one electronic computer processor, input data based on interaction, by students, with the learning analysis system, wherein the input data comprises clickstream data; calculating the following: (a) student-learning data based on the clickstream data, wherein the student learning data is associated with the students performing at least one activity in the learning environment, (b) knowledge component model data based on the clickstream data, wherein the knowledge component model data comprises a mapping of at least one knowledge component to at least one activity to be performed by the student in the learning environment; generating, with an inference engine of the learning analysis system, in association with the student-learning data and the knowledge component model data, a statistical probability distribution or a point estimate for at least the following components of a statistical model: (a) a learning state parameter representing a level of learning the student has attained for at least one knowledge component, wherein the at least one knowledge component comprises a predetermined number of skills, facts, concepts, strategies, or relationships regarding subject matter within a learning domain and is specific to an individual student, (b) a skill dynamics parameter representing a relationship between practice and the learning state parameter for the at least one knowledge component, wherein the skill dynamics parameter is specific to an individual knowledge component, and (c) a variability parameter representing variability in the learning state parameter and the skill dynamics parameter across the students; and providing, via a monitor, a screen display that displays a plurality of learning objectives, wherein at least one of the plurality of learning objectives provides an interactive link in the screen display that, when activated by a user, causes the monitor to display a graphical representation of a student learning and performance based on the statistical model; wherein the graphical representation of the at least one student learning and performance comprises information illustrating at least one of the following: which knowledge component of a plurality of knowledge components were not well learned across the students; which students achieved comparatively lower levels of learning for a given learning objective; and which learning objective had not been practiced sufficiently. | 11. A method for analyzing student performance and learning activity in a learning environment, the method comprising: receiving, with a learning analysis system including at least one electronic computer processor, input data based on interaction, by students, with the learning analysis system, wherein the input data comprises clickstream data; calculating the following: (a) student-learning data based on the clickstream data, wherein the student learning data is associated with the students performing at least one activity in the learning environment, (b) knowledge component model data based on the clickstream data, wherein the knowledge component model data comprises a mapping of at least one knowledge component to at least one activity to be performed by the student in the learning environment; generating, with an inference engine of the learning analysis system, in association with the student-learning data and the knowledge component model data, a statistical probability distribution or a point estimate for at least the following components of a statistical model: (a) a learning state parameter representing a level of learning the student has attained for at least one knowledge component, wherein the at least one knowledge component comprises a predetermined number of skills, facts, concepts, strategies, or relationships regarding subject matter within a learning domain and is specific to an individual student, (b) a skill dynamics parameter representing a relationship between practice and the learning state parameter for the at least one knowledge component, wherein the skill dynamics parameter is specific to an individual knowledge component, and (c) a variability parameter representing variability in the learning state parameter and the skill dynamics parameter across the students; and providing, via a monitor, a screen display that displays a plurality of learning objectives, wherein at least one of the plurality of learning objectives provides an interactive link in the screen display that, when activated by a user, causes the monitor to display a graphical representation of a student learning and performance based on the statistical model; wherein the graphical representation of the at least one student learning and performance comprises information illustrating at least one of the following: which knowledge component of a plurality of knowledge components were not well learned across the students; which students achieved comparatively lower levels of learning for a given learning objective; and which learning objective had not been practiced sufficiently. 19. The method of claim 11 , further comprising receiving student learning data include data indicative of an activity accessed by the students in a computer based learning environment. | 0.78833 |
9,922,098 | 2 | 11 | 2. The computing system of claim 1 wherein the context identification system is configured to detect whether a user is using the computing system in a work context or a non-work context, and the relevancy generator is configured to generate the relevancy metric for the documents based on the detected work context or non-work context. | 2. The computing system of claim 1 wherein the context identification system is configured to detect whether a user is using the computing system in a work context or a non-work context, and the relevancy generator is configured to generate the relevancy metric for the documents based on the detected work context or non-work context. 11. The computing system of claim 2 wherein the context identification system comprises: a document personnel detector configured to detect other personnel that are related to the documents, other than the user, wherein the relevancy generator is configured to generate the relevancy metric for the documents based on the detected other personnel. | 0.666987 |
9,436,764 | 9 | 14 | 9. A system for performing a method for enhancing search results, comprising: a data storage that stores search query log data; a data storage that stores a web page icon database; one or more processors configured to: A) receive a search query from a user; B) identify web pages relevant to the search query; C) access the search query log data; D) for each of the relevant web pages, determine that the web page is a popular web page when the search query log data indicates that the web page has been accessed a number of times greater than a popularity threshold, wherein a plurality of popular web pages are determined; E) access the web page icon database storing one or more icons that identify a provider of each web page or group of related web pages in the database and retrieve an icon that identifies the provider of each web page relevant to the search query that is determined to be popular; F) in response to the search query from the user, generate a first search result page that simultaneously displays a search result listing and a subset of the search result listing, wherein i) the search result listing includes popular web pages for which icons were retrieved, and ii) a search result page header includes the subset of the search result listing that includes a plurality of retrieved icons that identify the providers of respective ones of the popular web pages, each icon linking to a respective popular web page, iii) wherein the number and arrangement of icons and other content items included in the search result page header are selected through ranking; and G) upon receiving a request from the user to select a first icon from the subset of the search result listing in the search result page header and navigate to a first respective popular web page, generate a second search result page having both content of the first respective popular web page and the search result page header of the first search result page, wherein the search result page header continues to display the subset of the search result listing from the original search query received from the user, including the first icon linking to the first respective popular web page and one or more other icons linking to one or more other popular web pages that were displayed on the search result page header on the first search result page. | 9. A system for performing a method for enhancing search results, comprising: a data storage that stores search query log data; a data storage that stores a web page icon database; one or more processors configured to: A) receive a search query from a user; B) identify web pages relevant to the search query; C) access the search query log data; D) for each of the relevant web pages, determine that the web page is a popular web page when the search query log data indicates that the web page has been accessed a number of times greater than a popularity threshold, wherein a plurality of popular web pages are determined; E) access the web page icon database storing one or more icons that identify a provider of each web page or group of related web pages in the database and retrieve an icon that identifies the provider of each web page relevant to the search query that is determined to be popular; F) in response to the search query from the user, generate a first search result page that simultaneously displays a search result listing and a subset of the search result listing, wherein i) the search result listing includes popular web pages for which icons were retrieved, and ii) a search result page header includes the subset of the search result listing that includes a plurality of retrieved icons that identify the providers of respective ones of the popular web pages, each icon linking to a respective popular web page, iii) wherein the number and arrangement of icons and other content items included in the search result page header are selected through ranking; and G) upon receiving a request from the user to select a first icon from the subset of the search result listing in the search result page header and navigate to a first respective popular web page, generate a second search result page having both content of the first respective popular web page and the search result page header of the first search result page, wherein the search result page header continues to display the subset of the search result listing from the original search query received from the user, including the first icon linking to the first respective popular web page and one or more other icons linking to one or more other popular web pages that were displayed on the search result page header on the first search result page. 14. The system of claim 9 , wherein at least four popular web sites are identified, and wherein the search result page header of the first search result page includes an icon for at least four of the popular web pages, each icon linking to the at least one web page. | 0.648148 |
8,548,980 | 1 | 4 | 1. A method in a database system, comprising: identifying a set of rows that satisfy local conditions to a table prior to an execution of a query; generating a data structure based on an actual effect of the local conditions on the table comprising one or more bits, each bit representing a row in the set of identified rows, a value of each bit indicating whether its respective row satisfies the local conditions to the table; modifying the query based on the generated data structure, wherein the modifying comprises identifying a quantity of rows that satisfy the local conditions by: identifying whether there are no rows that satisfy the local conditions in the data structure; identifying whether there is exactly one row that satisfies the local conditions for contents of cell values in the exactly one row in the data structure; and identifying whether there are a moderate number of rows that satisfy the local conditions for contents of cell values in the moderate number of rows in the data structure, and wherein the modifying further comprises modifying the query based on the identifying the quantity of rows; and processing the modified query to generate an execution plan for the query. | 1. A method in a database system, comprising: identifying a set of rows that satisfy local conditions to a table prior to an execution of a query; generating a data structure based on an actual effect of the local conditions on the table comprising one or more bits, each bit representing a row in the set of identified rows, a value of each bit indicating whether its respective row satisfies the local conditions to the table; modifying the query based on the generated data structure, wherein the modifying comprises identifying a quantity of rows that satisfy the local conditions by: identifying whether there are no rows that satisfy the local conditions in the data structure; identifying whether there is exactly one row that satisfies the local conditions for contents of cell values in the exactly one row in the data structure; and identifying whether there are a moderate number of rows that satisfy the local conditions for contents of cell values in the moderate number of rows in the data structure, and wherein the modifying further comprises modifying the query based on the identifying the quantity of rows; and processing the modified query to generate an execution plan for the query. 4. The method of claim 1 , wherein the identifying no rows comprises inferring a false prefilter condition, which is migrated to a highest level of a query operator tree of the query. | 0.733236 |
9,622,053 | 5 | 6 | 5. The method according to claim 1 , further including receiving a message from a device that received the transmitted text and analyzing the message to confirm receipt of the text. | 5. The method according to claim 1 , further including receiving a message from a device that received the transmitted text and analyzing the message to confirm receipt of the text. 6. The method according to claim 5 , wherein the message includes a checksum corresponding to the text. | 0.654362 |
7,901,211 | 16 | 17 | 16. The method of claim 1 , wherein the user is required to perform a set number of eye movement activities before proceeding to other activities. | 16. The method of claim 1 , wherein the user is required to perform a set number of eye movement activities before proceeding to other activities. 17. The method of claim 16 , wherein the set number of eye movement activities is three. | 0.5 |
8,650,038 | 18 | 20 | 18. A system for managing real estate transaction documents, the system comprising: a memory storing real estate transaction documents; and a document manager adapted to: receive a request for access to real estate transaction documents; presenting a first portion of the real estate documents including a first signature block and a second signature block; block presentation of a second portion of the real estate transaction documents based on an identity of a user currently logged into a system for managing real estate transaction documents; identify the first signature block and the second signature block by presenting one or more signature indicators in the real estate transaction documents, wherein a signature indicator is associated with a signature block; request signature of the first signature block of the first portion of the real estate transaction documents; prior to receiving the requested signature, receive a request to enter a signature of the second signature block of the first portion of the real estate transaction documents; determine that the request to enter the signature of the second signature block prior to receiving the requested signature violates at least one rule prohibiting signature of the second signature block; inhibit signature of the second signature block while the first signature block is unsigned; present a notification indicating that signature of the first signature block is required before a signature of the second signature block can be entered; and receive a signature of the presented portion of the real estate transaction documents, wherein the received signature is associated with at least the first signature block. | 18. A system for managing real estate transaction documents, the system comprising: a memory storing real estate transaction documents; and a document manager adapted to: receive a request for access to real estate transaction documents; presenting a first portion of the real estate documents including a first signature block and a second signature block; block presentation of a second portion of the real estate transaction documents based on an identity of a user currently logged into a system for managing real estate transaction documents; identify the first signature block and the second signature block by presenting one or more signature indicators in the real estate transaction documents, wherein a signature indicator is associated with a signature block; request signature of the first signature block of the first portion of the real estate transaction documents; prior to receiving the requested signature, receive a request to enter a signature of the second signature block of the first portion of the real estate transaction documents; determine that the request to enter the signature of the second signature block prior to receiving the requested signature violates at least one rule prohibiting signature of the second signature block; inhibit signature of the second signature block while the first signature block is unsigned; present a notification indicating that signature of the first signature block is required before a signature of the second signature block can be entered; and receive a signature of the presented portion of the real estate transaction documents, wherein the received signature is associated with at least the first signature block. 20. The system of claim 18 wherein the memory stores rules based on at least one of government rules or industry standards; and further comprising a rules engine configured to apply the rules to the real estate transaction documents. | 0.614238 |
8,082,308 | 1 | 8 | 1. A server-based system for managing tasks, the system comprising: a. a hardware server that maintains multiple workspaces having varying access rights, wherein at least some of the unrelated workspaces have the same names; b. the server also maintaining multiple tasks in the workspaces having varying access rights for different users; c. the server configured to receive an e-mail from any user, the e-mail including the system's global e-mail address as one of recipients in “to”, “cc”, or “bcc” field; d. the server, based on the email address of the sender, configured to find workspaces and tasks to which the sender has access; e. the server, based on the subject of the email or body of the email, configured to identify workspaces by its non-unique name; f. the server configured to add a task to a workspace that satisfies both (d) and (e); g. the server configured to control access to the task based on access rights to the workspace and based on the data from the email by permitting access to the task by a subset of users of the system; and h. the server configured to enable collaboration on the task by the subset of users. | 1. A server-based system for managing tasks, the system comprising: a. a hardware server that maintains multiple workspaces having varying access rights, wherein at least some of the unrelated workspaces have the same names; b. the server also maintaining multiple tasks in the workspaces having varying access rights for different users; c. the server configured to receive an e-mail from any user, the e-mail including the system's global e-mail address as one of recipients in “to”, “cc”, or “bcc” field; d. the server, based on the email address of the sender, configured to find workspaces and tasks to which the sender has access; e. the server, based on the subject of the email or body of the email, configured to identify workspaces by its non-unique name; f. the server configured to add a task to a workspace that satisfies both (d) and (e); g. the server configured to control access to the task based on access rights to the workspace and based on the data from the email by permitting access to the task by a subset of users of the system; and h. the server configured to enable collaboration on the task by the subset of users. 8. The system of claim 1 , wherein the system's address does not vary from user to user or from task to task. | 0.802536 |
9,135,583 | 1 | 2 | 1. A non-transitory computer-readable medium having stored thereon processor-executable instructions that when executed by a processor result in the following: receiving, at a query technique engine, continuous query definition parameters from a user via a graphical user interface; retrieving, at the query technique engine, semantic layer information associated with an event processing engine, the event processing engine being adapted to receive an event stream; based on the continuous query definition parameters from the user, automatically creating at the query technique engine a pre-fetch query to pre-fetch historical data from a database using a pull-model; automatically creating an event processing language statement, by a processor at the query technique engine, the event processing language statement being created based on (i) the continuous query definition parameters from the user and (ii) the semantic layer information; and providing the event processing language statement to the complex event processing engine so as to establish a continuous query, the continuous query providing at least one output data value based on both the pre-fetched historical data and new push-model events in the event stream. | 1. A non-transitory computer-readable medium having stored thereon processor-executable instructions that when executed by a processor result in the following: receiving, at a query technique engine, continuous query definition parameters from a user via a graphical user interface; retrieving, at the query technique engine, semantic layer information associated with an event processing engine, the event processing engine being adapted to receive an event stream; based on the continuous query definition parameters from the user, automatically creating at the query technique engine a pre-fetch query to pre-fetch historical data from a database using a pull-model; automatically creating an event processing language statement, by a processor at the query technique engine, the event processing language statement being created based on (i) the continuous query definition parameters from the user and (ii) the semantic layer information; and providing the event processing language statement to the complex event processing engine so as to establish a continuous query, the continuous query providing at least one output data value based on both the pre-fetched historical data and new push-model events in the event stream. 2. The computer-readable medium of claim 1 , wherein execution of the instructions further results in: joining the historical data with information associated with events in the event stream. | 0.851014 |
10,083,031 | 3 | 4 | 3. The method of claim 2 , wherein said building said behavior evolution model comprises: utilizing description information and structure of a source code of said application to evaluate or refine or both evaluate and refine, the identified one or more structured features. | 3. The method of claim 2 , wherein said building said behavior evolution model comprises: utilizing description information and structure of a source code of said application to evaluate or refine or both evaluate and refine, the identified one or more structured features. 4. The method of claim 3 , wherein said automatically extracting comprises: extracting, using said processor, feature related description units, said units comprising keywords or structure characteristics, identifying, by said processor device, potential umbrella features based on said keywords or structure characteristics; generating said low-level features for each potential umbrella feature based on its nearby information. | 0.646623 |
7,933,843 | 1 | 2 | 1. A computer-implemented method for a highly automated media analysis of influencer networks, comprising: defining, by an application of a computerized selection process of a computer that considers user-entered criteria, one or more scopes of media content to be included in an analysis project; retrieving, by the computer, relevant media content from a plurality of providers as defined by the one or more scopes of the analysis project, the media content including published text articles and a body of text for each of the text articles; extracting, by an application of an automatic computerized, linguistic-based and statistically-supported entity extraction process, entities from the text articles, the entities being data including names of people, organizations, locations, and brands recited in the body of text of the text articles in the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a functional role of each of the entities for each text article of the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a favorability score for each of the entities for each text article of the received media content; storing the entities in a relational database, where the entities that are co-cited in a body of text of the text articles are linked to each other for an associated text article; performing, by the computer, a first computation characterizing a network of influence relationships between each of the entities and each text article of the retrieved media content based on the extracted information and the manually associated functional role and favorability of each of the entities; and performing, by the computer, a second computation characterizing connection properties of individual entities with respect to the other entities; performing, by the computer, a third computation characterizing connection properties of at least a portion of the overall network of influence, the third computation to include a value for the network's cohesion property and density property; and outputting a result of the first, second, and third computations to produce a graphical, interactive representation of the network of influence in which a user may select individual entities to examine their associated connection properties, link to other documents, and link to web pages related to the entities, and combinations thereof. | 1. A computer-implemented method for a highly automated media analysis of influencer networks, comprising: defining, by an application of a computerized selection process of a computer that considers user-entered criteria, one or more scopes of media content to be included in an analysis project; retrieving, by the computer, relevant media content from a plurality of providers as defined by the one or more scopes of the analysis project, the media content including published text articles and a body of text for each of the text articles; extracting, by an application of an automatic computerized, linguistic-based and statistically-supported entity extraction process, entities from the text articles, the entities being data including names of people, organizations, locations, and brands recited in the body of text of the text articles in the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a functional role of each of the entities for each text article of the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a favorability score for each of the entities for each text article of the received media content; storing the entities in a relational database, where the entities that are co-cited in a body of text of the text articles are linked to each other for an associated text article; performing, by the computer, a first computation characterizing a network of influence relationships between each of the entities and each text article of the retrieved media content based on the extracted information and the manually associated functional role and favorability of each of the entities; and performing, by the computer, a second computation characterizing connection properties of individual entities with respect to the other entities; performing, by the computer, a third computation characterizing connection properties of at least a portion of the overall network of influence, the third computation to include a value for the network's cohesion property and density property; and outputting a result of the first, second, and third computations to produce a graphical, interactive representation of the network of influence in which a user may select individual entities to examine their associated connection properties, link to other documents, and link to web pages related to the entities, and combinations thereof. 2. The computer-implemented method of claim 1 , wherein said entity extraction process can handle a very high volume media content data. | 0.880282 |
9,589,563 | 9 | 13 | 9. A speech recognition system comprising: a memory configured to store: a corpus including a plurality of complex proper names; and a model for a speech recognizer; and a processor operatively connected to the memory, the processor being configured to: perform natural language processing to generate syntactic structure corresponding to a plurality of words in one of the plurality of complex proper names in the corpus; generate a plurality of candidate partial names corresponding to the one complex proper name using a machine learning process with reference to the syntactic structure corresponding to the one complex proper name and the plurality of words in the one complex proper name, wherein the one complex proper name is divided into categories of syntactic units and each of the plurality of candidate partial names comprises a subset of words from the plurality of words contained within the one complex proper name and the subset of words classified into a specific syntactic category; select only a portion of the plurality of candidate partial names based on at least one syntactic structural identifier of at least one phrase in each candidate partial name to provide a modified list of candidate partial names; incorporate the modified list of candidate partial names based on the phonetic transcription into the model for the speech recognizer to recognize partial names in a speech recognition process; store the model for the speech recognizer in the memory; receive speech input from a user comprising a candidate partial name from the modified candidate partial names; perform speech recognition, using the model, on the received speech; and identify the one complex proper name based on the recognized speech and performing an action on a user device based on the identified one complex proper name. | 9. A speech recognition system comprising: a memory configured to store: a corpus including a plurality of complex proper names; and a model for a speech recognizer; and a processor operatively connected to the memory, the processor being configured to: perform natural language processing to generate syntactic structure corresponding to a plurality of words in one of the plurality of complex proper names in the corpus; generate a plurality of candidate partial names corresponding to the one complex proper name using a machine learning process with reference to the syntactic structure corresponding to the one complex proper name and the plurality of words in the one complex proper name, wherein the one complex proper name is divided into categories of syntactic units and each of the plurality of candidate partial names comprises a subset of words from the plurality of words contained within the one complex proper name and the subset of words classified into a specific syntactic category; select only a portion of the plurality of candidate partial names based on at least one syntactic structural identifier of at least one phrase in each candidate partial name to provide a modified list of candidate partial names; incorporate the modified list of candidate partial names based on the phonetic transcription into the model for the speech recognizer to recognize partial names in a speech recognition process; store the model for the speech recognizer in the memory; receive speech input from a user comprising a candidate partial name from the modified candidate partial names; perform speech recognition, using the model, on the received speech; and identify the one complex proper name based on the recognized speech and performing an action on a user device based on the identified one complex proper name. 13. The system of claim 9 , the processor being further configured to: generate the plurality of partial proper name candidates using Conditional Maximum Entropy (CME). | 0.538462 |
9,239,894 | 12 | 14 | 12. The method of claim 11 , further comprising determining, by the at least one computer processor, a stability of the distribution parameter comprising determining an approach based at least in part on a type of failure of the part of the power system. | 12. The method of claim 11 , further comprising determining, by the at least one computer processor, a stability of the distribution parameter comprising determining an approach based at least in part on a type of failure of the part of the power system. 14. The method of claim 12 , wherein determining, by the at least one computer processor, the stability of the distribution model further comprises, for a given set of initial parameters, comparing a first Beta of the distribution model against one or more additional Betas of the distribution model, when the comparison yields a difference greater than approximately 1% and a Beta converges as the given set of initial parameters increases, recommending the distribution model with at least one initial parameter associated with a converged Beta, and when the comparison yields a difference greater than approximately 1% and a Beta increases as the given set of initial parameters increases, determining a model with at least one of a pre-determined Beta or at a higher or lower level of initial parameters. | 0.5 |
8,380,492 | 9 | 16 | 9. A document cleaning system for cleaning an electronic document, comprising: a memory; one or more processors, configured to: identify at least one sentence in the electronic document; numerically represent features of the sentence to obtain a numeric feature representation associated with the sentence; input the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and remove sentences determined to be bad sentences from the electronic document to create a cleaned document, wherein numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence comprises: creating a part of speech feature vector representation by performing part of speech tagging on each word in the sentence and determining a unique number associated with each part-of-speech corresponding to each word in the sentence, each position in the part of speech feature vector representation indicating a frequency of occurrence of a part of speech tag; creating a rule vector feature representation by determining whether the sentence satisfies a plurality of predetermined rules, each position in the rule vector feature representation indicating whether the sentence satisfies a particular one of the plurality of predetermined rules; and obtaining the numeric feature representation by concatenating the part of speech feature vector representation and the rule vector feature representation. | 9. A document cleaning system for cleaning an electronic document, comprising: a memory; one or more processors, configured to: identify at least one sentence in the electronic document; numerically represent features of the sentence to obtain a numeric feature representation associated with the sentence; input the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and remove sentences determined to be bad sentences from the electronic document to create a cleaned document, wherein numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence comprises: creating a part of speech feature vector representation by performing part of speech tagging on each word in the sentence and determining a unique number associated with each part-of-speech corresponding to each word in the sentence, each position in the part of speech feature vector representation indicating a frequency of occurrence of a part of speech tag; creating a rule vector feature representation by determining whether the sentence satisfies a plurality of predetermined rules, each position in the rule vector feature representation indicating whether the sentence satisfies a particular one of the plurality of predetermined rules; and obtaining the numeric feature representation by concatenating the part of speech feature vector representation and the rule vector feature representation. 16. The document cleaning system of claim 9 , wherein at least one of the rules is satisfied when a word contains a date or time, and wherein the numeric feature representation indicates the number of words in the sentence containing a date or time. | 0.752976 |
9,910,914 | 1 | 5 | 1. A computer-implemented, informational retrieval system for real-time, interactive semantic curation from a networked database, the system comprising: (a) a gloss vector engine configured with means to generate semantic gloss vectors for data mining by unsupervised machine learning; (b) a deconstruction engine configured with means to identify well-formed sentences; (c) a data discovery engine configured with means to identify indirect communicating links; (d) a collocation engine configured with means to identify compound nouns; (e) a disambiguation engine configured with means to assign nouns that fit the context of the sentence in which said nouns occur; (f) a generic noun disambiguation engine configured with means to identify context shifts produced by use of nouns selected from the group of generic nouns, common nouns; (g) a pronoun disambiguation engine configured with means to link common nouns to proper corresponding nouns; (h) a data evaluation engine configured with means to identify well-formed sentences containing information of maximal semantic value; (i) a retrieval engine configured with means to return information with maximal semantic value score for a given search term; (j) a context targeting engine configured with means to display in context the specific output sentence that is generated by the input query, in the context of the source article containing said sentence; wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. | 1. A computer-implemented, informational retrieval system for real-time, interactive semantic curation from a networked database, the system comprising: (a) a gloss vector engine configured with means to generate semantic gloss vectors for data mining by unsupervised machine learning; (b) a deconstruction engine configured with means to identify well-formed sentences; (c) a data discovery engine configured with means to identify indirect communicating links; (d) a collocation engine configured with means to identify compound nouns; (e) a disambiguation engine configured with means to assign nouns that fit the context of the sentence in which said nouns occur; (f) a generic noun disambiguation engine configured with means to identify context shifts produced by use of nouns selected from the group of generic nouns, common nouns; (g) a pronoun disambiguation engine configured with means to link common nouns to proper corresponding nouns; (h) a data evaluation engine configured with means to identify well-formed sentences containing information of maximal semantic value; (i) a retrieval engine configured with means to return information with maximal semantic value score for a given search term; (j) a context targeting engine configured with means to display in context the specific output sentence that is generated by the input query, in the context of the source article containing said sentence; wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. 5. The collocation engine in the computer-implemented, information retrieval system of claim 1 , further comprising a module with means to identify one or more collocation words and replace said words with compound noun equivalents. | 0.751073 |
8,352,857 | 16 | 18 | 16. A non-transitory storage medium storing instructions executable by a digital processor to perform reference identification and resolution to identify reference text fragments in a document and associate referenced object text fragments in the document with the identified reference text fragments using a method comprising: identifying a set of candidate object text fragments from the document wherein each candidate object text fragment includes at least a reference number, the set of candidate text object fragments including both object text fragments and reference text fragments, the identifying not differentiating between object text fragments and reference text fragments; abstracting reference profiles from the set of candidate object text fragments, each reference profile specifying at least a reference number and an object type identifier; pairing a reference profile with an object text fragment of the set of candidate object text fragments containing that contains the reference number of the reference profile; repeating the pairing to associate reference profiles with object text fragments wherein the pairing and repeated pairing are performed substantially simultaneously based on (i) likelihood measures of candidate pairings of reference profiles and text fragments of the document and (ii) constraints including at least a constraint that each reference profile and each object text fragment belong to only one pairing; associating a reference text fragment of the set of candidate object text fragments satisfying one of the reference profiles with the object text fragment paired with the satisfied reference profile; and repeating the associating to associate reference text fragments of the document with object text fragments. | 16. A non-transitory storage medium storing instructions executable by a digital processor to perform reference identification and resolution to identify reference text fragments in a document and associate referenced object text fragments in the document with the identified reference text fragments using a method comprising: identifying a set of candidate object text fragments from the document wherein each candidate object text fragment includes at least a reference number, the set of candidate text object fragments including both object text fragments and reference text fragments, the identifying not differentiating between object text fragments and reference text fragments; abstracting reference profiles from the set of candidate object text fragments, each reference profile specifying at least a reference number and an object type identifier; pairing a reference profile with an object text fragment of the set of candidate object text fragments containing that contains the reference number of the reference profile; repeating the pairing to associate reference profiles with object text fragments wherein the pairing and repeated pairing are performed substantially simultaneously based on (i) likelihood measures of candidate pairings of reference profiles and text fragments of the document and (ii) constraints including at least a constraint that each reference profile and each object text fragment belong to only one pairing; associating a reference text fragment of the set of candidate object text fragments satisfying one of the reference profiles with the object text fragment paired with the satisfied reference profile; and repeating the associating to associate reference text fragments of the document with object text fragments. 18. The storage medium as set forth in claim 16 , wherein the pairing and repeated pairing are performed using integer linear programming to optimize the likelihood measures of candidate pairings of reference profiles and text fragments of the document subject to the constraints including at least the constraint that each reference profile and each object text fragment belong to only one pairing. | 0.538194 |
8,798,519 | 2 | 5 | 2. A method for creating a curriculum unit in a learning management system comprising the steps of: creating, at a computer server, in the learning management system at least one programmed project associated with the curriculum unit, the programmed project comprising: a) at least one instruction set specifying at least one rule capable of reacting differently to different inputs; and b) at least one executable, social network-based learning object having at least one associated attributes wherein the at least one rule is capable of reacting dynamically to inputs adapted to the rule for controlling the at least one attribute associated with the object and triggering an event based on the at least one attribute associated with the object or other inputs and wherein the at least one instruction set specifies a manner of use in which the at least one executable, social network-based learning object can be executed; setting, at the computer server, the properties for the curriculum unit in the learning management system; creating, at the computer server, at least one state for the at least one programmed project; retrieving, at the computer server, the instruction set independently from the executable, social network-based learning object and determining at least one event for the at least one state in the learning management system based on the at least one rule and the at least one retrieved instruction set; and defining, at the computer server, at least one role of at least one participant in the learning management system with respect to the curriculum unit. | 2. A method for creating a curriculum unit in a learning management system comprising the steps of: creating, at a computer server, in the learning management system at least one programmed project associated with the curriculum unit, the programmed project comprising: a) at least one instruction set specifying at least one rule capable of reacting differently to different inputs; and b) at least one executable, social network-based learning object having at least one associated attributes wherein the at least one rule is capable of reacting dynamically to inputs adapted to the rule for controlling the at least one attribute associated with the object and triggering an event based on the at least one attribute associated with the object or other inputs and wherein the at least one instruction set specifies a manner of use in which the at least one executable, social network-based learning object can be executed; setting, at the computer server, the properties for the curriculum unit in the learning management system; creating, at the computer server, at least one state for the at least one programmed project; retrieving, at the computer server, the instruction set independently from the executable, social network-based learning object and determining at least one event for the at least one state in the learning management system based on the at least one rule and the at least one retrieved instruction set; and defining, at the computer server, at least one role of at least one participant in the learning management system with respect to the curriculum unit. 5. The method of claim 2 further comprising adding another executable, social network-based learning object associated with the at least one programmed project to the curriculum unit in the learning management system. | 0.544118 |
8,762,469 | 20 | 24 | 20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. | 20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 24. The method of claim 20 , wherein the contextual information includes information from one or more sensors on the portable electronic device. | 0.829787 |
7,801,912 | 1 | 4 | 1. A system, comprising: one or more computer devices configured to implement a web services platform configured to provide a web service interface to a searchable data service, wherein the web services platform is configured to receive service requests from a plurality of client applications in accordance with the web service interface, wherein the service requests comprise query requests and storage requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests and storage requests; and a plurality of computer devices configured to implement a plurality of nodes configured to participate in the searchable data service to: store searchable data service objects specified in received storage requests in respective searchable indexes for a plurality of independent data stores used by the client applications, wherein the searchable indexes are on the plurality of nodes, wherein the data stores are on one or more storage devices each on a network and separate from the one or more computer devices that implement the plurality of nodes configured to participate in the searchable data service, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; locate sets of one or more searchable data service objects from the searchable indexes that satisfy received query requests, wherein the received query requests specify one of the searchable indexes; and return at least the entity identifiers from the sets of one or more searchable data service objects that satisfy the query requests to the client applications in accordance with the web service interface. | 1. A system, comprising: one or more computer devices configured to implement a web services platform configured to provide a web service interface to a searchable data service, wherein the web services platform is configured to receive service requests from a plurality of client applications in accordance with the web service interface, wherein the service requests comprise query requests and storage requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests and storage requests; and a plurality of computer devices configured to implement a plurality of nodes configured to participate in the searchable data service to: store searchable data service objects specified in received storage requests in respective searchable indexes for a plurality of independent data stores used by the client applications, wherein the searchable indexes are on the plurality of nodes, wherein the data stores are on one or more storage devices each on a network and separate from the one or more computer devices that implement the plurality of nodes configured to participate in the searchable data service, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; locate sets of one or more searchable data service objects from the searchable indexes that satisfy received query requests, wherein the received query requests specify one of the searchable indexes; and return at least the entity identifiers from the sets of one or more searchable data service objects that satisfy the query requests to the client applications in accordance with the web service interface. 4. The system as recited in claim 1 , wherein the plurality of nodes comprises one or more query nodes each configured to maintain a local query cache of responses to previous query requests. | 0.900624 |
9,678,619 | 10 | 11 | 10. The system of claim 8 where the grouping results in a group that contains the some of the various windows. | 10. The system of claim 8 where the grouping results in a group that contains the some of the various windows. 11. The system of claim 10 where the windows in the group are related to each other by at least a portion of the switches. | 0.5 |
10,108,712 | 7 | 8 | 7. The system of claim 6 further comprising: a storage memory configured to store a set of standardized rewrites comprising the first standardized query rewrite, and configured to communicate the set of standardized rewrites to the search engine after the QRIL processor device has processed each QRIL record of the one or more QRIL records. | 7. The system of claim 6 further comprising: a storage memory configured to store a set of standardized rewrites comprising the first standardized query rewrite, and configured to communicate the set of standardized rewrites to the search engine after the QRIL processor device has processed each QRIL record of the one or more QRIL records. 8. The system of claim 7 further comprising: a query transcoding device coupled to the QRIL record database, wherein the query transcoding device comprises: an input module configured to receive, from a first query rewrite source device, a first set of query rewrite data, wherein the first set of query rewrite data comprises constraint data, metaflag data, and rewrite data, wherein the constraint data comprises at least the first trigger value, and wherein the rewrite data identifies at least the first query rewrite value associated with the first trigger value; a data parser module coupled to the input module configured to process the first set of query data to identify the first trigger and the first query rewrite value, and to communicate parsed query data to one or more identifier module to identify the first query rewrite type associated with the first set of query rewrite data from a plurality of query rewrite types; a query rewrite input language (QRIL) record generation and formatting module configured to generate the first QRIL record from the first set of query rewrite data, wherein the first QRIL record comprises the first trigger value, the first query rewrite value, and the query rewrite type metaflag, and wherein the QRIL record generation and formatting module is configured to generate a category constraint value, a merchant site constraint value, and a query origination country value as part of the first QRIL record based on the analyzing of the query rewrite data by the constraint identifier module; and a constraint identifier module coupled to the data parser module configured to analyze the first set of query rewrite data to identify one or more constraints associated with application of the first trigger value to a user query. | 0.5 |
9,836,451 | 11 | 15 | 11. A computer system, comprising: a computer memory; and a hardware processor interoperably coupled with the computer memory and configured to perform operations comprising: identifying an expression for validation by a parser, the expression represented as a natural language input including a set of phrases; iteratively converting each of the phrases of the natural language input into a set of tokens, wherein converting each phrase includes: determining whether a current phrase matches a pre-defined token of a plurality of pre-defined tokens associated with a known grammar rule; in response to determining that the current phrase matches a pre-defined token associated with a known grammar rule, generating a token for the current phrase for use in validating the expression; in response to determining that the current phrase does not match a pre-defined token associated with a known grammar rule, the current phrase comprising an unrecognized string of characters: comparing the unrecognized string of characters to a plurality of dynamic tokens included in an external pool of tokens, the plurality of dynamic tokens included in the external pool of tokens different than the plurality of pre-defined tokens associated with the known grammar rule; identifying a dynamic token from the external pool of tokens corresponding to the unrecognized string of characters; identifying a type of the identified dynamic token, wherein the identified type is one of a string, a number, or a date; and generating a generic token for the current phrase based on the identified type of the identified dynamic token, wherein the generic token is a character string corresponding to the identified type of the identified dynamic token; and replacing the identified dynamic token with the generic token for use in validating the expression; generating a tokenized expression by combining the generated tokens; and validating the tokenized expression. | 11. A computer system, comprising: a computer memory; and a hardware processor interoperably coupled with the computer memory and configured to perform operations comprising: identifying an expression for validation by a parser, the expression represented as a natural language input including a set of phrases; iteratively converting each of the phrases of the natural language input into a set of tokens, wherein converting each phrase includes: determining whether a current phrase matches a pre-defined token of a plurality of pre-defined tokens associated with a known grammar rule; in response to determining that the current phrase matches a pre-defined token associated with a known grammar rule, generating a token for the current phrase for use in validating the expression; in response to determining that the current phrase does not match a pre-defined token associated with a known grammar rule, the current phrase comprising an unrecognized string of characters: comparing the unrecognized string of characters to a plurality of dynamic tokens included in an external pool of tokens, the plurality of dynamic tokens included in the external pool of tokens different than the plurality of pre-defined tokens associated with the known grammar rule; identifying a dynamic token from the external pool of tokens corresponding to the unrecognized string of characters; identifying a type of the identified dynamic token, wherein the identified type is one of a string, a number, or a date; and generating a generic token for the current phrase based on the identified type of the identified dynamic token, wherein the generic token is a character string corresponding to the identified type of the identified dynamic token; and replacing the identified dynamic token with the generic token for use in validating the expression; generating a tokenized expression by combining the generated tokens; and validating the tokenized expression. 15. The system of claim 11 , wherein each dynamic token is associated with a type. | 0.79602 |
6,092,045 | 1 | 5 | 1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of: a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech. | 1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of: a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech. 5. The method of claim 1 wherein the models comprise groups of representations of phonemes. | 0.91165 |
9,055,148 | 21 | 22 | 21. The method of claim 15 , further comprising: performing a noun extraction process in which a part-of-speech (pos) tagger is used to tag lines in the chat based on pos information. | 21. The method of claim 15 , further comprising: performing a noun extraction process in which a part-of-speech (pos) tagger is used to tag lines in the chat based on pos information. 22. The method of claim 21 , wherein a first noun from the line of chat text is extracted based on the hypothesis that most of the time the product name is mentioned as the first noun. | 0.5 |
8,996,568 | 1 | 4 | 1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. | 1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. 4. The method of claim 1 , wherein the query comprises a combination of an AND and an OR query. | 0.9 |
8,752,011 | 1 | 10 | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. 10. The method of claim 1 wherein the graphical pattern identifies a kind of shape to be displayed by one of the application objects and a set of application methods of the application object for reading and changing attributes of the shape. | 0.825615 |
8,751,422 | 1 | 7 | 1. A system comprising: a client application configured to issue query requests comprising a string query and a plurality of contextual metadata regarding the string query, wherein said string query requires string analysis; a string analysis module configured to provide the client application with results of the string analysis responsive to issued query requests, said string analysis module further comprising: a plurality of string analysis algorithms representing different string analysis techniques; and a dynamic string analysis handler configured to, when in a training mode, utilize a heuristic strategy to synthesize a string analysis algorithm selection policy based upon interactions with the client application in an instructional environment, wherein an interaction comprises at least a query request from the client application, a response to the query request by the dynamic string analysis handler, and a selection feedback regarding the response from the client application, wherein the query request of the interactions utilizes a subset of string queries expected to be generated by the client application in an operational environment, and, when in a production mode, utilize the string analysis algorithm selection policy to dynamically select a string analysis algorithm from the plurality of string analysis algorithms to provide responses to query requests issued by the client application in the operational environment. | 1. A system comprising: a client application configured to issue query requests comprising a string query and a plurality of contextual metadata regarding the string query, wherein said string query requires string analysis; a string analysis module configured to provide the client application with results of the string analysis responsive to issued query requests, said string analysis module further comprising: a plurality of string analysis algorithms representing different string analysis techniques; and a dynamic string analysis handler configured to, when in a training mode, utilize a heuristic strategy to synthesize a string analysis algorithm selection policy based upon interactions with the client application in an instructional environment, wherein an interaction comprises at least a query request from the client application, a response to the query request by the dynamic string analysis handler, and a selection feedback regarding the response from the client application, wherein the query request of the interactions utilizes a subset of string queries expected to be generated by the client application in an operational environment, and, when in a production mode, utilize the string analysis algorithm selection policy to dynamically select a string analysis algorithm from the plurality of string analysis algorithms to provide responses to query requests issued by the client application in the operational environment. 7. The system of claim 1 , wherein the plurality of contextual metadata comprises at least parameters describing a level of complexity of software code originating the string query, a type of string analysis typically used for the string query, and a performance type of the software code originating the string query. | 0.738056 |
6,167,565 | 5 | 7 | 5. A method in a computer system for marshaling of a parameter for inter-language invocation of functions between a first language and a second language, the parameter to be marshaled having a first type in the first language and a second type in the second language, the method comprising: when a computer program implemented in the first language invokes a function implemented in the second language, determining that a parameter being passed to the function requires custom marshaling; creating for the invoked function an in stub that invokes custom marshaling code for converting the passed parameter of the first type to a parameter of the second type and an out stub that invokes custom marshaling code for converting a returned parameter of the second type to a parameter of the first type; executing the in stub, thereby converting the passed parameter of the first type to a parameter of the second type; invoking the function implemented in the second language and passing the parameter converted to the second type; and after invocation of the function, executing the out stub, thereby converting the parameter of the second type to a parameter of the first type. | 5. A method in a computer system for marshaling of a parameter for inter-language invocation of functions between a first language and a second language, the parameter to be marshaled having a first type in the first language and a second type in the second language, the method comprising: when a computer program implemented in the first language invokes a function implemented in the second language, determining that a parameter being passed to the function requires custom marshaling; creating for the invoked function an in stub that invokes custom marshaling code for converting the passed parameter of the first type to a parameter of the second type and an out stub that invokes custom marshaling code for converting a returned parameter of the second type to a parameter of the first type; executing the in stub, thereby converting the passed parameter of the first type to a parameter of the second type; invoking the function implemented in the second language and passing the parameter converted to the second type; and after invocation of the function, executing the out stub, thereby converting the parameter of the second type to a parameter of the first type. 7. The method of claim 5 wherein the first language is the C++ programming language. | 0.730769 |
7,788,652 | 1 | 2 | 1. A method, implemented at least in part by a computing device comprising a processing unit and memory, of representing type information for a typed intermediate language via objects of classes in a class hierarchy, wherein the class hierarchy comprises at least one class and a plurality of sub-classes for representing different type classifications, the method comprising: with the computing device: instantiating one or more objects of one or more of the sub-classes of the hierarchy, wherein the one or more sub-classes represent classifications of types for the typed intermediate language; and storing information in the one or more objects; wherein the typed intermediate language is capable of representing a plurality of different programming languages, and wherein the one or more objects represent type information for instructions in the typed intermediate language; wherein the classifications of types comprises a primitive type associated with a primitive type size, and wherein the primitive type size is settable to represent a constant size, the primitive type size is settable to represent a symbolic size, and the primitive type size is settable to represent an unknown size; and wherein one of the sub-classes representing a primitive type represents an unknown type, wherein the unknown type can represent any type, wherein the unknown type represents a lack of all type information, wherein a compiler drops type information by changing a known type to the unknown type during a stage of lowering, wherein the unknown type is set independently of the primitive type size, and wherein the classifications of types support an unknown type with an unknown primitive type size. | 1. A method, implemented at least in part by a computing device comprising a processing unit and memory, of representing type information for a typed intermediate language via objects of classes in a class hierarchy, wherein the class hierarchy comprises at least one class and a plurality of sub-classes for representing different type classifications, the method comprising: with the computing device: instantiating one or more objects of one or more of the sub-classes of the hierarchy, wherein the one or more sub-classes represent classifications of types for the typed intermediate language; and storing information in the one or more objects; wherein the typed intermediate language is capable of representing a plurality of different programming languages, and wherein the one or more objects represent type information for instructions in the typed intermediate language; wherein the classifications of types comprises a primitive type associated with a primitive type size, and wherein the primitive type size is settable to represent a constant size, the primitive type size is settable to represent a symbolic size, and the primitive type size is settable to represent an unknown size; and wherein one of the sub-classes representing a primitive type represents an unknown type, wherein the unknown type can represent any type, wherein the unknown type represents a lack of all type information, wherein a compiler drops type information by changing a known type to the unknown type during a stage of lowering, wherein the unknown type is set independently of the primitive type size, and wherein the classifications of types support an unknown type with an unknown primitive type size. 2. The method of claim 1 wherein at least one of the objects comprises information for a size of a type represented by the object. | 0.735772 |
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