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8,327,260 | 7 | 8 |
7. A computer-implemented method for deploying an annotation management system on a network and searching the system, the method comprising: installing the annotation management system on the network; identifying by an administrator an annotatable data item manipulated by at least one application on the network; defining at least one annotation structure of an annotation to be received from an annotation author comprising one or more annotation fields; assigning the at least one annotation structure to the data item; structuring the annotation based on a context of the annotation author; presenting the annotation on retrieval by a reader in a different format than as received from the annotation author based on a context of the reader of the annotation; receiving a query having conditions, the conditions including annotation search conditions and data search conditions; simultaneously searching both an annotation database and a data objects to produce a search result, the search result containing objects that satisfy both the annotation search conditions and the data search conditions; and presenting the search result to the user.
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7. A computer-implemented method for deploying an annotation management system on a network and searching the system, the method comprising: installing the annotation management system on the network; identifying by an administrator an annotatable data item manipulated by at least one application on the network; defining at least one annotation structure of an annotation to be received from an annotation author comprising one or more annotation fields; assigning the at least one annotation structure to the data item; structuring the annotation based on a context of the annotation author; presenting the annotation on retrieval by a reader in a different format than as received from the annotation author based on a context of the reader of the annotation; receiving a query having conditions, the conditions including annotation search conditions and data search conditions; simultaneously searching both an annotation database and a data objects to produce a search result, the search result containing objects that satisfy both the annotation search conditions and the data search conditions; and presenting the search result to the user. 8. The computer-implemented method of claim 7 , wherein defining the at least one annotation structure comprises: entering at least one category of information to be captured about the data item; and defining the at least one annotation structure based on the category.
| 0.5 |
8,543,564 | 1 | 4 |
1. An information retrieval system comprising: a plurality of databases; and a server for providing client access to the plurality of databases, wherein the server includes: database-selection means for enabling a user to select one of a first or a second set of categories, with each of the first set of categories associated with a subset of the plurality of databases and each of the second set of categories associated with a respective set of interactive control features for requesting additional category-specific information from the user; database-navigation means for providing a user-navigable directory of at least a subset of the plurality of databases, with the directory including: one or more beginning, intermediate, and terminal nodes, with each intermediate node associated with at least one of the beginning nodes and one or more of the terminal nodes, and each terminal node associated with a subset of the plurality of databases or a subset of corresponding database profiles; and one or more sets of interactive control features, with each set of control features associated with a corresponding one of the intermediate nodes for enabling the user to query a set of databases including databases associated with each terminal node that is associated with the one of the intermediate nodes; and database-discovery means for receiving a user-defined query, for executing the received query against a profile database including profiles of one or more of the plurality of databases, and for identifying one or more databases from the plurality of databases based on computed relevance of the corresponding profiles to the received query and according to a ranking of the profiles having the corresponding computed relevance based on a jurisdictional lexical analysis, wherein the query includes a plurality of terms, wherein the computed relevance includes a bias based on geographic, jurisdictional, or generic terms in the query.
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1. An information retrieval system comprising: a plurality of databases; and a server for providing client access to the plurality of databases, wherein the server includes: database-selection means for enabling a user to select one of a first or a second set of categories, with each of the first set of categories associated with a subset of the plurality of databases and each of the second set of categories associated with a respective set of interactive control features for requesting additional category-specific information from the user; database-navigation means for providing a user-navigable directory of at least a subset of the plurality of databases, with the directory including: one or more beginning, intermediate, and terminal nodes, with each intermediate node associated with at least one of the beginning nodes and one or more of the terminal nodes, and each terminal node associated with a subset of the plurality of databases or a subset of corresponding database profiles; and one or more sets of interactive control features, with each set of control features associated with a corresponding one of the intermediate nodes for enabling the user to query a set of databases including databases associated with each terminal node that is associated with the one of the intermediate nodes; and database-discovery means for receiving a user-defined query, for executing the received query against a profile database including profiles of one or more of the plurality of databases, and for identifying one or more databases from the plurality of databases based on computed relevance of the corresponding profiles to the received query and according to a ranking of the profiles having the corresponding computed relevance based on a jurisdictional lexical analysis, wherein the query includes a plurality of terms, wherein the computed relevance includes a bias based on geographic, jurisdictional, or generic terms in the query. 4. The system of claim 1 , further comprising a plurality of sample-based database profiles, with at least one of the profiles associated with one or more databases in the plurality of databases.
| 0.820111 |
9,487,167 | 17 | 18 |
17. An apparatus comprising one or more processors configured to: store a plurality of grammar elements associated with audible commands for a vehicle; identify a user input associated with the vehicle function control input element, based at least upon information received from a sensor, wherein the information is indicative of a proximity of an arm, a hand, or a finger of a user to the vehicle function control input element; select, based at least in part upon an evaluation of the identified user input, a function associated with the vehicle function control input element, wherein the function is associated with a subset of the plurality of stored grammar elements; receive audio input; identify, based upon an evaluation of the received audio input, a grammar element associated with the selected function; and output information associated with the identified grammar element.
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17. An apparatus comprising one or more processors configured to: store a plurality of grammar elements associated with audible commands for a vehicle; identify a user input associated with the vehicle function control input element, based at least upon information received from a sensor, wherein the information is indicative of a proximity of an arm, a hand, or a finger of a user to the vehicle function control input element; select, based at least in part upon an evaluation of the identified user input, a function associated with the vehicle function control input element, wherein the function is associated with a subset of the plurality of stored grammar elements; receive audio input; identify, based upon an evaluation of the received audio input, a grammar element associated with the selected function; and output information associated with the identified grammar element. 18. The apparatus of claim 17 , wherein the identified user input comprises at least one of a user gesture.
| 0.832288 |
9,639,509 | 1 | 2 |
1. A method of database replication, the method comprising: detecting, by one or more processor of a machine, a request for provision of a first document that is available for provision; updating a count of referrals upon detecting a request sent from a set of one or more networks for provision of the first document; generating a second document based on the first document, the second document being a substitute for the first document subsequent to the first document becoming unavailable for provision, the generating of the second document being responsive to a determination that the updated count of referrals has transgressed a predetermined threshold value, the generating of the second document being performed by one or more processor of the machine; and providing the second document in lieu of the first document when the first document is requested subsequent to the first document becoming unavailable upon expiration of a predetermined time of availability of the first document.
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1. A method of database replication, the method comprising: detecting, by one or more processor of a machine, a request for provision of a first document that is available for provision; updating a count of referrals upon detecting a request sent from a set of one or more networks for provision of the first document; generating a second document based on the first document, the second document being a substitute for the first document subsequent to the first document becoming unavailable for provision, the generating of the second document being responsive to a determination that the updated count of referrals has transgressed a predetermined threshold value, the generating of the second document being performed by one or more processor of the machine; and providing the second document in lieu of the first document when the first document is requested subsequent to the first document becoming unavailable upon expiration of a predetermined time of availability of the first document. 2. The method of claim 1 , wherein the first document includes an identifier of a network that referred the request.
| 0.694737 |
9,798,829 | 13 | 14 |
13. A method comprising: generating, using at least one processor, data used to display tabular data to a user, a first column of the tabular data being associated with a first entity type and non-heading rows in the tabular data representing entities of the first entity type in a knowledge document; permitting the user to select a second column of the tabular data and provide a second entity type as an object type to be associated with a labeled relationship represented by a heading of the second column; generating, using the at least one processor, an entity in the knowledge document of the second entity type that represents a value in a non-heading row in the tabular data; linking an entity of the first entity type that is associated with a non-heading row to the generated entity by the relationship; and storing an updated knowledge document in a memory.
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13. A method comprising: generating, using at least one processor, data used to display tabular data to a user, a first column of the tabular data being associated with a first entity type and non-heading rows in the tabular data representing entities of the first entity type in a knowledge document; permitting the user to select a second column of the tabular data and provide a second entity type as an object type to be associated with a labeled relationship represented by a heading of the second column; generating, using the at least one processor, an entity in the knowledge document of the second entity type that represents a value in a non-heading row in the tabular data; linking an entity of the first entity type that is associated with a non-heading row to the generated entity by the relationship; and storing an updated knowledge document in a memory. 14. The method of claim 13 , further comprising: modifying a display of the tabular data responsive to storing the updated knowledge document so that values in the second column are selectable.
| 0.856399 |
5,384,702 | 6 | 7 |
6. The method of claim 1, wherein a grammar marker of said plurality of said grammar markers is a singular-noun-subject marker.
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6. The method of claim 1, wherein a grammar marker of said plurality of said grammar markers is a singular-noun-subject marker. 7. The method of claim 6 wherein said first database includes singular-form verb conversion rules, rules governing the use of a singular noun subject in the present tense, and rules governing use of a singular noun subject in past tense.
| 0.5 |
8,370,278 | 1 | 13 |
1. One or more computer-readable storage media hardware device storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method comprising: identifying a document corpus comprising one or more documents; extracting entities within text of the one or more documents; extracting relationships between entities based on the text of the one or more documents; identifying a plurality of assertions based on the entities and relationships extracted from the text of the one or more documents; and inverting the plurality of assertions to generate a plurality of questions; and generating a question graph from the plurality of questions.
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1. One or more computer-readable storage media hardware device storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method comprising: identifying a document corpus comprising one or more documents; extracting entities within text of the one or more documents; extracting relationships between entities based on the text of the one or more documents; identifying a plurality of assertions based on the entities and relationships extracted from the text of the one or more documents; and inverting the plurality of assertions to generate a plurality of questions; and generating a question graph from the plurality of questions. 13. The one or more computer-readable storage media of claim 1 , wherein the method further comprises generating a combined graph that allows traversal among the topics, the questions, the assertions, and the one or more documents.
| 0.723684 |
6,094,506 | 1 | 2 |
1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters.
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1. A method in a computer system for generating a shape feature probability matrix for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters each sample handwritten character representing a character and having a sequence of one or more strokes each stroke represented by one of a plurality of shape features that describes a shape of the stroke; determining for each sample handwritten character a shape feature string that represents that character, the shape feature string having the shape feature of each stroke in the sequence of one or more strokes for that character, each of the shape features in a shape feature string having a place within the shape feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible combination of pairs of the plurality of shape features, generating a match count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings, in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings, and in which each of the pair of shape feature strings represents the same character; generating a total count, for all possible pairs of shape feature strings representing the plurality of handwritten characters, of all occurrences of the combination in which one of the shape features of the combination is at a place within one of the pair of shape feature strings and in which the other of the shape features of the combination is at the same place within the other of the pair of shape feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the combination of the shape features in the shape feature probability matrix, so that the stored probability values can be used to recognize handwritten characters. 2. The method of claim 1 wherein each shape feature string has a feature length indicating the number of feature shapes in the shape feature string and wherein generating the total count includes: for each of the plurality of shape features, for each of a plurality of possible places within a feature string, for each of a plurality of possible feature lengths, generating a shape/place/length count of a number of times that the shape feature occurs at the place within a shape feature string having the feature length; and for each possible combination of pairs of the plurality of shape features, for each of the plurality of possible places within a feature string, for each of the possible feature lengths, multiplying the shape/place/length count for one of the shape features of the combination by the shape/place/length count for the other shape feature of the combination for the place and the feature length to generate a product; and accumulating the generated products as the total count for the combination of shape features.
| 0.58206 |
7,734,357 | 2 | 3 |
2. The system according to claim 1 , wherein said graphics editor, when editing a graphical object, compares a consistency of a graphical user selection made by the user on a basis of the graphical object selected with an association function, and allows said data editor to be called only if the association is admissible.
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2. The system according to claim 1 , wherein said graphics editor, when editing a graphical object, compares a consistency of a graphical user selection made by the user on a basis of the graphical object selected with an association function, and allows said data editor to be called only if the association is admissible. 3. The system according to claim 2 , wherein said data editor takes the graphical user selection in said graphics editor as a basis for updating the configuration data for the graphically represented subunits.
| 0.744499 |
7,507,902 | 1 | 25 |
1. A stringed instrument comprising: an elongated instrument body; a plurality of strings coupled to said instrument body, wherein each string of said plurality of strings is under tension and spans a distance over said instrument body; a plurality of bridges, wherein each bridge of said plurality of bridges is associated with a separate string of said plurality of strings, and wherein each bridge of said plurality of bridges is slideably adjustable over a substantial portion of said span over said instrument body; a plurality of vibration-sensing transducers, wherein each transducer of said plurality of vibration-sensing transducers is associated with a separate string of said plurality of strings, and wherein each transducer of said plurality of vibration-sensing transducers generates a distinct electrical transducer signal responsive to vibrations of said associated separate string; and an interface adapted to provide transducer signals generated by said plurality of vibration-sensing transducers to a multi-channel processing system.
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1. A stringed instrument comprising: an elongated instrument body; a plurality of strings coupled to said instrument body, wherein each string of said plurality of strings is under tension and spans a distance over said instrument body; a plurality of bridges, wherein each bridge of said plurality of bridges is associated with a separate string of said plurality of strings, and wherein each bridge of said plurality of bridges is slideably adjustable over a substantial portion of said span over said instrument body; a plurality of vibration-sensing transducers, wherein each transducer of said plurality of vibration-sensing transducers is associated with a separate string of said plurality of strings, and wherein each transducer of said plurality of vibration-sensing transducers generates a distinct electrical transducer signal responsive to vibrations of said associated separate string; and an interface adapted to provide transducer signals generated by said plurality of vibration-sensing transducers to a multi-channel processing system. 25. The instrument according to claim 1 , wherein said instrument further comprises at least one control button coupled to said instrument body.
| 0.85 |
8,984,387 | 1 | 10 |
1. A method comprising: enabling a set of users to interact with a system over a network, wherein a first user and a plurality of second users belong to the set of users; generating, for the first user, within the system, content for one or more application displays to be displayed to the first user; receiving, by the system, from each user from the plurality of second users, a corresponding specification of interest in being notified about interactions of the first user; in response to receiving first text that was input by the first user, the system performing the steps of: adding the first text to sharable content, wherein the sharable content includes at least a portion of content from the one or more application displays that were generated for the first user; and causing display of first information, in a respective application display of each user from the plurality of second users, based, at least in part, on the corresponding specification of interest of each user of the plurality of second users, wherein the first information includes an access identifier that provides access to the sharable content; receiving, from a particular second user of the plurality of second users, a specification of interest in being notified about interactions of another user, wherein the other user is a different user than the first user and the particular second user; in response to receiving particular text that was input by the other user, the system causing display of another information in the respective application display of the particular second user, based, at least in part, on the specification of interest in being notified about interactions of the other user, wherein the other information includes at least a portion of the particular text; and wherein the other information is concurrently displayed with the first information in the respective application display of the particular second user.
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1. A method comprising: enabling a set of users to interact with a system over a network, wherein a first user and a plurality of second users belong to the set of users; generating, for the first user, within the system, content for one or more application displays to be displayed to the first user; receiving, by the system, from each user from the plurality of second users, a corresponding specification of interest in being notified about interactions of the first user; in response to receiving first text that was input by the first user, the system performing the steps of: adding the first text to sharable content, wherein the sharable content includes at least a portion of content from the one or more application displays that were generated for the first user; and causing display of first information, in a respective application display of each user from the plurality of second users, based, at least in part, on the corresponding specification of interest of each user of the plurality of second users, wherein the first information includes an access identifier that provides access to the sharable content; receiving, from a particular second user of the plurality of second users, a specification of interest in being notified about interactions of another user, wherein the other user is a different user than the first user and the particular second user; in response to receiving particular text that was input by the other user, the system causing display of another information in the respective application display of the particular second user, based, at least in part, on the specification of interest in being notified about interactions of the other user, wherein the other information includes at least a portion of the particular text; and wherein the other information is concurrently displayed with the first information in the respective application display of the particular second user. 10. The method of claim 1 wherein the sharable content includes identity of each user of the plurality of the second users.
| 0.88035 |
4,397,635 | 1 | 15 |
1. A method for teaching reading using an audio-visual projection device, said device including a visual display area, the method comprising the following steps: displaying a set of baseline words at a baseline portion of the display area, said words made up of letters; displaying a chosen baseline word at a main portion of the display area; configuring said chosen word at said main portion according to a first speech parameter; positioning said chosen word in said main portion according to a second speech parameter; and selectively vocalizing said chosen word simultaneously with said chosen baseline word displaying step.
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1. A method for teaching reading using an audio-visual projection device, said device including a visual display area, the method comprising the following steps: displaying a set of baseline words at a baseline portion of the display area, said words made up of letters; displaying a chosen baseline word at a main portion of the display area; configuring said chosen word at said main portion according to a first speech parameter; positioning said chosen word in said main portion according to a second speech parameter; and selectively vocalizing said chosen word simultaneously with said chosen baseline word displaying step. 15. The teaching method of claim 1 wherein said configuring step includes the step of altering the size of an individual letter of said chosen word.
| 0.706349 |
9,779,084 | 1 | 5 |
1. A system adapted to assist instructors with interactions with students, comprising: a network server comprising a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions, that when executed, receive a communication posted by a student; instructions, that when executed, receive a communication written by an instructor; instructions, that when executed, apply a psychologically-based linguistic analysis to text of the student communication and instructor communication to predict a likelihood of a student outcome with the instructor; instructions, that when executed, monitor the electronic communication between the instructor and the student to measure instructor performance; instructions, that when executed, apply a scoring algorithm to the measured instructor performance and to the analyzed text of the instructor communication to detect keywords and phrases; instructions, that when executed, generate a score for the instructor communication from the application of the scoring algorithm and from comparison of the detected keywords and phrases with a plurality of keywords and phrases stored in a library; and instructions, that when executed, create an evaluation report that provides guidance to the instructor to facilitate a responsive communication with the student based on the score for the instructor communication, wherein the responsive communication is received on a student device using a modality for the responsive communication based on the predicted likelihood of the student outcome.
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1. A system adapted to assist instructors with interactions with students, comprising: a network server comprising a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions, that when executed, receive a communication posted by a student; instructions, that when executed, receive a communication written by an instructor; instructions, that when executed, apply a psychologically-based linguistic analysis to text of the student communication and instructor communication to predict a likelihood of a student outcome with the instructor; instructions, that when executed, monitor the electronic communication between the instructor and the student to measure instructor performance; instructions, that when executed, apply a scoring algorithm to the measured instructor performance and to the analyzed text of the instructor communication to detect keywords and phrases; instructions, that when executed, generate a score for the instructor communication from the application of the scoring algorithm and from comparison of the detected keywords and phrases with a plurality of keywords and phrases stored in a library; and instructions, that when executed, create an evaluation report that provides guidance to the instructor to facilitate a responsive communication with the student based on the score for the instructor communication, wherein the responsive communication is received on a student device using a modality for the responsive communication based on the predicted likelihood of the student outcome. 5. The system of claim 1 , wherein applying the psychologically-based linguistic analysis to text of the student communication and the instructor communication provides a personality type of the student and the instructor.
| 0.529661 |
9,069,646 | 3 | 5 |
3. The non-transitory computer-readable medium of claim 1 , the operations further comprising: updating the list of object descriptions when a change event, a create event, or a delete event is detected.
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3. The non-transitory computer-readable medium of claim 1 , the operations further comprising: updating the list of object descriptions when a change event, a create event, or a delete event is detected. 5. The non-transitory computer-readable medium of claim 3 , wherein the create event is triggered when a new object is added to the repository.
| 0.506897 |
8,949,247 | 1 | 9 |
1. A method for dynamic updating of an index of a search engine, comprising: storing the index on a mass storage device of a search engine that is implemented on one or more servers, the index being an inverted index, the index comprising a dictionary that maps words to word identifiers, a posting file, and a database log that stores changes to the dictionary as the changes occur, the posting file having posting lists for each keyword of the index; generating a position list for a keyword, wherein the position list gives all locations of the keyword in the documents; inserting a record in the database log in response to each change made to the dictionary, the record including the keyword, the position list and a reference to a previous record of the same keyword in the database log, said previous entry having a reference stored in the mass storage device as the last added entry of all recently added keywords; retrieving a dictionary entry from the dictionary that corresponds to a keyword; using data indicated by the dictionary entry to read a given position list and a given delta list from the posting file, the given position list indicating positions of the given keyword, the given delta list containing changes to the given occurrence list; merging into a single position list the given position list, updates from the given delta list and given entries in the database log, the given entries in the database log indicating modifications to the given position list; and using the single position list for further processing of a search query.
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1. A method for dynamic updating of an index of a search engine, comprising: storing the index on a mass storage device of a search engine that is implemented on one or more servers, the index being an inverted index, the index comprising a dictionary that maps words to word identifiers, a posting file, and a database log that stores changes to the dictionary as the changes occur, the posting file having posting lists for each keyword of the index; generating a position list for a keyword, wherein the position list gives all locations of the keyword in the documents; inserting a record in the database log in response to each change made to the dictionary, the record including the keyword, the position list and a reference to a previous record of the same keyword in the database log, said previous entry having a reference stored in the mass storage device as the last added entry of all recently added keywords; retrieving a dictionary entry from the dictionary that corresponds to a keyword; using data indicated by the dictionary entry to read a given position list and a given delta list from the posting file, the given position list indicating positions of the given keyword, the given delta list containing changes to the given occurrence list; merging into a single position list the given position list, updates from the given delta list and given entries in the database log, the given entries in the database log indicating modifications to the given position list; and using the single position list for further processing of a search query. 9. The method according to claim 1 , wherein merging of the given position list and the given delta list is performed without including any update generation more recent than a specified generation, such that the search query can be processed for occurrences of the keyword existing at the end of the specific generation.
| 0.716431 |
9,569,424 | 1 | 6 |
1. A method for use with a voicemail transcription system that processes a voicemail message and generates a textual representation of at least a portion of the voicemail message, the method comprising: determining based, at least in part, on the textual representation of the at least a portion of the voicemail message, at least one emotion expressed in the voicemail message, wherein the determining comprises applying at least one emotion classifier to the textual representation of the at least a portion of the voicemail message; storing preference information for a user of a client device configured to receive voicemail transcriptions, wherein the preference information describes preferences for how the user of the client device wants emotion information associated with the received voicemail transcriptions to be conveyed to the user on the client device; and providing on the client device, in accordance with the stored preference information, an indication of the determined at least one emotion prior to displaying the textual representation of the at least a portion of the voicemail message on the client device, wherein providing an indication of the determined at least one emotion comprises displaying on the client device at least one graphical symbol representing the determined at least one emotion with a truncated version of the textual representation.
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1. A method for use with a voicemail transcription system that processes a voicemail message and generates a textual representation of at least a portion of the voicemail message, the method comprising: determining based, at least in part, on the textual representation of the at least a portion of the voicemail message, at least one emotion expressed in the voicemail message, wherein the determining comprises applying at least one emotion classifier to the textual representation of the at least a portion of the voicemail message; storing preference information for a user of a client device configured to receive voicemail transcriptions, wherein the preference information describes preferences for how the user of the client device wants emotion information associated with the received voicemail transcriptions to be conveyed to the user on the client device; and providing on the client device, in accordance with the stored preference information, an indication of the determined at least one emotion prior to displaying the textual representation of the at least a portion of the voicemail message on the client device, wherein providing an indication of the determined at least one emotion comprises displaying on the client device at least one graphical symbol representing the determined at least one emotion with a truncated version of the textual representation. 6. The method of claim 1 , wherein providing the indication of the determined at least one emotion comprises outputting a particular ringtone from client device, selecting a particular agent persona to communicate with the user of the client device, or providing a particular vibration output from the client device.
| 0.540698 |
8,910,113 | 8 | 21 |
8. A computing system comprising a processor with access to a computer-readable medium tangibly embodying program components, the program components comprising: a user interface module that configures the computing system to provide a graphical user interface of an application development environment, the graphical user interface depicting a runtime appearance of a plurality of interface elements of an application under development; a source management module that configures the computing system to access source code of the application under development, the source code comprising expressions that define the interface elements, the source code expressed in a declarative markup language; a refactoring module that configures the computing system to: identify, in response to selection of a plurality of interface elements in the graphical user interface, expressions corresponding to the selected interface elements, define a new declarative expression, generate at least one code segment using the identified expressions, and store the generated code segment in a computer readable medium, the stored code segment associated with the new declarative expression.
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8. A computing system comprising a processor with access to a computer-readable medium tangibly embodying program components, the program components comprising: a user interface module that configures the computing system to provide a graphical user interface of an application development environment, the graphical user interface depicting a runtime appearance of a plurality of interface elements of an application under development; a source management module that configures the computing system to access source code of the application under development, the source code comprising expressions that define the interface elements, the source code expressed in a declarative markup language; a refactoring module that configures the computing system to: identify, in response to selection of a plurality of interface elements in the graphical user interface, expressions corresponding to the selected interface elements, define a new declarative expression, generate at least one code segment using the identified expressions, and store the generated code segment in a computer readable medium, the stored code segment associated with the new declarative expression. 21. The computing system set forth in claim 8 , wherein the refactoring module is further configured to: receive, through the graphical user interface, an indication to adjust a property value associated with at least one of the plurality of interface elements; adjust the property value associated with the at least one of the plurality of interface elements; define an adjusted declarative expression, generate at least another code segment using the adjusted declarative expressions, and store the at least another code segment in the computer readable medium, the stored at least another code segment associated with the adjusted declarative expression.
| 0.5 |
9,386,046 | 1 | 13 |
1. A method for improving a statistical message classifier, the method comprising: receiving a message over a network communication interface; identifying by a processor executing instructions out of a memory a feature in the message that is associated with a junk count; testing the message with a machine classifier by the processor performing a calculation according to a logarithmic function including the junk count, wherein the machine classifier outputs a value for the statistical message classifier for storage in the memory; updating the statistical message classifier stored in the memory according to the logarithmic calculation made by the machine classifier, wherein the stored statistical message classifier corresponds to a probability that the feature in the message is spam; identifying that the message is spam based on the probability that the feature in the message is spam; and quarantining the message.
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1. A method for improving a statistical message classifier, the method comprising: receiving a message over a network communication interface; identifying by a processor executing instructions out of a memory a feature in the message that is associated with a junk count; testing the message with a machine classifier by the processor performing a calculation according to a logarithmic function including the junk count, wherein the machine classifier outputs a value for the statistical message classifier for storage in the memory; updating the statistical message classifier stored in the memory according to the logarithmic calculation made by the machine classifier, wherein the stored statistical message classifier corresponds to a probability that the feature in the message is spam; identifying that the message is spam based on the probability that the feature in the message is spam; and quarantining the message. 13. The method for improving a message classifier as recited in claim 1 , wherein updating the statistical message classifier comprises parsing the message to obtain a feature and computing a spam probability associated with the feature.
| 0.5 |
9,552,402 | 1 | 3 |
1. A computer program product for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, both the tabbed table in the XML format and the collapsible section in XML format derived from respective unstructured rich text, the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on at least one of the one or more storage devices, said one or more computer-readable tangible storage devices not including a transitory signal, the program instructions comprising: program instructions to convert unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; program instructions to transform, using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in a relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; program instructions to initiate storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in a relational database; program instructions to subsequently export the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to a web-based application; program instructions to transform, using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in a relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; program instructions to initiate storage of the collapsible section in the XHTML format in a relational database; and program instructions to subsequently export the collapsible section in the XHMTL format from the relational database to a web-based application.
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1. A computer program product for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, both the tabbed table in the XML format and the collapsible section in XML format derived from respective unstructured rich text, the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on at least one of the one or more storage devices, said one or more computer-readable tangible storage devices not including a transitory signal, the program instructions comprising: program instructions to convert unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; program instructions to transform, using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in a relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; program instructions to initiate storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in a relational database; program instructions to subsequently export the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to a web-based application; program instructions to transform, using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in a relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; program instructions to initiate storage of the collapsible section in the XHTML format in a relational database; and program instructions to subsequently export the collapsible section in the XHMTL format from the relational database to a web-based application. 3. The computer program product of claim 1 , wherein the unstructured rich text information further comprises twisties as unstructured rich text, wherein the twisties is a third type of unstructured rich text information that is twisties specific, wherein the XML files in the XML format further comprise the twisties in the XML format, and wherein the program instructions further comprise: program instructions to transform, using a third reusable stylesheet that is specific to the third type of unstructured rich text information that is twisties specific, the twisties in the XML format to an XHTML format configured for storage in the relational database.
| 0.750754 |
8,831,365 | 1 | 2 |
1. A method comprising: receiving, at a computing device, text captured from a rendered document during a text capture operation; receiving, at the computing device, supplemental information relating to circumstances under which the text capture operation was performed, the supplemental information comprising information indicating a geographical location at which the text capture operation occurs, the information indicating a geographical location at which the text capture operation occurs comprising information indicating a location as being indoors or outdoors; and determining, by the computing device and based on the captured text and the supplemental information, an action to be performed; wherein a determination of the location as being indoors or outdoors is based on light entering a sensor of an optical capture device.
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1. A method comprising: receiving, at a computing device, text captured from a rendered document during a text capture operation; receiving, at the computing device, supplemental information relating to circumstances under which the text capture operation was performed, the supplemental information comprising information indicating a geographical location at which the text capture operation occurs, the information indicating a geographical location at which the text capture operation occurs comprising information indicating a location as being indoors or outdoors; and determining, by the computing device and based on the captured text and the supplemental information, an action to be performed; wherein a determination of the location as being indoors or outdoors is based on light entering a sensor of an optical capture device. 2. The method of claim 1 , wherein determining the action to be performed comprises determining to discard at least one document from among a plurality of documents identified as having the captured text.
| 0.622222 |
7,729,913 | 19 | 21 |
19. A method for conducting database searches by telephone, the method comprising: receiving a sequence of N character utterances from a telephone user, said character utterances corresponding to respective characters of a search query; receiving an utterance of the search query from the user; interpreting the sequence of character utterances to generate a sequence of N characters; translating the sequence of N characters to a corresponding sequence of N telephone digits; and selecting a speech recognition grammar that corresponds to the sequence of N telephone digits, said speech recognition grammar corresponding to multiple different possible N-character sequences; and interpreting the utterance of the search query using the selected speech recognition grammar to generate a textual representation of the search query; wherein N is less than the number of characters in the search query as uttered by the user such that the user need not verbally spell the entire search query; wherein the method is performed by a system that comprises computer hardware; wherein the speech recognition grammar is selected from a repository of pre-generated speech recognition grammars in which different speech recognition grammars correspond to different sequences of N telephone digits, said repository of pre-generated speech recognition grammars generated by subdividing a master grammar set based on the first N characters of entries in said master grammar set.
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19. A method for conducting database searches by telephone, the method comprising: receiving a sequence of N character utterances from a telephone user, said character utterances corresponding to respective characters of a search query; receiving an utterance of the search query from the user; interpreting the sequence of character utterances to generate a sequence of N characters; translating the sequence of N characters to a corresponding sequence of N telephone digits; and selecting a speech recognition grammar that corresponds to the sequence of N telephone digits, said speech recognition grammar corresponding to multiple different possible N-character sequences; and interpreting the utterance of the search query using the selected speech recognition grammar to generate a textual representation of the search query; wherein N is less than the number of characters in the search query as uttered by the user such that the user need not verbally spell the entire search query; wherein the method is performed by a system that comprises computer hardware; wherein the speech recognition grammar is selected from a repository of pre-generated speech recognition grammars in which different speech recognition grammars correspond to different sequences of N telephone digits, said repository of pre-generated speech recognition grammars generated by subdividing a master grammar set based on the first N characters of entries in said master grammar set. 21. The method of claim 19 , wherein the speech recognition grammar comprises search queries starting with multiple different sets of N characters.
| 0.704819 |
7,496,833 | 1 | 3 |
1. A computer-based method of coding a document for presentation on a presentation apparatus, comprising: defining a structure section which specifies a structure for content of said document in terms of document elements, wherein the defining of the structure section includes defining the structure section in a hierarchical structured format which specifies the structure of said document in terms of said document elements; defining a time section including a time constraint which acts upon document elements in the structure section, wherein the defining of the time section includes defining the time section in said hierarchical structured format that includes said time constraint, wherein the time constraint specifies that the document elements it acts upon have to be presented consecutively; linking the time section with the structure section to establish the coding of the document, wherein the structure section and the time section are defined in separate sections, and wherein the coding of the document constitutes an hierarchical structured application; defining a style section in the hierarchical structured format which includes style rules specifying properties of one or more document elements selected from the structure section, the time constraint acts upon a style rule of the style section, the linking including linking the time section, style section, and the structure section to establish structural, style, and temporal coding of the document, wherein the document elements in the structure section which are acted upon by the time constraint are selected by a CSS (Cascading Style Sheets) selector syntax; and at least one of (i) presenting the coded document on a presentation apparatus and (ii) storing the coded document for subsequent presentation.
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1. A computer-based method of coding a document for presentation on a presentation apparatus, comprising: defining a structure section which specifies a structure for content of said document in terms of document elements, wherein the defining of the structure section includes defining the structure section in a hierarchical structured format which specifies the structure of said document in terms of said document elements; defining a time section including a time constraint which acts upon document elements in the structure section, wherein the defining of the time section includes defining the time section in said hierarchical structured format that includes said time constraint, wherein the time constraint specifies that the document elements it acts upon have to be presented consecutively; linking the time section with the structure section to establish the coding of the document, wherein the structure section and the time section are defined in separate sections, and wherein the coding of the document constitutes an hierarchical structured application; defining a style section in the hierarchical structured format which includes style rules specifying properties of one or more document elements selected from the structure section, the time constraint acts upon a style rule of the style section, the linking including linking the time section, style section, and the structure section to establish structural, style, and temporal coding of the document, wherein the document elements in the structure section which are acted upon by the time constraint are selected by a CSS (Cascading Style Sheets) selector syntax; and at least one of (i) presenting the coded document on a presentation apparatus and (ii) storing the coded document for subsequent presentation. 3. The method as claimed in claim 1 , wherein the time constraint specifies that the document elements it acts upon have to be presented simultaneously.
| 0.823666 |
9,122,683 | 15 | 16 |
15. The system of claim 13 , wherein one or more computing devices are further configured to at least: determine one or more first search terms based at least in part on at least a portion of the first descriptive information when no physical media product storing the particular media content is identified by searching using the first identifier and the second identifier; and search the electronic data store using the first search terms to identify second descriptive information associated with a physical media product.
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15. The system of claim 13 , wherein one or more computing devices are further configured to at least: determine one or more first search terms based at least in part on at least a portion of the first descriptive information when no physical media product storing the particular media content is identified by searching using the first identifier and the second identifier; and search the electronic data store using the first search terms to identify second descriptive information associated with a physical media product. 16. The system of claim 15 , wherein the one or more first search terms include a title associated with the particular media content.
| 0.861746 |
7,516,397 | 4 | 10 |
4. A method for generating a representation of a Web-site comprising a plurality of Web-pages, said method comprising: identifying anchor text for each of a set of hyperlinks associated with said Web-site, wherein said set of hyperlinks consists of inbound hyperlinks to said Web-site from another Web-site other than said Web-site, outbound hyperlinks from said Web-site to another Web-site other than said Web-site, and internal hyperlinks linking a plurality of said Web-pages within said Web-site, wherein said anchor text for each of the hyperlinks is associated with a node within a DOM tree that represents a structure of said Web-site, wherein said anchor text comprises a subset of words within neighboring nodes of said node within said DOM tree, and wherein said subset comprises words formatted within format tags; referring to said DOM tree to identify a set of related nodes within said DOM tree for each hyperlink anchor text, and determining a location-specific context for each anchor text, wherein said context comprises information relating to said set of related nodes within said DOM tree, wherein said location-specific context comprises a location above and before said anchor text up to a root node of said DOM tree, wherein said root node of said DOM tree corresponds to a top of a particular Web page; and combining said anchor text with a respective location-specific context for each of said set of hyperlinks, to generate a representation of said Web-site.
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4. A method for generating a representation of a Web-site comprising a plurality of Web-pages, said method comprising: identifying anchor text for each of a set of hyperlinks associated with said Web-site, wherein said set of hyperlinks consists of inbound hyperlinks to said Web-site from another Web-site other than said Web-site, outbound hyperlinks from said Web-site to another Web-site other than said Web-site, and internal hyperlinks linking a plurality of said Web-pages within said Web-site, wherein said anchor text for each of the hyperlinks is associated with a node within a DOM tree that represents a structure of said Web-site, wherein said anchor text comprises a subset of words within neighboring nodes of said node within said DOM tree, and wherein said subset comprises words formatted within format tags; referring to said DOM tree to identify a set of related nodes within said DOM tree for each hyperlink anchor text, and determining a location-specific context for each anchor text, wherein said context comprises information relating to said set of related nodes within said DOM tree, wherein said location-specific context comprises a location above and before said anchor text up to a root node of said DOM tree, wherein said root node of said DOM tree corresponds to a top of a particular Web page; and combining said anchor text with a respective location-specific context for each of said set of hyperlinks, to generate a representation of said Web-site. 10. The method according to claim 4 , further comprising identifying text within format tags in said Web-site, wherein said text comprises a predefined proximity relationship to said anchor text, and combining said anchor text and said respective location-specific context with the identified text, for each of the set of hyperlinks.
| 0.526989 |
9,946,783 | 15 | 16 |
15. One or more non-transitory computer-readable media encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying, within a set of documents that have been classified within a hierarchical taxonomy using a classification algorithm, documents having a classification confidence level that is below a predetermined confidence level threshold; disassociating the identified documents from their respective classifications based on the classification level being below the predetermined confidence level threshold; obtaining, from a different classifier, a new classification within the hierarchical taxonomy for each of the identified documents; associating each of the newly classified documents with a highest classification confidence level for its respective new classification; including the newly classified documents in a trusted corpus of documents that are used to train the classification algorithm; determining a distribution of classifications of the newly classified documents within the trusted corpus of documents; updating the classification algorithm based on the trusted corpus of documents, such that the classification algorithm is configured to classify documents to promote a classification distribution that is in accordance with the determined distribution of classifications; and applying the updated classification algorithm to at least a portion of the set of documents to obtain new classifications within the taxonomy or new classification confidence levels for the portion of the set of documents, such that the at least a portion of the set of documents are classified in accordance with the classification distribution.
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15. One or more non-transitory computer-readable media encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying, within a set of documents that have been classified within a hierarchical taxonomy using a classification algorithm, documents having a classification confidence level that is below a predetermined confidence level threshold; disassociating the identified documents from their respective classifications based on the classification level being below the predetermined confidence level threshold; obtaining, from a different classifier, a new classification within the hierarchical taxonomy for each of the identified documents; associating each of the newly classified documents with a highest classification confidence level for its respective new classification; including the newly classified documents in a trusted corpus of documents that are used to train the classification algorithm; determining a distribution of classifications of the newly classified documents within the trusted corpus of documents; updating the classification algorithm based on the trusted corpus of documents, such that the classification algorithm is configured to classify documents to promote a classification distribution that is in accordance with the determined distribution of classifications; and applying the updated classification algorithm to at least a portion of the set of documents to obtain new classifications within the taxonomy or new classification confidence levels for the portion of the set of documents, such that the at least a portion of the set of documents are classified in accordance with the classification distribution. 16. The non-transitory computer-readable media of claim 15 , wherein the classification algorithm includes a plurality of classifiers, the operations further comprising assigning, by each of the classifiers, a different classification to documents that are recognized by the classifier as having attributes that match the classification.
| 0.58701 |
9,818,448 | 4 | 5 |
4. A media editing system comprising: a first digital audio workstation comprising a first automation system and first audio storage, the first digital audio station in data communication with a second digital audio workstation, the second digital audio workstation comprising a second automation system and second audio storage, wherein the first digital audio workstation is configured to: receive from the second digital audio workstation an audio track and time-based metadata pertaining to the audio track; enabling a user of the first digital audio workstation to: actuate a first single control of the first digital audio workstation to select whether the first digital audio workstation (i) monitors playback of the audio track and the time-based metadata received from the second digital audio workstation; or (ii) monitors playback of a corresponding audio track and time-based metadata pertaining to the audio track stored on the first digital audio workstation; and actuate a second single control of the first digital audio workstation to cause the first digital audio workstation to start recording both the audio track and the time-based metadata pertaining to the audio track received from the second digital audio workstation, wherein recording the received audio and time-based metadata overwrites a temporally corresponding portion of the audio track and time-based metadata stored on the first digital audio workstation.
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4. A media editing system comprising: a first digital audio workstation comprising a first automation system and first audio storage, the first digital audio station in data communication with a second digital audio workstation, the second digital audio workstation comprising a second automation system and second audio storage, wherein the first digital audio workstation is configured to: receive from the second digital audio workstation an audio track and time-based metadata pertaining to the audio track; enabling a user of the first digital audio workstation to: actuate a first single control of the first digital audio workstation to select whether the first digital audio workstation (i) monitors playback of the audio track and the time-based metadata received from the second digital audio workstation; or (ii) monitors playback of a corresponding audio track and time-based metadata pertaining to the audio track stored on the first digital audio workstation; and actuate a second single control of the first digital audio workstation to cause the first digital audio workstation to start recording both the audio track and the time-based metadata pertaining to the audio track received from the second digital audio workstation, wherein recording the received audio and time-based metadata overwrites a temporally corresponding portion of the audio track and time-based metadata stored on the first digital audio workstation. 5. The media editing system of claim 4 , wherein the time-based metadata stored on the first digital audio workstation and the time-based metadata received from the second digital audio workstation are panning metadata that define an apparent spatial location of a source of audio data of their corresponding audio tracks in a venue for playing back the audio tracks.
| 0.591314 |
9,910,887 | 1 | 6 |
1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query input comprising a character string having a first number of characters; accessing one or more verticals, each vertical being external to the client system and storing one or more objects of a particular object-type of a plurality of object types associated with the online social network, wherein: if the first number is less than or equal to a first threshold number, then accessing one or more first verticals, wherein each first vertical stores objects of a first object-type; and if the first number is greater than the first threshold number, then accessing the one or more first verticals and one or more second verticals, wherein each second vertical stores objects of a second object-type different than the first object-type; searching each accessed vertical to identify one or more objects associated with the vertical that substantially match the character string; and sending, to the client system of the first user, one or more references to one or more of the identified objects, respectively.
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1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query input comprising a character string having a first number of characters; accessing one or more verticals, each vertical being external to the client system and storing one or more objects of a particular object-type of a plurality of object types associated with the online social network, wherein: if the first number is less than or equal to a first threshold number, then accessing one or more first verticals, wherein each first vertical stores objects of a first object-type; and if the first number is greater than the first threshold number, then accessing the one or more first verticals and one or more second verticals, wherein each second vertical stores objects of a second object-type different than the first object-type; searching each accessed vertical to identify one or more objects associated with the vertical that substantially match the character string; and sending, to the client system of the first user, one or more references to one or more of the identified objects, respectively. 6. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network.
| 0.520518 |
8,965,752 | 1 | 5 |
1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings.
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1. A method comprising: detecting that a text string is subject to a line-wrap function that would divide the text string into a first plurality of substrings for presentation via a user interface; evaluating at least one of the first plurality of substrings against one or more prohibited text strings prohibited for presentation via the user interface; detecting, in response to the evaluating of the at least one of the first plurality of substrings against the one or more prohibited text strings, that the at least one of the first plurality of substrings is one or more prohibited text strings; and dividing the text string into a second plurality of text substrings that are different from the first plurality of text substrings, wherein the dividing the text string into the second plurality of text substrings is in response to the detecting that the at least one of the first plurality of substrings is one of the one or more prohibited text strings. 5. The method of claim 1 wherein the line-wrap function is configured to abbreviate the text string based on a limited space for presentation of the text string on the user interface.
| 0.770101 |
8,103,676 | 1 | 5 |
1. A method comprising: receiving a result set, the result set including a plurality of individual search results of a query, each of the individual search results including a first search result part and a second search result part that is different from the first search result part, wherein: the first search result part is exactly one of a uniform resource locator (URL), a hostname from the URL, a title, a snippet, a label, or a label histogram, and the second search result part is exactly one of a URL, a hostname from the URL, a title, a snippet, a label, or a label histogram; determining, by operation of one or more computing devices, an interpretation of the query from the individual search results, the interpretation being represented as a result classification of the result set as a whole, the result classification including a result category and a result score for the result set, wherein determining the result classification comprises: for each of the plurality of individual search results: determining, based on the first search result part: a first search result part category for determining the interpretation of the query; and a corresponding first search result part score; determining, based on the second search result part: a second search result part category for determining the interpretation of the query; and a corresponding second search result part score; and determining an individual result category and a corresponding individual result score based on the first search result part category, the second search result part category, and a weighted combination of the first search result part score and second search result part score; and determining the result category and the result score for the result set based on the individual result categories and corresponding individual result scores; identifying, by operation of one or more computing devices, a page clement that corresponds to the interpretation of the query, based on the interpretation of the query as represented by the result classification; and providing for display a page that includes the page element in addition to at least a portion of the result set.
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1. A method comprising: receiving a result set, the result set including a plurality of individual search results of a query, each of the individual search results including a first search result part and a second search result part that is different from the first search result part, wherein: the first search result part is exactly one of a uniform resource locator (URL), a hostname from the URL, a title, a snippet, a label, or a label histogram, and the second search result part is exactly one of a URL, a hostname from the URL, a title, a snippet, a label, or a label histogram; determining, by operation of one or more computing devices, an interpretation of the query from the individual search results, the interpretation being represented as a result classification of the result set as a whole, the result classification including a result category and a result score for the result set, wherein determining the result classification comprises: for each of the plurality of individual search results: determining, based on the first search result part: a first search result part category for determining the interpretation of the query; and a corresponding first search result part score; determining, based on the second search result part: a second search result part category for determining the interpretation of the query; and a corresponding second search result part score; and determining an individual result category and a corresponding individual result score based on the first search result part category, the second search result part category, and a weighted combination of the first search result part score and second search result part score; and determining the result category and the result score for the result set based on the individual result categories and corresponding individual result scores; identifying, by operation of one or more computing devices, a page clement that corresponds to the interpretation of the query, based on the interpretation of the query as represented by the result classification; and providing for display a page that includes the page element in addition to at least a portion of the result set. 5. The method of claim 1 , further comprising: determining a query classification based on the query, wherein the query classification includes a query category.
| 0.948065 |
7,650,286 | 5 | 6 |
5. The system of claim 1 , wherein each said at least one resume comprises a document in an electronic format.
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5. The system of claim 1 , wherein each said at least one resume comprises a document in an electronic format. 6. The system of claim 5 , wherein the electronic format includes a standard digital document format.
| 0.5 |
7,653,876 | 42 | 46 |
42. A system comprising: a processor; a machine-readable medium coupled with the processor; a network interface coupled with the processor; and a server software product tangibly stored on the machine-readable medium, the server software product comprising instructions that cause a programmable processor to perform operations for reversing a format of a reversible electronic document comprising two formatting states, the operations comprising: in a first document conversion for reversing an electronic document in a binary format into a markup language format, transforming the electronic document from the binary format into the markup language format by extracting a subset of information from the electronic document in the binary format according to predefined extraction parameters, inserting the subset of the information into portions of the electronic document in the markup language format, and inserting a reduced-information version of the electronic document in the binary format into a storage location of the electronic document in the markup language format such that the version of the electronic document in the binary format is retrievable upon reversal of the electronic document in the markup language format in a second document conversion, wherein the reduced-information version comprises data that is unconvertible to the markup language format; and in the second document conversion for reversing an electronic document in the markup language format into the binary format, transforming the electronic document from the markup language format into the binary format by extracting a first subset of information, from the electronic document in the markup language format, that is recognized in the binary format, extracting a second subset of information, from the electronic document in the markup language format, that is not recognized in the binary format, inserting the first subset of information, from the electronic document in the markup language format, into portions of the electronic document in the binary format, and placing the second subset of information from the electronic document in the markup language format into a storage location of the electronic document in the binary format such that the unrecognized information is retrievable upon reversal of the electronic document in the binary format in the first document conversion, wherein the second subset of information comprises data that is unconvertible to the binary format.
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42. A system comprising: a processor; a machine-readable medium coupled with the processor; a network interface coupled with the processor; and a server software product tangibly stored on the machine-readable medium, the server software product comprising instructions that cause a programmable processor to perform operations for reversing a format of a reversible electronic document comprising two formatting states, the operations comprising: in a first document conversion for reversing an electronic document in a binary format into a markup language format, transforming the electronic document from the binary format into the markup language format by extracting a subset of information from the electronic document in the binary format according to predefined extraction parameters, inserting the subset of the information into portions of the electronic document in the markup language format, and inserting a reduced-information version of the electronic document in the binary format into a storage location of the electronic document in the markup language format such that the version of the electronic document in the binary format is retrievable upon reversal of the electronic document in the markup language format in a second document conversion, wherein the reduced-information version comprises data that is unconvertible to the markup language format; and in the second document conversion for reversing an electronic document in the markup language format into the binary format, transforming the electronic document from the markup language format into the binary format by extracting a first subset of information, from the electronic document in the markup language format, that is recognized in the binary format, extracting a second subset of information, from the electronic document in the markup language format, that is not recognized in the binary format, inserting the first subset of information, from the electronic document in the markup language format, into portions of the electronic document in the binary format, and placing the second subset of information from the electronic document in the markup language format into a storage location of the electronic document in the binary format such that the unrecognized information is retrievable upon reversal of the electronic document in the binary format in the first document conversion, wherein the second subset of information comprises data that is unconvertible to the binary format. 46. The system of claim 42 , wherein the operations further comprise: sending the reversible electronic document over a network, and wherein operations for transforming the electronic document from the markup language format into the binary format further comprise: accessing the reduced-information version of the electronic document in the binary format in the storage location of the electronic document in the markup language format; and inserting the data that is unconvertible to the markup language format into the electronic document in the binary format.
| 0.5 |
7,814,147 | 19 | 21 |
19. A system comprising: a first computer; a web browser operably installed on the first computer; a web page accessible to the first computer via the web browser; a second computer different from the first computer; a web browser readable code component accessible to the second computer, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page.
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19. A system comprising: a first computer; a web browser operably installed on the first computer; a web page accessible to the first computer via the web browser; a second computer different from the first computer; a web browser readable code component accessible to the second computer, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. 21. The system as claimed in claim 19 wherein the content of the portion of the web page changed upon execution of the web browser readable code component includes an image.
| 0.601382 |
8,666,974 | 6 | 7 |
6. The method of claim 1 , wherein the search criteria are ordered so that a query is applied to each complying predefined search index in a specific order, a complying predefined search index being a predefined search index corresponding to one of the plurality of search criteria with which the query complies.
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6. The method of claim 1 , wherein the search criteria are ordered so that a query is applied to each complying predefined search index in a specific order, a complying predefined search index being a predefined search index corresponding to one of the plurality of search criteria with which the query complies. 7. The method of claim 6 , wherein the ordering is based on a number of items in each index, wherein a query is applied to an index with fewer items before an index with more items.
| 0.621339 |
6,134,532 | 50 | 56 |
50. A method of selecting advertisements in a computer environment, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer environment to a behavior vector, modifying a profile vector indicative of the user with the behavior vector; comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector; and selecting at least one electronic advertisement to communicate to the user computing device.
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50. A method of selecting advertisements in a computer environment, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer environment to a behavior vector, modifying a profile vector indicative of the user with the behavior vector; comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector; and selecting at least one electronic advertisement to communicate to the user computing device. 56. The method as defined in claim 50, wherein the converting includes identifying the behavior vector based upon a page identifier.
| 0.897036 |
9,530,400 | 16 | 20 |
16. The system of claim 11 , wherein the DNN is configured to classify the bitstream as belonging to a particular language.
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16. The system of claim 11 , wherein the DNN is configured to classify the bitstream as belonging to a particular language. 20. The system of claim 16 , further comprising: performing an action based upon the classification, wherein the action includes at least one of, automatically routing a call in a call center, non-intrusively obtaining statistics regarding language usage in a network, and performing speaker identification.
| 0.5 |
8,214,079 | 14 | 17 |
14. The method of claim 12 , wherein the actual measurement information layer for an object includes information of 2D/3D raw information that stores 2D or 3D representation data obtained by actually measuring an object, the topological information layer for an object includes information about accessible directions represented by a plurality of 3D contact points and 3D directional vectors, the spatio-temporal information layer for an object includes information about an object-space temporal dependency representing how a location of an object changes in a time domain, an object presence and spatiotemporal dependency representing influence to existence of the other objects when a specific object is in a specific temporal space, an object-object spatiotemporal dependency representing how an object is influenced by existence of the other object, an object-function spatiotemporal dependency representing how a function of an object changes according to a time and a space, and an object-physical feature spatiotemporal dependency representing what features of an object are changed according to a time and a space, and the reasoning information layer for an object includes information about an evidence structure formed as a graph representing relation between information of lower information layers as a probability.
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14. The method of claim 12 , wherein the actual measurement information layer for an object includes information of 2D/3D raw information that stores 2D or 3D representation data obtained by actually measuring an object, the topological information layer for an object includes information about accessible directions represented by a plurality of 3D contact points and 3D directional vectors, the spatio-temporal information layer for an object includes information about an object-space temporal dependency representing how a location of an object changes in a time domain, an object presence and spatiotemporal dependency representing influence to existence of the other objects when a specific object is in a specific temporal space, an object-object spatiotemporal dependency representing how an object is influenced by existence of the other object, an object-function spatiotemporal dependency representing how a function of an object changes according to a time and a space, and an object-physical feature spatiotemporal dependency representing what features of an object are changed according to a time and a space, and the reasoning information layer for an object includes information about an evidence structure formed as a graph representing relation between information of lower information layers as a probability. 17. The method of claim 14 , wherein the 2D or 3D representation data includes at least one of: a 2D raw image calculated through at least two of camera angles; depth data obtained from one of a laser scanner, a stereo camera and a structured light camera; mesh data generated from the depth data.
| 0.5 |
8,885,797 | 1 | 5 |
1. A method comprising: receiving, by a network device, a request to perform a transaction, the request being received from a device of a user, the transaction corresponding to a particular type of transaction; determining, by the network device, an authentication level, of a plurality of authentication levels, associated with the request, the authentication level being determined based on the transaction corresponding to the particular type of transaction; selecting, by the network device, an access telephone number, the access telephone number being selected, from a plurality of access numbers, based on the authentication level, each of the plurality of access numbers being associated with a different authentication level of the plurality of authentication levels; transferring, by the network device, the request and information regarding the authentication level to a different network device to perform speaker verification of the user for the transaction, the request being transferred using the selected access telephone number, the information regarding the authentication level being transferred after determining the authentication level, the different network device performing, based on the authentication level, the speaker verification of the user to generate a verification score associated with the transaction; receiving, by the network device, the verification score from the different network device; and performing, by the network device, the transaction based on the verification score.
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1. A method comprising: receiving, by a network device, a request to perform a transaction, the request being received from a device of a user, the transaction corresponding to a particular type of transaction; determining, by the network device, an authentication level, of a plurality of authentication levels, associated with the request, the authentication level being determined based on the transaction corresponding to the particular type of transaction; selecting, by the network device, an access telephone number, the access telephone number being selected, from a plurality of access numbers, based on the authentication level, each of the plurality of access numbers being associated with a different authentication level of the plurality of authentication levels; transferring, by the network device, the request and information regarding the authentication level to a different network device to perform speaker verification of the user for the transaction, the request being transferred using the selected access telephone number, the information regarding the authentication level being transferred after determining the authentication level, the different network device performing, based on the authentication level, the speaker verification of the user to generate a verification score associated with the transaction; receiving, by the network device, the verification score from the different network device; and performing, by the network device, the transaction based on the verification score. 5. The method of claim 1 , where performing the transaction includes: performing the transaction when the verification score exceeds a threshold value associated with at least one of the transaction or the authentication level.
| 0.724515 |
9,304,614 | 6 | 7 |
6. The method recited in claim 1 , the method further comprising: in response to receiving the message from the client machine, generating a new custom action activation mechanism for the first responsive post, the new custom action activation mechanism having a visual presentation that reflects the performed custom action; and transmitting, from the server to the client machine, custom action activation mechanism update data for displaying the new custom action activation mechanism in the user interface component at the client machine.
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6. The method recited in claim 1 , the method further comprising: in response to receiving the message from the client machine, generating a new custom action activation mechanism for the first responsive post, the new custom action activation mechanism having a visual presentation that reflects the performed custom action; and transmitting, from the server to the client machine, custom action activation mechanism update data for displaying the new custom action activation mechanism in the user interface component at the client machine. 7. The method recited in claim 6 , wherein the custom action activation mechanism update data is transmitted to the client machine and the new custom action activation mechanism is displayed at the client machine without reloading the user interface component.
| 0.5 |
9,201,969 | 15 | 16 |
15. A computer-readable memory comprising computer-executable instructions for execution by a computer machine to identify a document that when executed, cause the computer machine to: receive a query including at least one legal concept; compare said at least one legal concept of said query to each document centric profile of a set of document centric concept profiles contained in a computerized database, wherein each document centric concept profile comprises a plurality of normalized legal concepts and, for each normalized legal concept, at least one reference value; surface a set of documents associated with one or more document centric concept profiles having a normalized legal concept that matches said at least one legal concept of said query; and rank said set of documents by their associated reference value scores.
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15. A computer-readable memory comprising computer-executable instructions for execution by a computer machine to identify a document that when executed, cause the computer machine to: receive a query including at least one legal concept; compare said at least one legal concept of said query to each document centric profile of a set of document centric concept profiles contained in a computerized database, wherein each document centric concept profile comprises a plurality of normalized legal concepts and, for each normalized legal concept, at least one reference value; surface a set of documents associated with one or more document centric concept profiles having a normalized legal concept that matches said at least one legal concept of said query; and rank said set of documents by their associated reference value scores. 16. A computer-readable memory as claimed in claim 15 wherein said computer machine is chosen from the group consisting of: a mobile device, desktop, and a laptop.
| 0.5 |
9,754,279 | 1 | 4 |
1. A computerized method comprising: sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein sampling the streams of electronic data comprises real-time sampling, sensing, and detection of user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients; analyzing the user-generated content data streams in the sample data to obtain targeting data for use in targeting electronic advertisements to electronic device users, wherein the targeting data comprises data relating to topics of interest to the electronic device users; based at least in part on the analyzing of the user-generated content data streams in the sample data, increasing one or more sampling frequencies or rates during at least one period based on a determination that targeting data is more likely to be concentrated during the at least one period than during other periods, wherein the increasing of the one or more sampling frequencies or rates is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns can include time-based or frequency-based patterns associated with the user-generated content data streams; based at least in part on the targeting data obtained, selecting electronic advertisements for serving to targeted electronic device users; and serving the selected electronic advertisements to the targeted electronic device users, the serving including causing an advertisement serving system to initiate or modify an automated advertising campaign that includes the selected electronic advertisements.
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1. A computerized method comprising: sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein sampling the streams of electronic data comprises real-time sampling, sensing, and detection of user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients; analyzing the user-generated content data streams in the sample data to obtain targeting data for use in targeting electronic advertisements to electronic device users, wherein the targeting data comprises data relating to topics of interest to the electronic device users; based at least in part on the analyzing of the user-generated content data streams in the sample data, increasing one or more sampling frequencies or rates during at least one period based on a determination that targeting data is more likely to be concentrated during the at least one period than during other periods, wherein the increasing of the one or more sampling frequencies or rates is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns can include time-based or frequency-based patterns associated with the user-generated content data streams; based at least in part on the targeting data obtained, selecting electronic advertisements for serving to targeted electronic device users; and serving the selected electronic advertisements to the targeted electronic device users, the serving including causing an advertisement serving system to initiate or modify an automated advertising campaign that includes the selected electronic advertisements. 4. The method of claim 1 , wherein the sampling comprises monitoring one or more streams of electronic data during transmission of the data but before reception by intended recipients, wherein the one or more streams can come from one geographic location or from multiple geographic locations.
| 0.530449 |
6,031,989 | 10 | 11 |
10. A method for displaying a main electronic document and one or more other nested electronic documents included therein, the main electronic document readable by a computer software application, the electronic documents having content for display, the method comprising the following steps: parsing the main electronic document with the computer software application; determining from the parsing whether the main electronic document contains a reference tag to a nested electronic document; and if the main electronic document contains a reference tag to a nested electronic document: determining from the reference tag a display layout and one or more display techniques for the displaying the nested electronic document; and displaying the content of the nested electronic document in an overlapping manner with the content of the main electronic document.
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10. A method for displaying a main electronic document and one or more other nested electronic documents included therein, the main electronic document readable by a computer software application, the electronic documents having content for display, the method comprising the following steps: parsing the main electronic document with the computer software application; determining from the parsing whether the main electronic document contains a reference tag to a nested electronic document; and if the main electronic document contains a reference tag to a nested electronic document: determining from the reference tag a display layout and one or more display techniques for the displaying the nested electronic document; and displaying the content of the nested electronic document in an overlapping manner with the content of the main electronic document. 11. A computer-readable storage medium having stored therein instructions for causing a computer to perform the method of claim 10.
| 0.884683 |
9,569,487 | 3 | 5 |
3. The method of claim 1 , wherein generating, in response to determining the value of the attribute for the entity, instructions for presentation of the set of search results in a user interface that includes, for the particular search result, an emphasis of the value of the attribute comprises generating instructions for displaying at least the value of the attribute in a display box within the set of search results.
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3. The method of claim 1 , wherein generating, in response to determining the value of the attribute for the entity, instructions for presentation of the set of search results in a user interface that includes, for the particular search result, an emphasis of the value of the attribute comprises generating instructions for displaying at least the value of the attribute in a display box within the set of search results. 5. The method of claim 3 , wherein the instructions comprise instructions for presenting the display box positioned below one of the search results in the set of search results.
| 0.536649 |
8,219,572 | 14 | 17 |
14. A system comprising: a plurality of processors configured to execute a plurality of enterprise applications including first and second applications, each application having a relational data store storing searchable data and non-searchable data; a plurality of communication points, each communication point associated with one of the applications and configured to provide a standardized interface to the internal structure of data stored in the data store of the associated application; and a search modeler in communication with each of the communication points, the search modeler comprising a processor configured to: create searchable data definitions that identify searchable data in each data store; the searchable data definitions comprising a first searchable data definition for the first application; add metadata describing the searchable data associated with the first and second applications to the first searchable data definition, wherein the first searchable data definition identifies the searchable data associated with the first and second applications and the locations of the searchable data associated with the first and second applications; add an identification of one or more database objects including searchable data associated with the first searchable data definition to the first searchable definition and adding searchable attributes of the one or more database objects to the first searchable definition; validate the first searchable data definition by performing a partial search of the associated data to verify that relationships identified or defined in the first searchable data definition are consistent with relationships stored within the first application; and based on validation of the first searchable data definition, use the searchable data definitions to index the searchable data stored by the first and second applications.
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14. A system comprising: a plurality of processors configured to execute a plurality of enterprise applications including first and second applications, each application having a relational data store storing searchable data and non-searchable data; a plurality of communication points, each communication point associated with one of the applications and configured to provide a standardized interface to the internal structure of data stored in the data store of the associated application; and a search modeler in communication with each of the communication points, the search modeler comprising a processor configured to: create searchable data definitions that identify searchable data in each data store; the searchable data definitions comprising a first searchable data definition for the first application; add metadata describing the searchable data associated with the first and second applications to the first searchable data definition, wherein the first searchable data definition identifies the searchable data associated with the first and second applications and the locations of the searchable data associated with the first and second applications; add an identification of one or more database objects including searchable data associated with the first searchable data definition to the first searchable definition and adding searchable attributes of the one or more database objects to the first searchable definition; validate the first searchable data definition by performing a partial search of the associated data to verify that relationships identified or defined in the first searchable data definition are consistent with relationships stored within the first application; and based on validation of the first searchable data definition, use the searchable data definitions to index the searchable data stored by the first and second applications. 17. The system of claim 14 , wherein the processor of the search modeler is further configured to perform a diagnostic verification of the metadata stored in the searchable data definitions.
| 0.5 |
9,996,527 | 2 | 4 |
2. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a document analysis device for performing a statistical analysis of documents with respect to a facet, wherein the computer readable program causes the computing device to: accept, by an acceptance module executing within the document analysis device, a natural language sentence; extract, by an extraction module executing within the document analysis device, a first facet from the natural language sentence; perform, by a statistical analysis module executing within the document analysis device, a first statistical analysis of a set of documents with respect to the first facet; determine, by the statistical analysis module, a value of the first facet based on a result of the first statistical analysis responsive to information being extracted from the natural language sentence, the information requesting for a second statistical analysis; perform, by the statistical analysis module, the second statistical analysis of the set of documents using the value of the first facet; and present, by a user interface executed by the computing device, a second facet determined based on a result of the second statistical analysis.
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2. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a document analysis device for performing a statistical analysis of documents with respect to a facet, wherein the computer readable program causes the computing device to: accept, by an acceptance module executing within the document analysis device, a natural language sentence; extract, by an extraction module executing within the document analysis device, a first facet from the natural language sentence; perform, by a statistical analysis module executing within the document analysis device, a first statistical analysis of a set of documents with respect to the first facet; determine, by the statistical analysis module, a value of the first facet based on a result of the first statistical analysis responsive to information being extracted from the natural language sentence, the information requesting for a second statistical analysis; perform, by the statistical analysis module, the second statistical analysis of the set of documents using the value of the first facet; and present, by a user interface executed by the computing device, a second facet determined based on a result of the second statistical analysis. 4. The computer program product of claim 2 , wherein extracting the first facet from the natural language sentence comprises extracting a type of the first statistical analysis from the natural language sentence and wherein performing the first statistical analysis comprises performing the first statistical analysis of the type extracted from the natural language sentence.
| 0.5 |
7,545,982 | 1 | 13 |
1. A method of assessing fraud in a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one of the information fields of the document, comparing handwriting in the information field to at least one handwriting profile representation from at least two information fields of at least one other document, wherein at least one handwriting profile representation has been stored in a computer system; assessing fraud in the document using at least one comparison, wherein evidence of fraud comprises a failure of at least a portion of the handwriting in at least one of the information fields of the document to approximately match at least one handwriting profile representation.
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1. A method of assessing fraud in a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one of the information fields of the document, comparing handwriting in the information field to at least one handwriting profile representation from at least two information fields of at least one other document, wherein at least one handwriting profile representation has been stored in a computer system; assessing fraud in the document using at least one comparison, wherein evidence of fraud comprises a failure of at least a portion of the handwriting in at least one of the information fields of the document to approximately match at least one handwriting profile representation. 13. The method of claim 1 , wherein the handwriting from at least one information field comprises an image.
| 0.923789 |
9,916,303 | 1 | 2 |
1. A method for providing an answer to an input question containing at least one time-sensitive word or at least one time-sensitive phrase using natural language processing (NLP), the method comprising: creating and maintaining an online T-Word Dictionary, wherein creating and maintaining the online T-Word Dictionary comprises: determining a relationship between a plurality of T-Words and a plurality of corresponding values, wherein the plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; mapping the plurality of T-Words to the plurality of corresponding values based on the determined relationship; and storing the mapped plurality of T-Words to the plurality of corresponding values in the online T-Word Dictionary; receiving the input question, wherein the input question is entered by a user via a graphical user interface associated with a first computer; performing natural language processing (NLP) analysis on the input question to extract a required value phrase; forming at least one mathematical equation based on the extracted required value phrase, wherein forming the at least one mathematical equation comprises: identifying the at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein a value associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase varies according to a particular point in time, and wherein the identifying comprises communicating online with a second computer to access the online T-Word Dictionary; and resolving the identified at least one time-sensitive word or the at least one time sensitive phrase contained in the received input question, wherein the resolving comprises communicating online with the second computer to access the online T-Word Dictionary and recursively mapping a plurality of variables associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase to at least one formula contained in the T-Word Dictionary; determining the answer to the input question in natural language based on the solved at least one mathematical equation; and narrating the answer to the input question in natural language based on the solved at least one mathematical equation.
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1. A method for providing an answer to an input question containing at least one time-sensitive word or at least one time-sensitive phrase using natural language processing (NLP), the method comprising: creating and maintaining an online T-Word Dictionary, wherein creating and maintaining the online T-Word Dictionary comprises: determining a relationship between a plurality of T-Words and a plurality of corresponding values, wherein the plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; mapping the plurality of T-Words to the plurality of corresponding values based on the determined relationship; and storing the mapped plurality of T-Words to the plurality of corresponding values in the online T-Word Dictionary; receiving the input question, wherein the input question is entered by a user via a graphical user interface associated with a first computer; performing natural language processing (NLP) analysis on the input question to extract a required value phrase; forming at least one mathematical equation based on the extracted required value phrase, wherein forming the at least one mathematical equation comprises: identifying the at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein a value associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase varies according to a particular point in time, and wherein the identifying comprises communicating online with a second computer to access the online T-Word Dictionary; and resolving the identified at least one time-sensitive word or the at least one time sensitive phrase contained in the received input question, wherein the resolving comprises communicating online with the second computer to access the online T-Word Dictionary and recursively mapping a plurality of variables associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase to at least one formula contained in the T-Word Dictionary; determining the answer to the input question in natural language based on the solved at least one mathematical equation; and narrating the answer to the input question in natural language based on the solved at least one mathematical equation. 2. The method of claim 1 further comprising: determining at least one relevant variable based on the extracted required value phrase; and determining at least one current value for the at least one determined relevant variable.
| 0.65184 |
8,335,802 | 12 | 14 |
12. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods; wherein the invoking of the producer, converter, and distributor methods is triggered by at least one of the following: a schedule, a user input, and an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the schedule, the user input, or the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the schedule, the user input, or the event meets a predefined criterion.
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12. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods; wherein the invoking of the producer, converter, and distributor methods is triggered by at least one of the following: a schedule, a user input, and an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the schedule, the user input, or the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the schedule, the user input, or the event meets a predefined criterion. 14. The method of claim 12 , wherein the invoking is triggered by the event, and wherein the event is a data change in at least one of the one or more data repositories.
| 0.743939 |
9,870,134 | 11 | 19 |
11. The method of claim 1 , wherein the object represents one of an actor, a dancer, a marching band participant, or a combination thereof and wherein the text is one of a play, a television show, a movie, a musical, musical score, or a combination thereof, and the method further comprising: associating a sequential series of identification numbers with a sequential series of lines of the text; determining a set of one or more characters associated with at least a subset of the sequential series of lines of the text; and displaying at least one character in the set of one or more characters with at least the subset sequential series of numbers to enable a user to identify one or characters that may be played by one person.
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11. The method of claim 1 , wherein the object represents one of an actor, a dancer, a marching band participant, or a combination thereof and wherein the text is one of a play, a television show, a movie, a musical, musical score, or a combination thereof, and the method further comprising: associating a sequential series of identification numbers with a sequential series of lines of the text; determining a set of one or more characters associated with at least a subset of the sequential series of lines of the text; and displaying at least one character in the set of one or more characters with at least the subset sequential series of numbers to enable a user to identify one or characters that may be played by one person. 19. The information processing system of claim 11 , wherein the updating the display of the second region includes displaying the digital representation of the object along with a path indicator between a plurality of x-positions and y-positions for the digital representation of the object to move in association with the one or more lines of the text.
| 0.606027 |
8,745,044 | 1 | 4 |
1. A method of generating a composite abstract for a document, the method comprising: receiving a query that includes one or more search query terms; generating a first version of a contextual abstract of the document, at least in part, by selecting, based on the one or more search query terms, first portions of the document for inclusion within the contextual abstract of the document; generating a static abstract of the document, at least in part, by selecting, without regard to the one or more search query terms, second portions of the document for inclusion within the static abstract of the document; generating a second version of the contextual abstract by removing one or more text strings from the first version of the contextual abstract; wherein removing the one or more text strings includes removing a particular text string from the first version of the contextual abstract based, at least in part, on similarities between the contextual abstract and the static abstract; combining text strings from the second version of the contextual abstract with text strings from the static abstract to form the composite abstract for the document; responding to the query with search results that include the composite abstract.
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1. A method of generating a composite abstract for a document, the method comprising: receiving a query that includes one or more search query terms; generating a first version of a contextual abstract of the document, at least in part, by selecting, based on the one or more search query terms, first portions of the document for inclusion within the contextual abstract of the document; generating a static abstract of the document, at least in part, by selecting, without regard to the one or more search query terms, second portions of the document for inclusion within the static abstract of the document; generating a second version of the contextual abstract by removing one or more text strings from the first version of the contextual abstract; wherein removing the one or more text strings includes removing a particular text string from the first version of the contextual abstract based, at least in part, on similarities between the contextual abstract and the static abstract; combining text strings from the second version of the contextual abstract with text strings from the static abstract to form the composite abstract for the document; responding to the query with search results that include the composite abstract. 4. The method of claim 1 , wherein each text string in the contextual abstract satisfies specified criteria.
| 0.906574 |
8,387,025 | 13 | 17 |
13. A system for dynamically integrating business logic rules with an application program operating on one or more processors for executing the business logic rules, the system comprising: a database that includes fields and subfields that correspond to parameters that are associated with the business logic rules; and a dynamic business logic rule integrator module operating on the one or more processors configured to (i) provide to a user a mechanism to produce an expression of the business logic rule, (ii) evaluate the expression to directly produce an executable routine by associating with the expression one or more functions and defined operators that correspond to one or more pre-coded subroutines and associating values with the one or more functions by calling the functions and parameters in the expression with associated values passed in and (iii) provide the routine to the application program.
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13. A system for dynamically integrating business logic rules with an application program operating on one or more processors for executing the business logic rules, the system comprising: a database that includes fields and subfields that correspond to parameters that are associated with the business logic rules; and a dynamic business logic rule integrator module operating on the one or more processors configured to (i) provide to a user a mechanism to produce an expression of the business logic rule, (ii) evaluate the expression to directly produce an executable routine by associating with the expression one or more functions and defined operators that correspond to one or more pre-coded subroutines and associating values with the one or more functions by calling the functions and parameters in the expression with associated values passed in and (iii) provide the routine to the application program. 17. The system of claim 13 wherein the database is dynamically configurable with new fields and sub-fields to correspond to changes in the business logic rules.
| 0.698113 |
8,862,604 | 12 | 16 |
12. One or more storage media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: obtaining exposed log files from a log system; computing Bayesian posterior probabilities for relevancy between the log files and a search request; computing expected values of the relevancy between the log files and the search request; filtering the log files based at least in part on the expected values or variances of the relevancy between the log files and the search request to filter out a log file having a respective expected value or variance less than or equal to a predefined threshold; after filtering the log files, storing the search request and identifiers of the filtered log files as keys and the expected values of the relevancy between the filtered log files and the search request as respective values into a search data structure; in response to receiving a search request submitted by a user, finding expected values of relevancy between the search request submitted by the user and log files that are relevant to the submitted search request from the search data structure; and ordering the relevant log files according to a descending order of the found expected values.
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12. One or more storage media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: obtaining exposed log files from a log system; computing Bayesian posterior probabilities for relevancy between the log files and a search request; computing expected values of the relevancy between the log files and the search request; filtering the log files based at least in part on the expected values or variances of the relevancy between the log files and the search request to filter out a log file having a respective expected value or variance less than or equal to a predefined threshold; after filtering the log files, storing the search request and identifiers of the filtered log files as keys and the expected values of the relevancy between the filtered log files and the search request as respective values into a search data structure; in response to receiving a search request submitted by a user, finding expected values of relevancy between the search request submitted by the user and log files that are relevant to the submitted search request from the search data structure; and ordering the relevant log files according to a descending order of the found expected values. 16. The one or more storage media as recited in claim 12 , wherein computing the Bayesian posterior probabilities comprises: based on whether the user has clicked a log file, whether the user has seen the log file, a degree of relevancy between the log file and the search request of the user, whether the user has browsed subsequent log files and clicking conditions of previous log files, and/or if a prior distribution follows a uniform distribution over [0, 1], computing a joint posterior distribution for relevancy between the log file and the request after the user clicks the log file.
| 0.5 |
7,660,705 | 23 | 33 |
23. A computer-implemented method of forecasting future observations in a sequence of time series data, comprising: storing, in a memory communicatively coupled to a processor, computer-executable instructions for performing the method of making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; executing the instructions on the processor, wherein the instructions result in data mining within the large amounts of data; according to the instructions being executed: performing a greedy search to grow a model corresponding to the set of time series data represented by a decision graph having at least one non-trivial linear regression at leaves of the decision graph, the greedy search algorithm being performed iteratively relative to respective leaves of the model for a subset of potential regressors, wherein the potential regressors are arranged in the subset in a descending order of their correlation to a predicted variable; computing a Bayesian score for the model and, wherein the performance of the greedy search further comprising splitting a leaf node of the model into a pair of additional leaves, each of the additional leaves including at least one linear regression on at least one variable of a set of potential regressors and the performance of the greedy search further comprising merging at least two leaf nodes of the decision graph provided that the merging improves the Bayesian score for the model and the decision graph is a regression decision graph model comprising a plurality of leaves and at least one non-leaf node, the at least one non-leaf node being associated with a Boolean function for one of a plurality of variables having a split value, at least one non-root node of the regression decision graph model having more than one parent in the regression decision graph model, at least two leaves of the regression decision graph model being associated with at least one linear regression on at least one of the variables so as to provide a piecewise linear regression decision graph model; repeating the performance of the greedy search and computation of the Bayesian score so long as the model score improves; if the model score does not improve, terminating the modification and computation, and providing a model having a model structure corresponding to a decision graph having a fixed number of leaves that include at least one non-trivial linear regression; modifying a regressor variable at one of the leaves of the decision graph to provide a submodel; computing a Bayesian score for the submodel; repeating the modifying and computation of the Bayesian score for the submodel so long as the score of the submodel improves; if the score of the submodel does not improve relative to a previous score of the submodel, providing the submodel with the highest model score as the regression model that best models future observations of the time series data; and employing the best regression model to generate the future observations of the time series data.
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23. A computer-implemented method of forecasting future observations in a sequence of time series data, comprising: storing, in a memory communicatively coupled to a processor, computer-executable instructions for performing the method of making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; executing the instructions on the processor, wherein the instructions result in data mining within the large amounts of data; according to the instructions being executed: performing a greedy search to grow a model corresponding to the set of time series data represented by a decision graph having at least one non-trivial linear regression at leaves of the decision graph, the greedy search algorithm being performed iteratively relative to respective leaves of the model for a subset of potential regressors, wherein the potential regressors are arranged in the subset in a descending order of their correlation to a predicted variable; computing a Bayesian score for the model and, wherein the performance of the greedy search further comprising splitting a leaf node of the model into a pair of additional leaves, each of the additional leaves including at least one linear regression on at least one variable of a set of potential regressors and the performance of the greedy search further comprising merging at least two leaf nodes of the decision graph provided that the merging improves the Bayesian score for the model and the decision graph is a regression decision graph model comprising a plurality of leaves and at least one non-leaf node, the at least one non-leaf node being associated with a Boolean function for one of a plurality of variables having a split value, at least one non-root node of the regression decision graph model having more than one parent in the regression decision graph model, at least two leaves of the regression decision graph model being associated with at least one linear regression on at least one of the variables so as to provide a piecewise linear regression decision graph model; repeating the performance of the greedy search and computation of the Bayesian score so long as the model score improves; if the model score does not improve, terminating the modification and computation, and providing a model having a model structure corresponding to a decision graph having a fixed number of leaves that include at least one non-trivial linear regression; modifying a regressor variable at one of the leaves of the decision graph to provide a submodel; computing a Bayesian score for the submodel; repeating the modifying and computation of the Bayesian score for the submodel so long as the score of the submodel improves; if the score of the submodel does not improve relative to a previous score of the submodel, providing the submodel with the highest model score as the regression model that best models future observations of the time series data; and employing the best regression model to generate the future observations of the time series data. 33. The method of claim 23 , the decision graph is an autoregressive tree model comprising a plurality of leaves and at least one non-leaf node, the at least one non-leaf node being associated with a Boolean function for one of a plurality of variables having a split value, at least two of the leaves being associated with at least one linear regression on at least one of the variables so as to provide a piecewise linear autoregressive tree model to facilitate forecasting relative to the time series data.
| 0.5 |
9,632,989 | 1 | 5 |
1. A method, comprising: storing, in a memory device, a hybrid markup language document; determining, by a hardware processor coupled to the memory device, a partition boundary in the hybrid markup language document; generating, by the hardware processor, a copy of the hybrid markup language document; discarding, by the hardware processor, content in the copy of the hybrid markup language document that precedes the partition boundary; and generating, by the hardware processor, an output markup language document from remaining content occurring after the partition boundary in the copy of the hybrid markup language document.
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1. A method, comprising: storing, in a memory device, a hybrid markup language document; determining, by a hardware processor coupled to the memory device, a partition boundary in the hybrid markup language document; generating, by the hardware processor, a copy of the hybrid markup language document; discarding, by the hardware processor, content in the copy of the hybrid markup language document that precedes the partition boundary; and generating, by the hardware processor, an output markup language document from remaining content occurring after the partition boundary in the copy of the hybrid markup language document. 5. The method of claim 1 , further comprising tagging the partition boundary.
| 0.69685 |
9,594,744 | 11 | 13 |
11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a lexicon model that maps phones to spoken text, wherein spoken text includes only words that are spelled out; obtaining a language model that assigns probabilities to written text, wherein written text includes (i) words that are spelled out and (ii) sequences of characters that include abbreviations that are not spelled out words, acronyms that are not spelled out words, and numeric symbols; obtaining grammar rules for expanding written text into spoken text; generating, using the grammar rules, expansions of written text that includes sequences of characters that include abbreviations that are not spelled out words, acronyms that are not spelled out words, and numeric symbols into spoken text that includes only words that are spelled out, the expansions including mappings of multiple different items of written text to a particular item of the spoken text; generating a transducer that includes the expansions, where the transducer maps the written text to the spoken text, the transducer mapping the multiple different items of written text to the particular item of the spoken text; constructing a decoding network for transcribing utterances into written text, by composing the lexicon model, the inverse of the transducer, and the language model; and generating, by an automated speech recognizer, a transcription of a subsequently received utterance into written text using the decoding network.
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11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a lexicon model that maps phones to spoken text, wherein spoken text includes only words that are spelled out; obtaining a language model that assigns probabilities to written text, wherein written text includes (i) words that are spelled out and (ii) sequences of characters that include abbreviations that are not spelled out words, acronyms that are not spelled out words, and numeric symbols; obtaining grammar rules for expanding written text into spoken text; generating, using the grammar rules, expansions of written text that includes sequences of characters that include abbreviations that are not spelled out words, acronyms that are not spelled out words, and numeric symbols into spoken text that includes only words that are spelled out, the expansions including mappings of multiple different items of written text to a particular item of the spoken text; generating a transducer that includes the expansions, where the transducer maps the written text to the spoken text, the transducer mapping the multiple different items of written text to the particular item of the spoken text; constructing a decoding network for transcribing utterances into written text, by composing the lexicon model, the inverse of the transducer, and the language model; and generating, by an automated speech recognizer, a transcription of a subsequently received utterance into written text using the decoding network. 13. The system of claim 11 , wherein the spoken text comprises a textual representation of a spoken language.
| 0.859173 |
9,358,685 | 1 | 6 |
1. A method for controlling actions of robots, the method comprising: identifying, at a device that includes a processor, a first context-variable value for a context variable detected by a robot at a first sensory-detection time; accessing, at the device, a policy comprising one or more parameters configured to map the context variable to a robot action variable; determining that a first robot action characterized by a first value of the robot action variable was performed at an action time in response to detection of the first context-variable value, the first robot action being in accordance with application of the policy; determining that a user input was received at an input time corresponding to the action time, wherein user input data derived from the user input at least partly defines a corrective command that specifies a corrective robot action for physical performance, the user input being indicative of at least partial dissatisfaction with the first robot action; modifying the policy based on the corrective command and the first context-variable value; and causing the modified policy to be used to: determine a second robot action characterized by a second value of the robot action variable based on a second context-variable value for the context variable detected at a second sensory-detection time; and initiate performance of the second robot action in accordance with the second value of the robot action variable.
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1. A method for controlling actions of robots, the method comprising: identifying, at a device that includes a processor, a first context-variable value for a context variable detected by a robot at a first sensory-detection time; accessing, at the device, a policy comprising one or more parameters configured to map the context variable to a robot action variable; determining that a first robot action characterized by a first value of the robot action variable was performed at an action time in response to detection of the first context-variable value, the first robot action being in accordance with application of the policy; determining that a user input was received at an input time corresponding to the action time, wherein user input data derived from the user input at least partly defines a corrective command that specifies a corrective robot action for physical performance, the user input being indicative of at least partial dissatisfaction with the first robot action; modifying the policy based on the corrective command and the first context-variable value; and causing the modified policy to be used to: determine a second robot action characterized by a second value of the robot action variable based on a second context-variable value for the context variable detected at a second sensory-detection time; and initiate performance of the second robot action in accordance with the second value of the robot action variable. 6. The method of claim 1 , wherein the corrective command is indicative of a magnitude of action.
| 0.928466 |
9,894,193 | 1 | 10 |
1. A method for controlling an electronic device being executed by a processor of the electronic device, the method comprising: establishing a central control tree for the electronic device; obtaining voice data; recognizing the voice data to obtain recognized voice data; and controlling an operation to the electronic device according to the central control tree based upon the recognized voice data; wherein the central control tree is established by: establishing a single control tree for each of a plurality of applications of the electronic device, and obtaining a plurality of single control trees, wherein each node of each of the plurality of single control trees corresponds to a serial number, wherein root nodes of the plurality of single control trees correspond to a same serial number, and other nodes of the plurality of single control trees correspond to different serial numbers; and obtaining the central control tree by merging the plurality of single control trees based upon the serial number corresponding to each node of each of the plurality of single control trees, wherein nodes corresponding to the same serial number are merged to be one node, and the other nodes corresponding to different serial numbers are correspondingly added to the central control tree; wherein the method further comprises: displaying the central control tree on a display screen of the electronic device in response to user's input; deleting a single control tree corresponding to one of the plurality of applications from the central control tree in response to a first signal; and adding a single control tree corresponding to a new application to the central control tree in response to a second signal.
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1. A method for controlling an electronic device being executed by a processor of the electronic device, the method comprising: establishing a central control tree for the electronic device; obtaining voice data; recognizing the voice data to obtain recognized voice data; and controlling an operation to the electronic device according to the central control tree based upon the recognized voice data; wherein the central control tree is established by: establishing a single control tree for each of a plurality of applications of the electronic device, and obtaining a plurality of single control trees, wherein each node of each of the plurality of single control trees corresponds to a serial number, wherein root nodes of the plurality of single control trees correspond to a same serial number, and other nodes of the plurality of single control trees correspond to different serial numbers; and obtaining the central control tree by merging the plurality of single control trees based upon the serial number corresponding to each node of each of the plurality of single control trees, wherein nodes corresponding to the same serial number are merged to be one node, and the other nodes corresponding to different serial numbers are correspondingly added to the central control tree; wherein the method further comprises: displaying the central control tree on a display screen of the electronic device in response to user's input; deleting a single control tree corresponding to one of the plurality of applications from the central control tree in response to a first signal; and adding a single control tree corresponding to a new application to the central control tree in response to a second signal. 10. The method according to claim 1 , further comprising: when the single control tree corresponding to the one of the plurality of applications is deleted from the central control tree, correspondingly adjust the serial number of each node of other applications of the plurality of applications on the central control tree.
| 0.865894 |
8,725,567 | 1 | 6 |
1. A computer-implemented system that facilitates presentation of targeted advertisements to an individual, comprising: a sensor component of a retail establishment that collects sensor information associated with a specific individual proximate to a presentation system; a customer component that analyzes the sensor information and generates a profile about the specific individual, the customer component further comprising: an inference component that makes an inference about the specific individual based on some or all of the sensor information collected by the sensor component of the retail establishment as part of generating the profile; and a storage component that stores historical data of the specific individual and transaction data associated with transactions conducted by the specific individual; and an advertisement component that facilitates dynamic presentation of a targeted advertisement to the specific individual as a function of the profile.
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1. A computer-implemented system that facilitates presentation of targeted advertisements to an individual, comprising: a sensor component of a retail establishment that collects sensor information associated with a specific individual proximate to a presentation system; a customer component that analyzes the sensor information and generates a profile about the specific individual, the customer component further comprising: an inference component that makes an inference about the specific individual based on some or all of the sensor information collected by the sensor component of the retail establishment as part of generating the profile; and a storage component that stores historical data of the specific individual and transaction data associated with transactions conducted by the specific individual; and an advertisement component that facilitates dynamic presentation of a targeted advertisement to the specific individual as a function of the profile. 6. The system of claim 1 , further comprising a presentation system that receives the advertisement from the advertisement component and presents the advertisement for perception by the individual.
| 0.649466 |
8,489,628 | 37 | 42 |
37. A system for selecting documents from a document collection in response to a query, the system comprising: one or more memory devices configured store executable instructions; and one or more processors configured to execute the stored instructions to cause the system to: receive a query; identify an incomplete phrase in the query, wherein phrases predicted by the incomplete phrase in the document collection include only phrase extensions of the incomplete phrase; identify a phrase extension of the incomplete phrase, wherein the phrase extension of the incomplete phrase is a sequence of words that begins with the incomplete phrase but that is longer than the incomplete phrase, and wherein the incomplete phrase predicts the phrase extension based an actual co-occurrence rate of the phrase extension and the incomplete phrase in the document collection exceeding an expected co-occurrence rate of the phrase extension and the incomplete phrase in the document collection; and suggest the phrase extension to the user to use in the query.
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37. A system for selecting documents from a document collection in response to a query, the system comprising: one or more memory devices configured store executable instructions; and one or more processors configured to execute the stored instructions to cause the system to: receive a query; identify an incomplete phrase in the query, wherein phrases predicted by the incomplete phrase in the document collection include only phrase extensions of the incomplete phrase; identify a phrase extension of the incomplete phrase, wherein the phrase extension of the incomplete phrase is a sequence of words that begins with the incomplete phrase but that is longer than the incomplete phrase, and wherein the incomplete phrase predicts the phrase extension based an actual co-occurrence rate of the phrase extension and the incomplete phrase in the document collection exceeding an expected co-occurrence rate of the phrase extension and the incomplete phrase in the document collection; and suggest the phrase extension to the user to use in the query. 42. The system of claim 37 , wherein the one or more processors are further configured to execute the stored instructions to cause the system to select documents from the document collection, wherein the selected documents contain the phrase extension.
| 0.76 |
9,098,567 | 1 | 7 |
1. A method that uses a processor to determine a document rank, comprising: calculating, using the processor, a document rank score of a second document based on a first term relationship score of a first document and a first contribution score, the first contribution score being determined based on a common keyword between the first document and the second document; changing the first term relationship score to a second term relationship score; and updating the document rank score of the second document based on the second term relationship score, wherein the first document is linked by a link to the second document, wherein the first term relationship score is determined based on content of the first document and the link, and wherein updating the document rank score comprises determining whether each of a plurality of contribution scores is greater than a predetermined threshold value, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value.
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1. A method that uses a processor to determine a document rank, comprising: calculating, using the processor, a document rank score of a second document based on a first term relationship score of a first document and a first contribution score, the first contribution score being determined based on a common keyword between the first document and the second document; changing the first term relationship score to a second term relationship score; and updating the document rank score of the second document based on the second term relationship score, wherein the first document is linked by a link to the second document, wherein the first term relationship score is determined based on content of the first document and the link, and wherein updating the document rank score comprises determining whether each of a plurality of contribution scores is greater than a predetermined threshold value, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value. 7. The method of claim 1 , wherein the first term relationship score and the second term relationship score are calculated based on a relationship between the content of the first document and the common keyword.
| 0.854993 |
9,575,965 | 1 | 3 |
1. A method comprising: identifying a first computer-generated translation from a first text in a first natural language to a second text in a second natural language; identifying a user-provided subjective translation quality score for the first computer-generated translation; determining, by a processor, a first set of semantic features of the first text, and a second set of semantic features of the second text; determining, by the processor, a first value that is based on one or more errors of plural form usage of the first text; determining, by the processor, a second value that is based on one or more errors of plural form usage of the second text; training, by the processor, a classifier with a set of input-output mappings, wherein a first input-output mapping of the set of input-output mappings comprises an input that is based on the first value, the second value, the first set of semantic features, and the second set of semantic features, and wherein the first input-output mapping comprises an output that is based on the first user-provided subjective translation quality score; identifying a second computer-generated translation from a third text in the first natural language to a fourth text in the second natural language; determining, by the processor, a third set of semantic features of the third text, and a fourth set of semantic features of the fourth text; determining, by the processor, a third value that is based on one or more errors of plural form usage of the third text; determining, by the processor, a fourth value that is based on one or more errors of plural form usage of the fourth text; providing, to the classifier, one or more inputs that are based on the third value, the fourth value, the third set of semantic features, and the fourth set of semantic features; running, by the processor, the classifier with the one or more inputs to obtain a computer-generated subjective translation quality score for the second computer-generated translation; and providing to a client device, by the processor, an assessment of the second computer-generated translation based on the computer-generated subjective translation quality score.
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1. A method comprising: identifying a first computer-generated translation from a first text in a first natural language to a second text in a second natural language; identifying a user-provided subjective translation quality score for the first computer-generated translation; determining, by a processor, a first set of semantic features of the first text, and a second set of semantic features of the second text; determining, by the processor, a first value that is based on one or more errors of plural form usage of the first text; determining, by the processor, a second value that is based on one or more errors of plural form usage of the second text; training, by the processor, a classifier with a set of input-output mappings, wherein a first input-output mapping of the set of input-output mappings comprises an input that is based on the first value, the second value, the first set of semantic features, and the second set of semantic features, and wherein the first input-output mapping comprises an output that is based on the first user-provided subjective translation quality score; identifying a second computer-generated translation from a third text in the first natural language to a fourth text in the second natural language; determining, by the processor, a third set of semantic features of the third text, and a fourth set of semantic features of the fourth text; determining, by the processor, a third value that is based on one or more errors of plural form usage of the third text; determining, by the processor, a fourth value that is based on one or more errors of plural form usage of the fourth text; providing, to the classifier, one or more inputs that are based on the third value, the fourth value, the third set of semantic features, and the fourth set of semantic features; running, by the processor, the classifier with the one or more inputs to obtain a computer-generated subjective translation quality score for the second computer-generated translation; and providing to a client device, by the processor, an assessment of the second computer-generated translation based on the computer-generated subjective translation quality score. 3. The method of claim 1 wherein the first input-output mapping comprises a fifth value that is based on one or more punctuation errors of the second text.
| 0.515625 |
6,055,333 | 1 | 4 |
1. A method, comprising the steps of: displaying a graphical user interface having a plurality of handwriting entry areas to receive on-line handwritten input; selecting, responsive to receiving on-line handwritten input in a handwriting entry area, a set of at least one dictionary from a plurality of dictionaries to provide selected recognition data at least some of which has a weighting value associated therewith; processing information representing the on-line handwritten input received at the handwriting entry area of the graphical user interface with the selected recognition data to identify candidate recognition information; and displaying the candidate recognition information.
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1. A method, comprising the steps of: displaying a graphical user interface having a plurality of handwriting entry areas to receive on-line handwritten input; selecting, responsive to receiving on-line handwritten input in a handwriting entry area, a set of at least one dictionary from a plurality of dictionaries to provide selected recognition data at least some of which has a weighting value associated therewith; processing information representing the on-line handwritten input received at the handwriting entry area of the graphical user interface with the selected recognition data to identify candidate recognition information; and displaying the candidate recognition information. 4. The method of claim 1, which includes the step of cross-referencing the candidate recognition information to other information and displaying the other information in a display area associated with the other information.
| 0.686798 |
8,892,443 | 1 | 3 |
1. A method comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query.
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1. A method comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query. 3. The method of claim 1 wherein the present location of the portable device is determined using one of a global positioning system, triangulation, and automatic number identification.
| 0.834234 |
8,171,412 | 1 | 6 |
1. A visual presentation system for synchronizing a display of a set of presentation with a speech input of a speaker, the system comprising: a speech recognition system for processing the speech input of the speaker during a visual presentation, wherein the processing of the speech input of the speaker includes converting the speech input into a spoken information data set; an association system for processing the spoken information data set to determine a display order of portions of the set of presentation data, wherein relevant portions of the set of presentation data are displayed in an order based upon the speech input of the speaker, wherein the processing of the spoken information data set includes: preprocessing the set of presentation data to exclude a predetermined list of terms from consideration in a presentation data match determination; determining a context of the speech input by analyzing speech patterns in the speech input over a predetermined time interval; and determining a set of matches of the context with the relevant portions of the set of presentation data; and a visual coordination system for coordinating the display of the relevant portions of the set of presentation data based on the set of matches determined by the association system, wherein the coordinating of the display of the relevant portions includes adjusting the display order of the relevant portions to synchronize the visual presentation with the speech input, and wherein the visual coordination system includes a user selection system for allowing a user to select which of the relevant portions to display from among the set of matches during the visual presentation.
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1. A visual presentation system for synchronizing a display of a set of presentation with a speech input of a speaker, the system comprising: a speech recognition system for processing the speech input of the speaker during a visual presentation, wherein the processing of the speech input of the speaker includes converting the speech input into a spoken information data set; an association system for processing the spoken information data set to determine a display order of portions of the set of presentation data, wherein relevant portions of the set of presentation data are displayed in an order based upon the speech input of the speaker, wherein the processing of the spoken information data set includes: preprocessing the set of presentation data to exclude a predetermined list of terms from consideration in a presentation data match determination; determining a context of the speech input by analyzing speech patterns in the speech input over a predetermined time interval; and determining a set of matches of the context with the relevant portions of the set of presentation data; and a visual coordination system for coordinating the display of the relevant portions of the set of presentation data based on the set of matches determined by the association system, wherein the coordinating of the display of the relevant portions includes adjusting the display order of the relevant portions to synchronize the visual presentation with the speech input, and wherein the visual coordination system includes a user selection system for allowing a user to select which of the relevant portions to display from among the set of matches during the visual presentation. 6. The visual presentation system of claim 1 , wherein the visual coordination system further includes a system for marking data items and saving an output of the presentation.
| 0.794872 |
8,645,390 | 14 | 23 |
14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query.
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14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query. 23. The system of claim 14 , wherein: the set of search results has a preliminary search result order; and ordering the portion of the search results in accordance with the identified predicted performance function includes: comparing predicted click through rates of a plurality search results in multiple different search result orders; selecting a respective search result order that increases a predicted click through rate of a plurality of the results over the preliminary search result order; and ordering the portion of the search results in the respective search result order.
| 0.5 |
9,361,293 | 1 | 2 |
1. A method, in a data processing system comprising a processor and a memory, for generating a lexical resource for linguistic analysis, the method comprising: receiving, by the data processing system, a document data structure comprising a renaming directive in natural language textual content of the document data structure, wherein the renaming directive is a statement that specifies a correspondence between a full expression and a moniker that is stand-in text for the full expression; applying, by the data processing system, filter logic to the document data structure to identify the renaming directive within the natural language textual content of the document data structure; analyzing, by the data processing system, the renaming directive to identify a relationship between semantic concepts represented by the renaming directive that are to be used to update a lexical resource based on the renaming directive; updating, by the data processing system, the lexical resource based on results of analyzing the renaming directive; and outputting, by the data processing system, the updated lexical resource to a linguistic analysis system, wherein the linguistic analysis system performs linguistic analysis of a portion of textual content based on the updated lexical resource.
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1. A method, in a data processing system comprising a processor and a memory, for generating a lexical resource for linguistic analysis, the method comprising: receiving, by the data processing system, a document data structure comprising a renaming directive in natural language textual content of the document data structure, wherein the renaming directive is a statement that specifies a correspondence between a full expression and a moniker that is stand-in text for the full expression; applying, by the data processing system, filter logic to the document data structure to identify the renaming directive within the natural language textual content of the document data structure; analyzing, by the data processing system, the renaming directive to identify a relationship between semantic concepts represented by the renaming directive that are to be used to update a lexical resource based on the renaming directive; updating, by the data processing system, the lexical resource based on results of analyzing the renaming directive; and outputting, by the data processing system, the updated lexical resource to a linguistic analysis system, wherein the linguistic analysis system performs linguistic analysis of a portion of textual content based on the updated lexical resource. 2. The method of claim 1 , wherein updating the lexical resource comprises generating a new lexical resource based on the results of analyzing the renaming directive.
| 0.738994 |
8,209,318 | 1 | 11 |
1. A product search method in a product search system, the method comprising: maintaining and storing a database in a memory, the database including a plurality of product identifiers and a plurality of product categories associated with the respective product identifiers; maintaining a plurality of search logics associated with categorical types of products, at least one predetermined search logic being assigned to each categorical type of products, each of said plurality of search logics including a set of search steps wherein at least two categorical types of products are associated with at least two different search logics and said at least two different search logics include different sets of search steps; receiving a search request including an original query for search of a product from a user terminal; determining whether a product identifier corresponding to the original query exists; extracting a category query associated with the original query and selecting at least one said product category included in the database using the category query, when the product identifier corresponding to the original query does not exist; selecting at least one product category including the product identifier as a category corresponding to the received original query, when the product identifier corresponding to the original query exists; identifying a categorical type of product associated with the selected product category; determining a search logic corresponding to the categorical type of product from among the plurality of search logics; in response to the search request, performing a search of the database for products by applying said determined search logic corresponding to the identified categorical type of product such that different search logics are applied depending on the categorical type of product; and outputting a search result including the searched products, wherein, when the identified categorical type of product is a first categorical type of product, the predetermined search logic corresponding to the first categorical type of product performs search steps in a predetermined sequence until a number of the searched products included in the search result exceeds a predetermined value, said search steps being selected from the group comprising: a search step of generating a first query by removing a space, a special character or both from the original query and of searching the database for products using the first query; a search step of generating second queries by separating the original query into a plurality of words according to the space, each of the plurality of words being the second queries, and of searching the database for products by using one or more words among the second queries, each of said one or more words being a combination of at least two selected from the group consisting of English alphabetic characters, numerals, special characters; a search step of generating third queries by separating the original query into a plurality of words according to the space, each of the third queries having an initial letter of an English alphabetic character and at least one numeral, and of searching the database for products by using the third queries; and a search step of generating fourth queries by separating the original query into a plurality of tokens according to the space based on analyzing the morpheme of the original query, each of the tokens comprising either a group of only alphabetic characters or a group of only numerals, and of searching the database for products by using the fourth queries.
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1. A product search method in a product search system, the method comprising: maintaining and storing a database in a memory, the database including a plurality of product identifiers and a plurality of product categories associated with the respective product identifiers; maintaining a plurality of search logics associated with categorical types of products, at least one predetermined search logic being assigned to each categorical type of products, each of said plurality of search logics including a set of search steps wherein at least two categorical types of products are associated with at least two different search logics and said at least two different search logics include different sets of search steps; receiving a search request including an original query for search of a product from a user terminal; determining whether a product identifier corresponding to the original query exists; extracting a category query associated with the original query and selecting at least one said product category included in the database using the category query, when the product identifier corresponding to the original query does not exist; selecting at least one product category including the product identifier as a category corresponding to the received original query, when the product identifier corresponding to the original query exists; identifying a categorical type of product associated with the selected product category; determining a search logic corresponding to the categorical type of product from among the plurality of search logics; in response to the search request, performing a search of the database for products by applying said determined search logic corresponding to the identified categorical type of product such that different search logics are applied depending on the categorical type of product; and outputting a search result including the searched products, wherein, when the identified categorical type of product is a first categorical type of product, the predetermined search logic corresponding to the first categorical type of product performs search steps in a predetermined sequence until a number of the searched products included in the search result exceeds a predetermined value, said search steps being selected from the group comprising: a search step of generating a first query by removing a space, a special character or both from the original query and of searching the database for products using the first query; a search step of generating second queries by separating the original query into a plurality of words according to the space, each of the plurality of words being the second queries, and of searching the database for products by using one or more words among the second queries, each of said one or more words being a combination of at least two selected from the group consisting of English alphabetic characters, numerals, special characters; a search step of generating third queries by separating the original query into a plurality of words according to the space, each of the third queries having an initial letter of an English alphabetic character and at least one numeral, and of searching the database for products by using the third queries; and a search step of generating fourth queries by separating the original query into a plurality of tokens according to the space based on analyzing the morpheme of the original query, each of the tokens comprising either a group of only alphabetic characters or a group of only numerals, and of searching the database for products by using the fourth queries. 11. The product search method of claim 1 , wherein, when the identified categorical type of product is cosmetics, powdered milk, diapers, or other general categorical type of product, said group further comprising a search step of generating a fifth query by analyzing a morpheme of the original query.
| 0.750413 |
7,818,658 | 14 | 24 |
14. A system for editing a multimedia presentation that includes plurality of scenes, each scene including a sequence of visual displays, the multimedia presentation being defined by a presentation script such as a presentation script including instructions that include identification of a plurality of content assets, identification of one or more visual displays in which the identified content assets are to be included, one or more modifications of the content assets to be performed prior to inclusion of the identified content assets in the one or more visual displays, instructions for positioning the modified content assets in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display, the system comprising: a processor configured to implement a user interface for editing a presentation script defining a multimedia presentation, the user interface comprising: a timeline strip for indicating a display order for individual scenes in a presentation; and a compose window coupled to the timeline strip for editing individual scenes in a presentation and individual content assets within the individual scenes, resulting in corresponding edits being made to the presentation script by the processor.
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14. A system for editing a multimedia presentation that includes plurality of scenes, each scene including a sequence of visual displays, the multimedia presentation being defined by a presentation script such as a presentation script including instructions that include identification of a plurality of content assets, identification of one or more visual displays in which the identified content assets are to be included, one or more modifications of the content assets to be performed prior to inclusion of the identified content assets in the one or more visual displays, instructions for positioning the modified content assets in the one or more visual displays, and layering instructions for determining, for a portion of the visual display that includes plurality of modified content assets, the forward and backward relation of the plurality of modified assets to each other in the visual display, the system comprising: a processor configured to implement a user interface for editing a presentation script defining a multimedia presentation, the user interface comprising: a timeline strip for indicating a display order for individual scenes in a presentation; and a compose window coupled to the timeline strip for editing individual scenes in a presentation and individual content assets within the individual scenes, resulting in corresponding edits being made to the presentation script by the processor. 24. The system of claim 14 , the compose window further including a frame out slider for adjusting the frame out cue of a presentation asset.
| 0.896324 |
8,732,151 | 19 | 20 |
19. One or more computer storage media storing computer-executable instructions for performing a method for identifying query rewriting replacement terms, the method comprising: receiving a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, wherein the user click log data including data for one or more search query sessions, and wherein the second string of each related string pair is identified by analyzing the user click log data including at least one dwell time associated with one or more search results and a number of links clicked; for one or more of the related string pairs, providing the string pair as inputs to a statistical machine translation model that: identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms, wherein when a related string pair is identified as being highly related in the received list of pairs, additional instances of the string pair are input into the statistical machine translation model to create a weighting effect; and upon determining that the calculated probability of relatedness of a pair of corresponding terms exceeds a threshold: characterizing the second term as a query term replacement for the first term, and incorporating the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database.
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19. One or more computer storage media storing computer-executable instructions for performing a method for identifying query rewriting replacement terms, the method comprising: receiving a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, wherein the user click log data including data for one or more search query sessions, and wherein the second string of each related string pair is identified by analyzing the user click log data including at least one dwell time associated with one or more search results and a number of links clicked; for one or more of the related string pairs, providing the string pair as inputs to a statistical machine translation model that: identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms, wherein when a related string pair is identified as being highly related in the received list of pairs, additional instances of the string pair are input into the statistical machine translation model to create a weighting effect; and upon determining that the calculated probability of relatedness of a pair of corresponding terms exceeds a threshold: characterizing the second term as a query term replacement for the first term, and incorporating the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database. 20. The media of claim 19 , wherein the statistical machine translation model is modified to identify groups of corresponding terms such that a probability of relatedness is calculated between a first group of two or more terms and a second group of two or more terms.
| 0.5 |
7,646,317 | 3 | 4 |
3. The decoding method of claim 1 , wherein interpreting the input sequence is determined by a linguistic model.
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3. The decoding method of claim 1 , wherein interpreting the input sequence is determined by a linguistic model. 4. The decoding method of claim 3 , wherein the linguistic model utilizes linguistic score calculation that applied on the encoding sequence combinations.
| 0.5 |
9,223,868 | 9 | 11 |
9. The system of claim 8 , wherein: the first profile characterizes one or more respective interactions with electronic documents in each of the first result sets of electronic documents responsive to search queries of a first category, the search queries of the first category are selected from among a plurality of queries including the search queries of the first category and other search queries, the second profile characterizes one or more respective interactions with electronic documents in each of the second result sets of electronic documents responsive to search queries of the first category, and the indication indicates that the first scoring algorithm is better than the second scoring algorithm for scoring electronic documents responsive to search queries of the first category.
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9. The system of claim 8 , wherein: the first profile characterizes one or more respective interactions with electronic documents in each of the first result sets of electronic documents responsive to search queries of a first category, the search queries of the first category are selected from among a plurality of queries including the search queries of the first category and other search queries, the second profile characterizes one or more respective interactions with electronic documents in each of the second result sets of electronic documents responsive to search queries of the first category, and the indication indicates that the first scoring algorithm is better than the second scoring algorithm for scoring electronic documents responsive to search queries of the first category. 11. The system of claim 9 , wherein the first category is queries having syntax.
| 0.921105 |
4,597,055 | 27 | 28 |
27. A method according to claim 26, wherein the step of inserting all untranslatable words from the first sentence into the translated sentence is further included.
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27. A method according to claim 26, wherein the step of inserting all untranslatable words from the first sentence into the translated sentence is further included. 28. A method according to claim 27, wherein the selecting step is further comprised of the steps of determining whether any sentence stored in the first memory means has a measure of equivalency to the first sentence, identifying any differences that exist between the first sentence and a sentence determined to have a measure of equivalency to it, and searching the first memory means for each word in the first sentence not found in a sentence determined to have a measure of equivalency to the first sentence.
| 0.5 |
9,430,563 | 1 | 7 |
1. An apparatus comprising: an electronic data processing device configured to: perform a modeling method including: constructing a set of word embedding transforms by operations including generating a term-document matrix whose elements represent occurrence frequencies for text words in documents of a set of documents and include inverse document frequency (IDF) scaling; applying the set of word embedding transforms to transform text words of a set of documents into K-dimensional word vectors in order to generate sets or sequences of word vectors representing the documents of the set of documents where K is an integer greater than or equal to two; and learning a probabilistic topic model comprising a mixture model including M mixture components representing M topics using the sets or sequences of word vectors representing the documents of the set of documents wherein the learned probabilistic topic model operates to assign probabilities for the topics of the probabilistic topic model to an input set or sequence of K-dimensional embedded word vectors; and perform a document processing method including: applying the set of word embedding transforms to transform text words of an input document into K-dimensional word vectors in order to generate a set or sequence of word vectors representing the input document; and applying the learned mixture model to the set or sequence of word vectors representing the input document in order to generate one of (1) a vector or histogram of topic probabilities representing the input document or (2) one or more Fisher vectors representing the input document.
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1. An apparatus comprising: an electronic data processing device configured to: perform a modeling method including: constructing a set of word embedding transforms by operations including generating a term-document matrix whose elements represent occurrence frequencies for text words in documents of a set of documents and include inverse document frequency (IDF) scaling; applying the set of word embedding transforms to transform text words of a set of documents into K-dimensional word vectors in order to generate sets or sequences of word vectors representing the documents of the set of documents where K is an integer greater than or equal to two; and learning a probabilistic topic model comprising a mixture model including M mixture components representing M topics using the sets or sequences of word vectors representing the documents of the set of documents wherein the learned probabilistic topic model operates to assign probabilities for the topics of the probabilistic topic model to an input set or sequence of K-dimensional embedded word vectors; and perform a document processing method including: applying the set of word embedding transforms to transform text words of an input document into K-dimensional word vectors in order to generate a set or sequence of word vectors representing the input document; and applying the learned mixture model to the set or sequence of word vectors representing the input document in order to generate one of (1) a vector or histogram of topic probabilities representing the input document or (2) one or more Fisher vectors representing the input document. 7. The apparatus of claim 1 , wherein the modeling method further includes extending the set of word embedding transforms by identifying one or more related words of a new word and generating a K-dimensional word vector for the new word by aggregating the K-dimensional word vectors generated for the identified one or more related words by the set of word embedding transforms.
| 0.5 |
9,077,933 | 22 | 31 |
22. A system, comprising: a memory that stores instructions; a processor that executes the instructions from memory to perform operations, the operations comprising: tabulating for each program in a program guide an occurrence count corresponding to each term of a plurality of terms, the occurrence count indicating a number of times the respective term is associated with a corresponding program; computing, for each program in the program guide, a relevance ranking score by multiplying an average of occurrence counts associated with a corresponding program by how many times the corresponding program is listed in the program guide; selecting a list of programs from the program guide based on a respective relevance ranking score of each program; and outputting the list of programs.
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22. A system, comprising: a memory that stores instructions; a processor that executes the instructions from memory to perform operations, the operations comprising: tabulating for each program in a program guide an occurrence count corresponding to each term of a plurality of terms, the occurrence count indicating a number of times the respective term is associated with a corresponding program; computing, for each program in the program guide, a relevance ranking score by multiplying an average of occurrence counts associated with a corresponding program by how many times the corresponding program is listed in the program guide; selecting a list of programs from the program guide based on a respective relevance ranking score of each program; and outputting the list of programs. 31. The system of claim 22 , wherein the operations further comprise ignoring terms of the plurality of terms that have a limited value.
| 0.704348 |
9,002,700 | 1 | 12 |
1. A method of grammar checking, the method comprising: receiving text through a communications network at a first computing device-based grammar checking facility from a second computing device of a user, wherein the grammar checking facility is adapted to automatically detect a plurality of grammatical errors in the text through software algorithms, wherein the second computing device has input limitations including at least one of a reduced size keyboard and a reduced size display relative to a standard keyboard and display; providing, from the grammar checking facility through the communications network to each of a plurality of human proofreader computing devices of a plurality of human proofreaders in a crowd-source population at least one excerpt of the text containing an identified possible grammatical error as a result of the automated detection of the grammar checking facility so that a human augmented grammar correction is collectively performed by the plurality of human proofreaders in parallel, and wherein each of the plurality of human proofreader computing devices is separate from the first computing device and the second computing device; receiving and incorporating results of the plurality of human proofreaders to contribute to an at least one corrected version of the received text; and sending the at least one corrected version back to the second computing device.
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1. A method of grammar checking, the method comprising: receiving text through a communications network at a first computing device-based grammar checking facility from a second computing device of a user, wherein the grammar checking facility is adapted to automatically detect a plurality of grammatical errors in the text through software algorithms, wherein the second computing device has input limitations including at least one of a reduced size keyboard and a reduced size display relative to a standard keyboard and display; providing, from the grammar checking facility through the communications network to each of a plurality of human proofreader computing devices of a plurality of human proofreaders in a crowd-source population at least one excerpt of the text containing an identified possible grammatical error as a result of the automated detection of the grammar checking facility so that a human augmented grammar correction is collectively performed by the plurality of human proofreaders in parallel, and wherein each of the plurality of human proofreader computing devices is separate from the first computing device and the second computing device; receiving and incorporating results of the plurality of human proofreaders to contribute to an at least one corrected version of the received text; and sending the at least one corrected version back to the second computing device. 12. The method of claim 1 , wherein the received text was generated as at least one of an email message or a text message on a mobile device.
| 0.821519 |
8,706,477 | 1 | 8 |
1. A system comprising: a lexical correspondence graphical user interface configured to co-display to a user a first dependency tree of a first multi-word expression in a first natural language and a second dependency tree of a corresponding second multi-word expression in a second natural language, and in response to co-displaying the first and second dependency trees to the user, receive a user input indicating a presence and a type of a lexical correspondence between a first node of the first dependency tree and a second node of the second dependency tree, the user input comprising an indicator of a user selection from a plurality of lexical correspondence type choices presented to the user of the type of the lexical correspondence between the first node of the first dependency tree and the second node of the second dependency tree; and a lexical correspondence code generator connected to the lexical correspondence graphical user interface and configured to generate grammar abstract language (GAL) computer-readable correspondence code representing the lexical correspondence in response to receiving an indicator of the user input, the grammar abstract language correspondence code designating a set of correspondences between nodes of a grammar abstract language dependency tree representing the first multi-word expression and corresponding nodes of a grammar abstract language dependency tree representing the second multi-word expression, wherein a node of the grammar abstract language representation of the first multi-word expression includes an attribute-value tree characterizing morphologically the node; wherein at least one node of the first dependency tree is a procedural node representing a procedure, wherein performing the procedure comprises executing code to perform an action selected from turning numerals into numeric values, manipulating a picture embedded in text, and manipulating a sound embedded in text associated with the node.
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1. A system comprising: a lexical correspondence graphical user interface configured to co-display to a user a first dependency tree of a first multi-word expression in a first natural language and a second dependency tree of a corresponding second multi-word expression in a second natural language, and in response to co-displaying the first and second dependency trees to the user, receive a user input indicating a presence and a type of a lexical correspondence between a first node of the first dependency tree and a second node of the second dependency tree, the user input comprising an indicator of a user selection from a plurality of lexical correspondence type choices presented to the user of the type of the lexical correspondence between the first node of the first dependency tree and the second node of the second dependency tree; and a lexical correspondence code generator connected to the lexical correspondence graphical user interface and configured to generate grammar abstract language (GAL) computer-readable correspondence code representing the lexical correspondence in response to receiving an indicator of the user input, the grammar abstract language correspondence code designating a set of correspondences between nodes of a grammar abstract language dependency tree representing the first multi-word expression and corresponding nodes of a grammar abstract language dependency tree representing the second multi-word expression, wherein a node of the grammar abstract language representation of the first multi-word expression includes an attribute-value tree characterizing morphologically the node; wherein at least one node of the first dependency tree is a procedural node representing a procedure, wherein performing the procedure comprises executing code to perform an action selected from turning numerals into numeric values, manipulating a picture embedded in text, and manipulating a sound embedded in text associated with the node. 8. The system of claim 1 , further comprising a lexical element manager connected to the lexical correspondence graphical user interface, and configured to receive the first multiword expression and the second multi-word expression in natural language form and to generate structured computer-readable grammar abstract language lexicon entries for the first multiword expression and the second multiword expression.
| 0.5 |
9,684,448 | 1 | 2 |
1. A user device for visually impaired users, the user device comprising: a touch screen configured to: receive touch input from a user; and present a touch-input interface for Braille input comprising a plurality of input regions defined by and separated by input region boundaries, each input region abutting at adjacent input region boundaries and being separated by a centrally-located portal region that is elongated and abuts at least a portion of each input region, wherein the plurality of input regions are configured for Braille input and arranged in rows and columns, and wherein the centrally-located portal region provides an area for dragging a finger as a buffer for selection of the plurality of input regions, such that the finger maintains contact with the touch screen and passes through the portal region while inputting a Braille character by selecting two or more of the plurality of input regions, and wherein contact is maintained until lifting the finger off the touch screen to trigger output of the Braille character based on the selected two or more of the plurality of input regions.
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1. A user device for visually impaired users, the user device comprising: a touch screen configured to: receive touch input from a user; and present a touch-input interface for Braille input comprising a plurality of input regions defined by and separated by input region boundaries, each input region abutting at adjacent input region boundaries and being separated by a centrally-located portal region that is elongated and abuts at least a portion of each input region, wherein the plurality of input regions are configured for Braille input and arranged in rows and columns, and wherein the centrally-located portal region provides an area for dragging a finger as a buffer for selection of the plurality of input regions, such that the finger maintains contact with the touch screen and passes through the portal region while inputting a Braille character by selecting two or more of the plurality of input regions, and wherein contact is maintained until lifting the finger off the touch screen to trigger output of the Braille character based on the selected two or more of the plurality of input regions. 2. The user device of claim 1 , wherein said plurality of input regions are configured for six-dot Braille input, and wherein said six input regions comprise six rectangular input regions in a 2×3 arrangement of rows and columns.
| 0.693029 |
8,229,921 | 1 | 20 |
1. A computer implemented method for indexing and retrieving documents in a database, comprising the steps of: constructing a set of particles and a simultaneously optimized particle-based language model using training documents, and in which a perplexity of the particle-based language model is at least ten times lower than the perplexity of a word-based language model constructed from the same training documents, wherein the set of particles applies expectation maximization to an objective function, and where the objective function considers any combination of: a size of the set of particles; errors in representing all documents in a document training set and a query training set; a retrieval accuracy of using the set of particles; an entropy of a statistical models that represent the set of particles; and a particle-level language model derived from the documents and the queries in the training sets; converting each document in a collection of documents to a document particle graph, the document particle graph including particles selected from the set of the particles; extracting, for each document, a set of document keys from the corresponding particle graph; storing the document keys for each document in an index to a database storing the collection of documents; converting a query to a query particle graph including a set of query particles, the query graph including particles selected from the set of the particles; extracting a set of query keys from the query particle graph; retrieving relevant documents from the database according to the query keys and the document keys stored in the index; and outputting the relevant documents to a user.
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1. A computer implemented method for indexing and retrieving documents in a database, comprising the steps of: constructing a set of particles and a simultaneously optimized particle-based language model using training documents, and in which a perplexity of the particle-based language model is at least ten times lower than the perplexity of a word-based language model constructed from the same training documents, wherein the set of particles applies expectation maximization to an objective function, and where the objective function considers any combination of: a size of the set of particles; errors in representing all documents in a document training set and a query training set; a retrieval accuracy of using the set of particles; an entropy of a statistical models that represent the set of particles; and a particle-level language model derived from the documents and the queries in the training sets; converting each document in a collection of documents to a document particle graph, the document particle graph including particles selected from the set of the particles; extracting, for each document, a set of document keys from the corresponding particle graph; storing the document keys for each document in an index to a database storing the collection of documents; converting a query to a query particle graph including a set of query particles, the query graph including particles selected from the set of the particles; extracting a set of query keys from the query particle graph; retrieving relevant documents from the database according to the query keys and the document keys stored in the index; and outputting the relevant documents to a user. 20. The method of claim 1 , further comprising: rank ordering the relevant documents.
| 0.822176 |
9,195,716 | 4 | 5 |
4. The apparatus of claim 1 , the ranking application further operative to: raise a sub-ranking of a ranked individual search result when there is a match between a first character set character in the search string and a first character set character in the individual search result; lower the sub-ranking of a ranked individual search result when there is not a match between a first character set character in the search string and a first character set character in the individual search result; and leave the sub-ranking of a ranked individual search result unchanged when there is no first character set character in the search string.
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4. The apparatus of claim 1 , the ranking application further operative to: raise a sub-ranking of a ranked individual search result when there is a match between a first character set character in the search string and a first character set character in the individual search result; lower the sub-ranking of a ranked individual search result when there is not a match between a first character set character in the search string and a first character set character in the individual search result; and leave the sub-ranking of a ranked individual search result unchanged when there is no first character set character in the search string. 5. The apparatus of claim 4 , the ranking application further operative to: determine how many first character set characters in the search string and first character set characters in the ranked individual search result match; assign a highest sub-ranking to the ranked individual search result when all the first character set characters in the search string match with first character set characters in the individual search result; and assign a raised sub-ranking but not a highest sub-ranking to the ranked individual search result when some of the first character set characters in the search string match with first character set characters in the individual search result.
| 0.5 |
9,710,699 | 1 | 5 |
1. An image processing appliance comprising a family of image processing functions instantiated on high thru put processor hardwares that accomplishes recognition of individuals of interest from analysis of images taken under real world lighting conditions, wherein the analysis functions accomplish a) extraction of indices of recognition from real work imagery sets containing the images of the individuals of interest, b) the construction of three dimensional morphable models of the individuals of interest based on data sets containing images of the individuals of interest, c) extraction of lighting conditions from the real world image data set containing images of the individual to be recognized, d) imposition of the extracted lighting conditions upon the three dimensional images of candidate individuals, and e) declaration of individual identify based on a high degree of correlation between the real world data set and the simulated data set extracted from the morphed three dimensional models with the lighting conditions of the real image rendered onto the three dimensional models morphed into the positional conditions of the individual to be recognized from the real world data set.
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1. An image processing appliance comprising a family of image processing functions instantiated on high thru put processor hardwares that accomplishes recognition of individuals of interest from analysis of images taken under real world lighting conditions, wherein the analysis functions accomplish a) extraction of indices of recognition from real work imagery sets containing the images of the individuals of interest, b) the construction of three dimensional morphable models of the individuals of interest based on data sets containing images of the individuals of interest, c) extraction of lighting conditions from the real world image data set containing images of the individual to be recognized, d) imposition of the extracted lighting conditions upon the three dimensional images of candidate individuals, and e) declaration of individual identify based on a high degree of correlation between the real world data set and the simulated data set extracted from the morphed three dimensional models with the lighting conditions of the real image rendered onto the three dimensional models morphed into the positional conditions of the individual to be recognized from the real world data set. 5. The declaration of recognition of claim 1 performed by computing the degree of correlation between the real world image data set and the data set produced by transforming the three morphed model of candidate individuals with correct pose and lighting and selecting the individual in the data base with sufficiently high or highest degree of correlation between the real worked data and the simulated data.
| 0.5 |
7,664,740 | 8 | 10 |
8. A computer-implemented method comprising: executing instructions stored on a computer-readable media, wherein the instructions when executed on a processor comprise; presenting a user interface in which a user can view email messages; responsive to the user selecting an email message, displaying one or more keywords found in the email message, wherein the act of displaying comprises: removing one or more of email tag lines or email header lines from consideration as a keyword; cross-indexing one or more keywords from a selected email message with other email messages that pertain to a contact from which the selected email message was received, to ascertain the use of a multiplier with a weight associated with the cross-indexed one or more keywords; re-calculating weights for detected keywords that re-occur over a pre-determined temporal domain such that the weights of the detected keywords found in last N configurable emails are modified or lowered; using the one or more keywords to conduct a search that provides search results; displaying the search results for the user; and displaying supplemental information that is related to at least one displayed keyword, wherein the acts of displaying selected keywords and supplemental information comprise displaying the selected keywords and the supplemental information.
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8. A computer-implemented method comprising: executing instructions stored on a computer-readable media, wherein the instructions when executed on a processor comprise; presenting a user interface in which a user can view email messages; responsive to the user selecting an email message, displaying one or more keywords found in the email message, wherein the act of displaying comprises: removing one or more of email tag lines or email header lines from consideration as a keyword; cross-indexing one or more keywords from a selected email message with other email messages that pertain to a contact from which the selected email message was received, to ascertain the use of a multiplier with a weight associated with the cross-indexed one or more keywords; re-calculating weights for detected keywords that re-occur over a pre-determined temporal domain such that the weights of the detected keywords found in last N configurable emails are modified or lowered; using the one or more keywords to conduct a search that provides search results; displaying the search results for the user; and displaying supplemental information that is related to at least one displayed keyword, wherein the acts of displaying selected keywords and supplemental information comprise displaying the selected keywords and the supplemental information. 10. The method of claim 8 , wherein the search comprises a web search using a web search engine and an ad search.
| 0.728365 |
8,046,228 | 5 | 9 |
5. A web browser, comprising: an input for receiving a uniform resource location (URL) directive from a speech user agent; an output for sending grammar HTML to the speech user agent; and an input for receiving a URL with arguments from the speech user agent.
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5. A web browser, comprising: an input for receiving a uniform resource location (URL) directive from a speech user agent; an output for sending grammar HTML to the speech user agent; and an input for receiving a URL with arguments from the speech user agent. 9. The web browser of claim 5 , further comprising an output for sending a grammar URL request to the world wide web (WWW).
| 0.530534 |
7,555,742 | 7 | 15 |
7. The computer-readable non-volatile memory of claim 3 wherein said computer-readable instructions control said computer to allow users of said CASE tool editor to enter user input data which defines services within each of said classes of said object model, each of said services being events or transactions and including at least a creation event to create an instance of said class and create links of said instance to instances of classes related to said class, and said instructions controlling said computer to provide the ability, but not the necessity, for each said class for said user of said CASE tool editor to enter user input data which defines a destruction event which breaks links of a given instance of said class to instances of related classes and destroys said given instance of said class, and said instructions controlling said computer to provide the ability, but not the necessity, for each said class to enter user input data which defines a set of modification events whose functionality is defined in said functional model by means of valuations where a valuation is a primitive which creates a relationship in the form of a mathematical or Boolean formula between a variable attribute and an event of a class so as to define how the occurrence of said event affects the value of said variable attribute.
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7. The computer-readable non-volatile memory of claim 3 wherein said computer-readable instructions control said computer to allow users of said CASE tool editor to enter user input data which defines services within each of said classes of said object model, each of said services being events or transactions and including at least a creation event to create an instance of said class and create links of said instance to instances of classes related to said class, and said instructions controlling said computer to provide the ability, but not the necessity, for each said class for said user of said CASE tool editor to enter user input data which defines a destruction event which breaks links of a given instance of said class to instances of related classes and destroys said given instance of said class, and said instructions controlling said computer to provide the ability, but not the necessity, for each said class to enter user input data which defines a set of modification events whose functionality is defined in said functional model by means of valuations where a valuation is a primitive which creates a relationship in the form of a mathematical or Boolean formula between a variable attribute and an event of a class so as to define how the occurrence of said event affects the value of said variable attribute. 15. The computer-readable non-volatile memory of claim 7 wherein said computer-readable instructions, when executed by a computer, control said computer to enable users of said CASE tool editor to enter user input data defining said formulas of said valuations which, when converted to data structures, define valuations which can be of a different type for each variable attribute, each valuation formula relating a specified variable attribute with the same or different events specified in said formula.
| 0.722588 |
8,650,031 | 1 | 20 |
1. A computer-implemented method for executing a voice search, the computer-implemented method comprising: receiving a spoken query; identifying, via an automated speech recognition process, multiple transcription hypotheses based on the spoken query, each respective transcription hypothesis being a proposed textual representation of the spoken query, each respective transcription hypothesis including a speech recognition score that indicates a probability of being a correct conversion of the spoken query to a text query; evaluating a portion of the transcription hypotheses using a co-occurrence identification process, the co-occurrence identification process identifying a frequency that proposed query terms, from each respective transcription hypothesis, co-occur within individual Web documents from a corpus of web documents, the co-occurrence identification process assigning a co-occurrence score to each respective transcription hypothesis from the portion of the transcription hypotheses, the co-occurrence score representing a measure of semantic relation of the proposed query terms based on identified co-occurrence frequencies including identifying non-sequential co-occurrences of the proposed query terms within the individual Web documents; selecting a best transcription hypothesis based on a combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses; and receiving search results, from an information retrieval system, based on a text query corresponding to the best transcription hypothesis.
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1. A computer-implemented method for executing a voice search, the computer-implemented method comprising: receiving a spoken query; identifying, via an automated speech recognition process, multiple transcription hypotheses based on the spoken query, each respective transcription hypothesis being a proposed textual representation of the spoken query, each respective transcription hypothesis including a speech recognition score that indicates a probability of being a correct conversion of the spoken query to a text query; evaluating a portion of the transcription hypotheses using a co-occurrence identification process, the co-occurrence identification process identifying a frequency that proposed query terms, from each respective transcription hypothesis, co-occur within individual Web documents from a corpus of web documents, the co-occurrence identification process assigning a co-occurrence score to each respective transcription hypothesis from the portion of the transcription hypotheses, the co-occurrence score representing a measure of semantic relation of the proposed query terms based on identified co-occurrence frequencies including identifying non-sequential co-occurrences of the proposed query terms within the individual Web documents; selecting a best transcription hypothesis based on a combination of speech recognition scores and co-occurrence scores from the portion of the transcription hypotheses; and receiving search results, from an information retrieval system, based on a text query corresponding to the best transcription hypothesis. 20. The computer-implemented method of claim 1 wherein the co-occurrence score is based upon matching terms in the transcription hypothesis appearing in proximity in the web documents.
| 0.881748 |
8,055,497 | 17 | 19 |
17. A processing system comprising: a processor; a memory coupled to the processor and containing a program that, when executed by the processor, performs an operation for parsing an address, comprising: separating an address into a plurality of tokens; performing an initial pass on the plurality of tokens based on geographic region-specific configuration information for the address to determine at least one candidate classification for each of the tokens in the plurality of tokens, wherein the initial token meaning discovery pass is performed without context-specific information for the address; and performing one or more additional passes on the plurality of tokens based on the geographic region-specific configuration information for the address to determine a final classification of each token in the address, wherein the final classification is selected from the determined candidate classifications for the token, and wherein the one or more additional passes are performed with context-specific information relating the token to one or more other tokens in the plurality of tokens.
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17. A processing system comprising: a processor; a memory coupled to the processor and containing a program that, when executed by the processor, performs an operation for parsing an address, comprising: separating an address into a plurality of tokens; performing an initial pass on the plurality of tokens based on geographic region-specific configuration information for the address to determine at least one candidate classification for each of the tokens in the plurality of tokens, wherein the initial token meaning discovery pass is performed without context-specific information for the address; and performing one or more additional passes on the plurality of tokens based on the geographic region-specific configuration information for the address to determine a final classification of each token in the address, wherein the final classification is selected from the determined candidate classifications for the token, and wherein the one or more additional passes are performed with context-specific information relating the token to one or more other tokens in the plurality of tokens. 19. The processing system of claim 17 , wherein the address comprises a street address.
| 0.724684 |
9,710,548 | 13 | 18 |
13. A system for using user preferences to customize answer output comprising: a computing platform having a processor; a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: extract from a first question one or more user preferences for a first user and one or more sentiment levels for a first user; perform a first semantic search on the first question; receive a plurality of candidate answers from the first semantic search; responsive to determining, by a computer that the first question contains multiple-parts or multiple-steps, retrieve, by a computer, supplemental information regarding at least one of the candidate answers; select one or more of the received candidate answers according to the one or more sentiment levels, or according to the one or more user preferences, or both, and adjust for the retrieved supplemental information; and produce a computer output including the selected one or more candidate answers.
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13. A system for using user preferences to customize answer output comprising: a computing platform having a processor; a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: extract from a first question one or more user preferences for a first user and one or more sentiment levels for a first user; perform a first semantic search on the first question; receive a plurality of candidate answers from the first semantic search; responsive to determining, by a computer that the first question contains multiple-parts or multiple-steps, retrieve, by a computer, supplemental information regarding at least one of the candidate answers; select one or more of the received candidate answers according to the one or more sentiment levels, or according to the one or more user preferences, or both, and adjust for the retrieved supplemental information; and produce a computer output including the selected one or more candidate answers. 18. The system as set forth in claim 13 wherein the program instructions which, when executed by a processor, cause a computing platform to select further comprise program instructions which, when executed by a processor, cause a computing platform to perform a weighting process.
| 0.845985 |
7,725,452 | 11 | 12 |
11. The scheduler system of claim 7 , wherein the threshold value is determined using a score computed for each document identifier in a sample set of document identifiers.
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11. The scheduler system of claim 7 , wherein the threshold value is determined using a score computed for each document identifier in a sample set of document identifiers. 12. The scheduler system of claim 11 , wherein the threshold value is further determined using a target size of a set of documents to be crawled.
| 0.5 |
8,294,017 | 16 | 17 |
16. The machine-readable medium including machine-readable instructions providing a method for creating a music file of claim 11 , wherein vowels are extracted from Genesis.1:1 in the Hebraic language.
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16. The machine-readable medium including machine-readable instructions providing a method for creating a music file of claim 11 , wherein vowels are extracted from Genesis.1:1 in the Hebraic language. 17. The machine-readable medium including machine-readable instructions providing a method for creating a music file of claim 16 , wherein vowels are grouped in groups of 5 vowels.
| 0.5 |
9,298,757 | 7 | 12 |
7. A computer program product comprising one or more non-transitory computer readable storage media storing instructions translatable by one or more processors to perform: generating content vectors for terms in a data set, wherein the content vectors define a similarity metric; generating index vectors for the terms in the data set from the content vectors to access the terms in the data set; and generating bitset signatures from the index vectors to determine similarity with the terms in the data set, wherein the bitset signatures include a first section for positive magnitude values and a second section for negative magnitude values, and generating the bitset signatures from the index vectors comprises: for each of a predetermined number of highest magnitude positive values in the corresponding index vector, setting a corresponding bitset signature value at a corresponding dimension in the first section to a predetermined value; and for each of a predetermined number of highest magnitude negative values in the corresponding index vector, setting a corresponding bitset signature value at a corresponding dimension in the second section to the predetermined value; storing the bitset signatures and content vectors in an index; and performing a search on each of one or more terms in a search query by: accessing a bitset signature and content vector from the index corresponding to a term in the search query; retrieving bitset signatures from the index that are within a predetermined closeness to the accessed bitset signature; selecting content vectors from the index corresponding to the retrieved bitset signatures; identifying the selected content vectors that are within a predetermined similarity to the accessed content vector corresponding to the term in the search query; and returning the terms of the data set corresponding to the identified content vectors.
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7. A computer program product comprising one or more non-transitory computer readable storage media storing instructions translatable by one or more processors to perform: generating content vectors for terms in a data set, wherein the content vectors define a similarity metric; generating index vectors for the terms in the data set from the content vectors to access the terms in the data set; and generating bitset signatures from the index vectors to determine similarity with the terms in the data set, wherein the bitset signatures include a first section for positive magnitude values and a second section for negative magnitude values, and generating the bitset signatures from the index vectors comprises: for each of a predetermined number of highest magnitude positive values in the corresponding index vector, setting a corresponding bitset signature value at a corresponding dimension in the first section to a predetermined value; and for each of a predetermined number of highest magnitude negative values in the corresponding index vector, setting a corresponding bitset signature value at a corresponding dimension in the second section to the predetermined value; storing the bitset signatures and content vectors in an index; and performing a search on each of one or more terms in a search query by: accessing a bitset signature and content vector from the index corresponding to a term in the search query; retrieving bitset signatures from the index that are within a predetermined closeness to the accessed bitset signature; selecting content vectors from the index corresponding to the retrieved bitset signatures; identifying the selected content vectors that are within a predetermined similarity to the accessed content vector corresponding to the term in the search query; and returning the terms of the data set corresponding to the identified content vectors. 12. A computer program product according to claim 7 , wherein the one or more terms in the search query and the terms corresponding to the identified content vectors are used to search the data set.
| 0.5 |
8,156,459 | 1 | 7 |
1. A method of detecting differences between high level block diagram models using text based analysis, comprising: converting a first block diagram-based model and a second block diagram-based model to a first text-based model and a second text-based model, respectively; on a processor, identifying differences between the first text-based model and the second text-based model; merging identified differences into a third block diagram model which has been converted to a plain text format; and displaying the identified differences on a graphical user interface.
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1. A method of detecting differences between high level block diagram models using text based analysis, comprising: converting a first block diagram-based model and a second block diagram-based model to a first text-based model and a second text-based model, respectively; on a processor, identifying differences between the first text-based model and the second text-based model; merging identified differences into a third block diagram model which has been converted to a plain text format; and displaying the identified differences on a graphical user interface. 7. The method of claim 1 , wherein the text-based model converted to is a hardware description language based model.
| 0.815287 |
7,967,194 | 15 | 18 |
15. A method for providing transaction card customization including a centralized issuer hub providing a single point of website integration for applicants in different countries, the method comprising the steps of: routing an applicant from a local issuer country website to a card customization services website for processing the applicant's request for a customized transaction card, the card customization services website allowing the applicant to customize an image to be added to a front surface of the customized transaction card; routing the request to a syndication layer for adding country-specific content to a base website that serves up the dedicated country-specific website for the applicant, wherein the base website includes central features and functionality that make up the transaction card customization software application without including any issuer-specific enhancements, branding, foreign language, colors, artwork and website links; and launching one of a plurality of dedicated country-specific websites for the applicant based upon on a recognized country of origin of the issuer country website.
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15. A method for providing transaction card customization including a centralized issuer hub providing a single point of website integration for applicants in different countries, the method comprising the steps of: routing an applicant from a local issuer country website to a card customization services website for processing the applicant's request for a customized transaction card, the card customization services website allowing the applicant to customize an image to be added to a front surface of the customized transaction card; routing the request to a syndication layer for adding country-specific content to a base website that serves up the dedicated country-specific website for the applicant, wherein the base website includes central features and functionality that make up the transaction card customization software application without including any issuer-specific enhancements, branding, foreign language, colors, artwork and website links; and launching one of a plurality of dedicated country-specific websites for the applicant based upon on a recognized country of origin of the issuer country website. 18. The method of claim 15 , further comprising the step of providing an automatic upgrading of all dedicated websites substantially simultaneously.
| 0.789174 |
8,052,722 | 1 | 4 |
1. A spine implant comprising: a first deflection rod system including a first inner rod and a first outer shell located about said first inner rod, and a first shield that can limit a deflection of the first inner rod and the first outer shell; a second deflection rod system including a second inner rod and a second outer shell located about said second inner rod, and a second shield that can limit a deflection of the second inner rod and the second outer shell; a mount; said first deflection rod system connected to said mount; and said second deflection rod system connected to said mount.
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1. A spine implant comprising: a first deflection rod system including a first inner rod and a first outer shell located about said first inner rod, and a first shield that can limit a deflection of the first inner rod and the first outer shell; a second deflection rod system including a second inner rod and a second outer shell located about said second inner rod, and a second shield that can limit a deflection of the second inner rod and the second outer shell; a mount; said first deflection rod system connected to said mount; and said second deflection rod system connected to said mount. 4. The implant of claim 1 wherein said first inner rod includes Nitinol and said second inner rod includes Nitinol and said first shell includes PEEK and second shell includes PEEK.
| 0.698333 |
8,055,605 | 13 | 14 |
13. The system of claim 12 , wherein the contract resources are travel-related contract resources.
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13. The system of claim 12 , wherein the contract resources are travel-related contract resources. 14. The system of claim 13 , wherein the travel-related contract resources comprise lodging contract resources.
| 0.5 |
7,865,491 | 1 | 7 |
1. A computer-readable storage medium containing a program, which when executed on a computer system performs an operation for accessing data stored in an underlying physical database, comprising: receiving a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in an underlying database; retrieving, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and performing the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation.
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1. A computer-readable storage medium containing a program, which when executed on a computer system performs an operation for accessing data stored in an underlying physical database, comprising: receiving a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in an underlying database; retrieving, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and performing the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. 7. The computer-readable storage medium of claim 1 , wherein the model entity represents an individual, and wherein the linking function identifies additional instances of the model entity that represent individuals related to one another by geographic locations.
| 0.691315 |
6,073,130 | 9 | 13 |
9. A method of presenting results of a search of a structured database containing a plurality of records, the method comprising the steps of: receiving a search query identifying at least two attribute/value pairs, the search query containing no explicit OR statements; comparing the search query to the records in said database; identifying each record in said database matching at least one and less than all of said attribute/value pairs; after said step of identifying, for each record identified in said step of identifying, assigning a ranking; and presenting a list of pointers to each record identified in said step of identifying wherein the order of pointers on said list corresponds to the record ranking assigned to the records corresponding to the pointers.
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9. A method of presenting results of a search of a structured database containing a plurality of records, the method comprising the steps of: receiving a search query identifying at least two attribute/value pairs, the search query containing no explicit OR statements; comparing the search query to the records in said database; identifying each record in said database matching at least one and less than all of said attribute/value pairs; after said step of identifying, for each record identified in said step of identifying, assigning a ranking; and presenting a list of pointers to each record identified in said step of identifying wherein the order of pointers on said list corresponds to the record ranking assigned to the records corresponding to the pointers. 13. The method of claim 9 wherein said search query includes n attribute/value pairs where n is an integer and n.gtoreq.2, and further steps include: identifying a first group of records, which each match at least m attribute/value pairs in said search query where 1.ltoreq.m<n; identifying a plurality of combinations of m attribute/value pairs associated with said first group; determining a matching frequency for each combination of said plurality of combinations of m attribute/value pairs; and ranking each given record in said first group in accordance with a matching frequency for that combination of m attribute/value pairs that matches said given record.
| 0.5 |
9,384,226 | 22 | 26 |
22. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item.
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22. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. 26. The method of claim 22 , wherein the second content item is stored at the user computer at the time the search query is obtained; and wherein the second search answer summary for the second content item indicates that the second content item is stored at the user computer.
| 0.773322 |
8,117,225 | 15 | 68 |
15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system.
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15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. 68. The computer program product of claim 15 , and further comprising: code for identifying at least one additional term by automatically suggesting a plurality of possible terms that are presented in a list; code for performing a second search in connection with the search results, based on the at least one additional term; and code for displaying second search results of the second search.
| 0.74147 |
9,633,671 | 1 | 2 |
1. A media device having a loudspeaker, a microphone, and a digital signal processor comprising: an echo canceller arranged to receive an input signal from the microphone and to receive a reference signal, wherein the echo canceller is configured to subtract one or more linear components of the reference signal from the input signal; a noise suppressor configured to suppress non-linear effects of the reference signal in each of a plurality of frequency bins in the input signal, wherein a degree of suppression provided by the noise suppressor for each frequency bin corresponds to an estimate of residual echo remaining in the respective frequency bin after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency bin; and a speech recognizer arranged to receive a processed input signal from the noise suppressor and to recognize an utterance from the processed input signal, wherein the media device is configured to be controlled responsively to the cognized utterance.
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1. A media device having a loudspeaker, a microphone, and a digital signal processor comprising: an echo canceller arranged to receive an input signal from the microphone and to receive a reference signal, wherein the echo canceller is configured to subtract one or more linear components of the reference signal from the input signal; a noise suppressor configured to suppress non-linear effects of the reference signal in each of a plurality of frequency bins in the input signal, wherein a degree of suppression provided by the noise suppressor for each frequency bin corresponds to an estimate of residual echo remaining in the respective frequency bin after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency bin; and a speech recognizer arranged to receive a processed input signal from the noise suppressor and to recognize an utterance from the processed input signal, wherein the media device is configured to be controlled responsively to the cognized utterance. 2. A media device according to claim 1 , wherein the noise suppressor applies a spectral gain or a binary mask to the input signal in correspondence with the estimated signal-to-noise ratio of near-end speech in the input signal.
| 0.607877 |
9,734,197 | 7 | 10 |
7. A computer program product embodied on a non-transitory computer-readable medium, the computer program product including instructions, which when executed by a computer system, are operable to cause the computer system to perform operations comprising: receiving an input term in a first language format; identifying two different groups of hyperlinks that each link to a same plurality of intermediary documents, wherein the different groups of hyperlinks have anchor texts in different respective language formats, including: identifying a first group of hyperlinks each having a respective first anchor text that includes the input term in the first language format, and identifying a second group of hyperlinks each having a respective second anchor text in a second language format; determining, from all of the second anchor texts of the second group of hyperlinks, a second term in the second language format that corresponds to the input term in the first language format, including: computing a total count of terms, including duplicates, occurring in all of the second anchor texts of the second group of hyperlinks, computing a respective individual count of occurrences, in all of the second anchor texts of the second group of hyperlinks, of each of a plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks, computing a respective score for each of the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks including comparing, for each term of the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks, the respective individual count for the term to the total count of terms occurring in the second anchor texts of the second group of hyperlinks, and designating a highest-scoring term among the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks as the second term in the second language format that corresponds to the input term in the first language format; receiving a first query having the input term in the first language format; generating a revised query that includes the second term in the second language format; obtaining search results using the revised query; and providing the search results obtained using the revised query in response to receiving the first query.
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7. A computer program product embodied on a non-transitory computer-readable medium, the computer program product including instructions, which when executed by a computer system, are operable to cause the computer system to perform operations comprising: receiving an input term in a first language format; identifying two different groups of hyperlinks that each link to a same plurality of intermediary documents, wherein the different groups of hyperlinks have anchor texts in different respective language formats, including: identifying a first group of hyperlinks each having a respective first anchor text that includes the input term in the first language format, and identifying a second group of hyperlinks each having a respective second anchor text in a second language format; determining, from all of the second anchor texts of the second group of hyperlinks, a second term in the second language format that corresponds to the input term in the first language format, including: computing a total count of terms, including duplicates, occurring in all of the second anchor texts of the second group of hyperlinks, computing a respective individual count of occurrences, in all of the second anchor texts of the second group of hyperlinks, of each of a plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks, computing a respective score for each of the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks including comparing, for each term of the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks, the respective individual count for the term to the total count of terms occurring in the second anchor texts of the second group of hyperlinks, and designating a highest-scoring term among the plurality of terms in the second language format that occur in all of the second anchor texts of the second group of hyperlinks as the second term in the second language format that corresponds to the input term in the first language format; receiving a first query having the input term in the first language format; generating a revised query that includes the second term in the second language format; obtaining search results using the revised query; and providing the search results obtained using the revised query in response to receiving the first query. 10. The computer program product of claim 7 , wherein the first language format comprises a first language and the second language format comprises a different, second language.
| 0.526738 |
9,558,400 | 12 | 13 |
12. The system of claim 10 , wherein to create the hierarchical cluster for the strokes in the field based on the distance metrics, the cluster module is configured to cluster two closest strokes with a minimal distance metric and cluster next closest strokes until a stopping criterion is reached.
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12. The system of claim 10 , wherein to create the hierarchical cluster for the strokes in the field based on the distance metrics, the cluster module is configured to cluster two closest strokes with a minimal distance metric and cluster next closest strokes until a stopping criterion is reached. 13. The system of claim 12 , wherein the stopping criterion includes at least one of a threshold inter-cluster distance or a threshold number of clusters.
| 0.5 |
10,152,549 | 1 | 2 |
1. A method comprising: selecting a plurality of n-grams from one or more social content items, each of the n-grams representing a plurality of terms from the one or more social content items, the social content items comprising content corresponding to activity performed by at least one user within a social networking service; assigning a score to each of the plurality of n-grams based on one or more significance criteria; generating one or more candidate suggestions from the plurality of n-grams based on the score of each of the plurality of n-grams, the one or more candidate suggestions including recommended actions to perform within the social networking service; identifying one or more contacts or groups of contacts associated with at least one of the one or more candidate suggestions; and providing the one or more contacts or groups of contacts for display, by the social network service, along with the at least one of the one or more candidate suggestions to facilitate additional user activity within the social networking service.
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1. A method comprising: selecting a plurality of n-grams from one or more social content items, each of the n-grams representing a plurality of terms from the one or more social content items, the social content items comprising content corresponding to activity performed by at least one user within a social networking service; assigning a score to each of the plurality of n-grams based on one or more significance criteria; generating one or more candidate suggestions from the plurality of n-grams based on the score of each of the plurality of n-grams, the one or more candidate suggestions including recommended actions to perform within the social networking service; identifying one or more contacts or groups of contacts associated with at least one of the one or more candidate suggestions; and providing the one or more contacts or groups of contacts for display, by the social network service, along with the at least one of the one or more candidate suggestions to facilitate additional user activity within the social networking service. 2. The method of claim 1 , further comprising: receiving an indication of a request to provide a user with one or more suggestions; and identifying the one or more social content items based on one or more contacts of the user.
| 0.571698 |
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